sharjeelyunus/github-issues-dataset huggingface dataset:
Repository: flutter
Issue: Editable Text after clear has issue with buffer korean input
Labels: a: text input,engine,platform-windows,a: desktop,has reproducible steps,P2,found in release: 3.7,found in release: 3.8,fyi-text-input,team-windows,triaged-windows

$ flutter --version
Flutter 3.7.4 • channel stable • https://github.com/flutter/flutter.git
Framework • revision b4bce91dd0 (3 days ago) • 2023-02-21 09:50:50 +0800
Engine • revision 248290d6d5
Tools • Dart 2.19.2 • DevTools 2.20.1

I have created a main.dart with the minimal steps to produce this issue but basically this might be related specifically to the way the Korean Keyboard has to build each character in a syllable. In a single syllable, the character can be made of 2 to 5 korean letters equivalent to the english alphabet. In the example syllable 광 (gwang), it is made up of 4 letters  (ㄱ ㅗ ㅏ ㅇ) but the keyboard has to keep a buffer of collected letters to build up to the full character. When the clear is called without clearing the buffer and breaking it, it seems to cause weird input until you deselect and re-select the Editable Text widget.

In the following modified Flutter Demo main project, you enter the text and when it is equal to the text to enter, the clear is called followed by the setState. From that point forward random characters are inputted until you unselect and reselect the editable text, clearing the buffer.

There are two methods in here, one producing the problem called onValueChangeWithIssue and the other not producing the problem called onValueChangeWithoutIssue. The only difference is that FocusNode.unfocus and FocusNode.requestFocus is being called. The problem with this fix is that on android devices, it produces undesirable behavior with the virtual keyboard and when a bluetooth keyboard is connected.

In the app I am building, I am not sure what the best workaround for this issue is.

This problem exists in the latest flutter as of 2023/02/24.

[main.dart.txt](https://github.com/flutter/flutter/files/10820238/main.dart.txt)

![image](https://user-images.githubusercontent.com/12561877/221080541-0ba84bfd-ddef-4636-a4af-f1e2eee50944.png)
Repository: go
Issue: proposal: os: expose all possible path and pathlist separators
Labels: Proposal

### Description

As of right now, `os` (and by extension, `filepath`) package exports `os.PathSeparator` and `os.PathListSeparator` constants that are tied to the system the binary is built on (by //go:build constraints). So, for example, on unix systems, these would be `/` and `:`. The problem with this approach is that there is no way to reference a Windows separator from a unix-built binary, and vice versa. While this might be a rare occasion, sometimes there is a need for that (i.e. if some unix-style binary requires unix-style separators even when executed in Windows environment, or if you need to render a help docstring for the user).

Of course, you can always get around this and just declare your own separators but that just feels hacky when there is an exposed const in the standard package. 

I'd be happy to submit a PR for this

### Proposed changes

What i propose is adding new constants to the `os` package that would reference each style, and only typealiasing them in `_<os>.go` files. This will not break existing external API, only expose new constants (that are already present in the library, but just not exposed due to build constraints).

In `os` package:

```go
// src/os/path_unix.go

const (
	PathSeparator     = UnixPathSeparator // OS-specific path separator
	PathListSeparator = UnixPathListSeparator // OS-specific path list separator
)
```

```go
// src/os/path_windows.go

const (
	PathSeparator     = WindowsPathSeparator // OS-specific path separator
	PathListSeparator = WindowsPathListSeparator // OS-specific path list separator
)
```

```go
// path.go

const (
	UnixPathSeparator     = '/' // unix-specific path separator
	UnixPathListSeparator = ':' // unix-specific path list separator
        WindowsPathSeparator     = '\\' // windows-specific path separator
	WindowsPathListSeparator = ';'  // windows-specific path list separator
)
```
Repository: PowerToys
Issue: File Locksmith问题反馈
Labels: Issue-Bug,Priority-2,Product-File Locksmith

### Microsoft PowerToys version

0.67.1

### Installation method

PowerToys auto-update, Microsoft Store

### Running as admin

Yes

### Area(s) with issue?

File Locksmith

### Steps to reproduce

文件删除、移动或拔出U盘时提示文件被占用。使用该功能检查锁定进程，显示未被任何程序占用。望解决，ᠪᠠᠨᡳᡥᠠ（巴尼哈/谢谢）

### ✔️ Expected Behavior

扫描到占用程序，并解除占用。

### ❌ Actual Behavior

扫描不到任何信息。

### Other Software

_No response_
Repository: nvm
Issue: Feature Request: Unofficial builds
Labels: feature requests,pull request wanted

@ljharb We recently talked about how it makes no sense to have a POSIX compliant installer, since on embedded systems you most likely need to compile node yourself, so the benefit of not installing bash is neglectable. 

The reason why nvm doesn't work on Alpine Linux, is because the official builds are compiled against glibc, but there are [unofficial builds](https://unofficial-builds.nodejs.org/download/release/) for musl that should work.

It would be beneficial to have a way to define a different source for node versions, so that I can use nvm on Alpine in the first place.

node releases on the Alpine package manager are tied to repository branches, meaning accessing an older node version means to run an ancient OS as well. I'd love if you could look into it.

Related: https://github.com/nodejs/build/issues/1140
Repository: deno
Issue: `node/http.ts` `http.request` should support `socketPath` option
Labels: bug

**Describe the bug**

**Steps to Reproduce**

<!--
Example
1. Create a file with the contents ...
2. Create a script with the contents ...
3. Execute the command ...
4. See error
-->

```ts
> var Docker = (await import('npm:dockerode@3.3.4')).default
undefined
> var docker = new Docker({socketPath: '/var/run/docker.sock'});
undefined
> await docker.listContainers()
Uncaught TypeError: error sending request for url (http://localhost/containers/json): error trying to connect: tcp connect error: Connection refused (os error 111)
    at async mainFetch (internal:ext/fetch/26_fetch.js:267:14)
    at async fetch (internal:ext/fetch/26_fetch.js:491:9)
    at async ClientRequest._final (https://deno.land/std@0.177.0/node/http.ts:147:7)
```

**Expected behavior**

<!-- A clear and concise description of what you expected to happen. -->
```ts
> var Docker = (await import('dockerode')).default
undefined
> var docker = new Docker({socketPath: '/var/run/docker.sock'});
undefined
> await docker.listContainers()
[
  {
    Id: ...
```

**Environment**

<!-- please complete the following information -->

- OS: [e.g. Ubuntu 20.04, MacOS 11] ArchLinux
- deno version: 1.30.3
- std version: https://deno.land/std@0.177.0/node/http.ts:147:7
Repository: node
Issue: Different behavior of { a: 1 } in the REPL and the debugger
Labels: repl,debugger

### Version

v19.7.0

### Platform

_No response_

### Subsystem

_No response_

### What steps will reproduce the bug?

Evaluating `{ a: 1 }` in the REPL and the debugger have different result

```
% node
> { a: 1 }
{ a: 1 }
```

```
% node inspect app.js
debug> { a: 1 }
1
```

### How often does it reproduce? Is there a required condition?

Always

### What is the expected behavior?

Like REPL, the result of debugger will be
```
% node inspect app.js
debug> { a: 1 }
{ a: 1 }
```

### What do you see instead?

```
% node inspect app.js
debug> { a: 1 }
1
```

### Additional information

The results of `{ a: 1 }` in other runtimes: 

- ChromeDevTools: `{ a: 1 }`

- Safari WebInspector: `{ a: 1 }`

We have a similar bug ([#45964](https://github.com/nodejs/node/issues/45964)) but we have not fixed yet and it was closed
Repository: go
Issue: encoding/json: misleading error for end-of-input in an escape sequence
Labels: NeedsInvestigation

### What version of Go are you using (`go version`)?

<pre>
$ go version
go version go1.20.1 linux/amd64
</pre>

### Does this issue reproduce with the latest release?

Yes.

### What operating system and processor architecture are you using (`go env`)?

<details><summary><code>go env</code> Output</summary><br><pre>
$ go env
GO111MODULE=""
GOARCH="amd64"
GOBIN=""
GOCACHE="/home/lukeshu/.cache/go-build"
GOENV="/home/lukeshu/.config/go/env"
GOEXE=""
GOEXPERIMENT=""
GOFLAGS=""
GOHOSTARCH="amd64"
GOHOSTOS="linux"
GOINSECURE=""
GOMODCACHE="/home/lukeshu/go/pkg/mod"
GONOPROXY=""
GONOSUMDB=""
GOOS="linux"
GOPATH="/home/lukeshu/go"
GOPRIVATE=""
GOPROXY="https://proxy.golang.org,direct"
GOROOT="/usr/lib/go"
GOSUMDB="sum.golang.org"
GOTMPDIR=""
GOTOOLDIR="/usr/lib/go/pkg/tool/linux_amd64"
GOVCS=""
GOVERSION="go1.20.1"
GCCGO="gccgo"
GOAMD64="v1"
AR="ar"
CC="gcc"
CXX="g++"
CGO_ENABLED="1"
GOMOD="/dev/null"
GOWORK=""
CGO_CFLAGS="-O2 -g"
CGO_CPPFLAGS=""
CGO_CXXFLAGS="-O2 -g"
CGO_FFLAGS="-O2 -g"
CGO_LDFLAGS="-O2 -g"
PKG_CONFIG="pkg-config"
GOGCCFLAGS="-fPIC -m64 -pthread -Wl,--no-gc-sections -fmessage-length=0 -fdebug-prefix-map=/run/user/1000/tmpdir/go-build3465712561=/tmp/go-build -gno-record-gcc-switches"
</pre></details>

### What did you do?

<!--
If possible, provide a recipe for reproducing the error.
A complete runnable program is good.
A link on go.dev/play is best.
-->

I fed the JSON parser a truncated JSON document that has a backslash as the final rune.

```go
package main

import (
	"encoding/json"
	"fmt"
)

func main() {
	var obj any
	err := json.Unmarshal([]byte(`"\`), &obj)
	fmt.Println(err)
}
```

https://go.dev/play/p/KxvQ6lpnT7I

### What did you expect to see?

I expected the error to be `unexpected end of JSON input`

### What did you see instead?

I saw the error `invalid character ' ' in string escape code`, which is a nonsense error as there is no ` ` character in the input at all!

`json.Compact` and `json.Indent` have the same issue, while `json.Decoder.Decode` correctly returns `io.ErrUnexpectedEOF`.
Repository: angular
Issue: Request a totally covered tastcase in Injector.get when default value is provided
Labels: area: core,core: di

### Which @angular/* package(s) are relevant/related to the feature request?

core

### Description

In issue [#47109](https://github.com/angular/angular/issues/47109), it pointed that the default value not worked when use `InjectFlags.Host` mode.

```
const d = injector.get(NON_PROVIDED_TOKEN, 'default value', InjectFlags.Host);
```

But, at the same situation, `InjectFlags.Self` mode will caught error either. The problom could only be found in `ElementInjector` but not in `ModuleInjector`, so both `InjectFlags.Self` and `InjectFlags.Host` are involved.

[Here](https://stackblitz.com/edit/angular-qpfnex?file=src%2Fmain.ts) is my repo with ng14.2.0.

---
```
Angular CLI: 14.2.10       
Node: 16.15.0
Package Manager: npm 8.5.5 
OS: win32 x64

Angular: 14.2.0
... animations, common, compiler, compiler-cli, core, forms
... platform-browser, platform-browser-dynamic, router

Package                         Version
---------------------------------------------------------
@angular-devkit/architect       0.1402.10
@angular-devkit/build-angular   14.2.10
@angular-devkit/core            14.2.10
@angular-devkit/schematics      14.2.10
@angular/cli                    14.2.10
@schematics/angular             14.2.10
rxjs                            7.5.7
typescript                      4.7.4
```
---

Although, this issue is fixed in this [commit](https://github.com/angular/angular/pull/47242/commits/82e6c894c5f3b5868c8f45a71bce5f5af1791fbe), and fortunately, `InjectFlags.Self` situation would be fixed together. But It is a little pity that the test case in commit not covered the `InjectFlags.Self` situation. I suppose maybe it will be a hidden trouble unless a fully covered testcase be offered.


### Proposed solution

Make a illustration about `InjectFlags.Self` situation and add a testcase about InjectFlags.Self` situation.

### Alternatives considered

no
Repository: stable-diffusion-webui
Issue: Integration of inifinite zoom video generation into the app[Feature Request]: 
Labels: enhancement

### Is there an existing issue for this?

- [X] I have searched the existing issues and checked the recent builds/commits

### What would your feature do ?

I think it would be great to have this tool integrated into the A1111 app
https://github.com/BalintKomjati/smooth-infinite-zoom

### Proposed workflow

sorry at this stage i cannot make good recommendation

### Additional information

_No response_
Repository: stable-diffusion-webui
Issue: [Bug]: ERROR: Could not find a version that satisfies the requirement aiohttp (from gradio) (from versions: none) ERROR: No matching distribution found for aiohttp
Labels: bug-report

### Is there an existing issue for this?

- [X] I have searched the existing issues and checked the recent builds/commits

### What happened?

ERROR: Could not find a version that satisfies the requirement aiohttp (from gradio) (from versions: none)
ERROR: No matching distribution found for aiohttp

### Steps to reproduce the problem

ERROR: Could not find a version that satisfies the requirement aiohttp (from gradio) (from versions: none)
ERROR: No matching distribution found for aiohttp

### What should have happened?

ERROR: Could not find a version that satisfies the requirement aiohttp (from gradio) (from versions: none)
ERROR: No matching distribution found for aiohttp

### Commit where the problem happens

ERROR: Could not find a version that satisfies the requirement aiohttp (from gradio) (from versions: none) ERROR: No matching distribution found for aiohttp

### What platforms do you use to access the UI ?

_No response_

### What browsers do you use to access the UI ?

_No response_

### Command Line Arguments

```Shell
ERROR: Could not find a version that satisfies the requirement aiohttp (from gradio) (from versions: none)
ERROR: No matching distribution found for aiohttp
```


### List of extensions

ERROR: Could not find a version that satisfies the requirement aiohttp (from gradio) (from versions: none)
ERROR: No matching distribution found for aiohttp

### Console logs

```Shell
ERROR: Could not find a version that satisfies the requirement aiohttp (from gradio) (from versions: none)
ERROR: No matching distribution found for aiohttp
```


### Additional information

_No response_
Repository: transformers
Issue: Add TensorFlow Whisper model for audio classification
Labels: TensorFlow,Good Second Issue,Feature request

### Feature request

The PR https://github.com/huggingface/transformers/pull/21754 adds the PyTorch version of `WhisperForAudioClassification`. It would be great to add the TensorFlow equivalent.

### Motivation

Whisper is an encoder-decoder model for speech recognition. However, we can repurpose the model for other speech tasks, such as _audio classification_.

Audio classification is the task of mapping from an input speech sequence to a single class prediction. For more details, refer to the task page on the Hub: https://huggingface.co/tasks/audio-classification

For audio classification, we only require a _single_ model output. Thus, we do not need the auto-regressive generation capacities of the Whisper decoder (which is used to generate a _sequence_ of text tokens during speech recognition). Instead, we can just use the Whisper encoder to get hidden states, and add a classification head on top to make class label predictions.

This is analogous to using a Wav2Vec2 model for audio classification: the Wav2Vec2 encoder is used to get hidden states, and a classification head added on top to make class label predictions.

The PR https://github.com/huggingface/transformers/pull/21754 adds the PyTorch version of `WhisperForAudioClassification`. It required adding a projection layer and classification layer on top of the `WhisperEncoder`. For more details, refer directly to the pull request.

It would be great to add the TensorFlow equivalent of this model for cross-framework support.

The most difficult part of this PR will be getting the model tester to work. You can see from the PyTorch PR that we require a standalone tester for the audio classification model. This is because the original Whisper model is an encoder-decoder model, but the audio classification model is an encoder-only model. Thus, we require different testing logic.

### Your contribution

Opening this one up to the community! If you're interested in tackling this, free to drop a comment in this thread and open a PR when you're ready. More than happy to answer any questions / queries about this integration!
Repository: transformers
Issue: Add TensorFlow Wav2Vec2 for sequence classification
Labels: TensorFlow,Good Second Issue,Feature request

### Feature request

Wav2Vec2 is one of the most popular speech recognition models, used over 2 million times monthly. In the PyTorch modelling code, we have Wav2Vec2 for speech recognition _and_ Wav2Vec2 for audio classification. However, in TensorFlow, we only have Wav2Vec2 for speech recognition. It would be great to add Wav2Vec2 for audio classification to the TensorFlow modelling code for cross-framework equivalence!

### Motivation

The audio classification class for PyTorch Wav2Vec2 lives under `Wav2Vec2ForSequenceClassification`:
https://github.com/huggingface/transformers/blob/13489248fa8f2cda7503628204f8f43b108797a2/src/transformers/models/wav2vec2/modeling_wav2vec2.py#L1745

For this feature request, we'll need to port this PyTorch code into TensorFlow to create an equivalent TensorFlow class, `TFWav2Vec2ForSequenceClassification`.

This means adding a projection layer and classification layer on top of the base `TFWav2Vec2Model`. See the PyTorch code for reference:
https://github.com/huggingface/transformers/blob/13489248fa8f2cda7503628204f8f43b108797a2/src/transformers/models/wav2vec2/modeling_wav2vec2.py#L1753-L1758

To check our that our implementation is correct, we can do one forward pass of the PyTorch model and a forward pass of the TensorFlow model with the same inputs. If the output logits are to within 1e-5, we know that our TensorFlow model is correct ✅. We can then enable PT-TF cross tests in the modelling file such that these checks are performed by the CI.

### Your contribution

Opening this one up to the community! If you're interested in tackling this, free to drop a comment in this thread and open a PR when you're ready. More than happy to answer any questions / queries about this integration!
Repository: stable-diffusion-webui
Issue: [Bug]: SwinIR 4x keeps crashing Python
Labels: bug-report,platform:mac

### Is there an existing issue for this?

- [X] I have searched the existing issues and checked the recent builds/commits

### What happened?

Upscale with SwinIR 4x keeps crash.

### Steps to reproduce the problem

1. Generate or pick an existing picture, 512*512 or 512*768
2. Send it to Extra
3. Select SwinIR 4x in dropdown menu
4. Hit the generate button and the system warning pops up: Python quit unexpectedly.

### What should have happened?

It should work like R-ESRGAN 4x+ without problems.

### Commit where the problem happens

0cc0ee1b

### What platforms do you use to access the UI ?

MacOS

### What browsers do you use to access the UI ?

Google Chrome

### Command Line Arguments

```Shell
--upcast-sampling --opt-sub-quad-attention --use-cpu interrogate
```


### List of extensions

ControlNet
Additional Networks

### Console logs

```Shell
SwinIR tiles:   0%|                                                                               | 0/9 [00:00<?, ?it/s]loc("mps_multiply"("(mpsFileLoc): /AppleInternal/Library/BuildRoots/9e200cfa-7d96-11ed-886f-a23c4f261b56/Library/Caches/com.apple.xbs/Sources/MetalPerformanceShadersGraph/mpsgraph/MetalPerformanceShadersGraph/Core/Files/MPSGraphUtilities.mm":228:0)): error: input types 'tensor<1x36864x480xf16>' and 'tensor<1xf32>' are not broadcast compatible
LLVM ERROR: Failed to infer result type(s).
[1]    4994 abort      ./webui.sh
/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/multiprocessing/resource_tracker.py:224: UserWarning: resource_tracker: There appear to be 1 leaked semaphore objects to clean up at shutdown
  warnings.warn('resource_tracker: There appear to be %d '
```


### Additional information

Mac mini M1 + 16GB ram + 512GB SD + Ventura 13.2.1
Repository: pytorch
Issue: Extend docs - Fixing out of memory with python garbage collection
Labels: module: docs,module: memory usage,triaged

### 📚 The doc issue

I suggest to extend https://pytorch.org/docs/stable/notes/faq.html to include a section about the python garbage collector, which is missing.

To be specific, we've now encountered several scenarios where we hit the following case:

Due to other processing during the training loop (in one case the data loader was loading complex data structures, in the other case the main loop created complex tensorboard logs), the garbage collector is triggered for gen0 and gen1, moving a few of those large tensors to gen2 (only about 10-20 objects, but a few hundred megabytes on GPU). Thus, these large tensors will not be released immediately. After adding a `gc.collect()` every nth iteration (or specifically, after each of these costly iterations), the leak was gone. An alternative/addition could be to call `gc.freeze()` before the loop, which will clear the gen2, thus reducing the number of required objects to perform gc gen2 and also reduce the gen2 collection overhead.

Detailed explanation: Because [gen2 gc will only trigger](https://devguide.python.org/internals/garbage-collector/#gc-oldest-generation) if `long_lived_pending / long_lived_total > 0.25` and there are already a few hundred thousand objects in gen2 after startup, it will not trigger before a lot of these large tensors end up in gen2. As an example with numbers: Assuming there are 350.000 objects in `long_lived_total` (which is approx the number I see when in the inference loop), you'd need 87.500 new objects in gen2 before gen2 gc would be triggered, which would need ~5k iterations. This will yield an OOM before ever being triggered.

### Suggest a potential alternative/fix

The suggested addition:

**Python garbage collection**: If you create many python objects during your loop(s), consider calling the Python garbage collector periodically with `gc.collect()` and/or freeze objects to keep generation 2 small by calling `gc.freeze()` after initialization before entering your loop(s). Read more about python garbage collection [here](https://devguide.python.org/internals/garbage-collector).


Thanks for considering this addition!

cc @svekars @carljparker