sharjeelyunus/github-issues-dataset huggingface dataset:
Repository: ant-design
Issue: Input.Password component doesn't get initial value from Form on SSR (Next.js)
Labels: 🐛 Bug,help wanted,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.

### Reproduction link
[![Edit on CodeSandbox](https://codesandbox.io/static/img/play-codesandbox.svg)](https://codesandbox.io/s/interesting-http-ox2xb?file=/pages/index.js)

### Steps to reproduce
open Next.js application
1. Create Form component and set initial values 
2. In Form.Item Create Input.Password component and set name as in initial value

### What is expected?
Input.Password component should get initial value and show it in input

### What is actually happening?
It doesn't shows initial value, only after focusing it updates value

| Environment | Info |
|---|---|
| antd | 4.17.2 |
| React | 17.0.2 |
| System | MacOS 11.1 |
| Browser | Google Chrome 96.0.4664.55 |


<!-- generated by ant-design-issue-helper. DO NOT REMOVE -->
Repository: godot
Issue: SplitContainer dragger does nothing when dragged if the container is too small
Labels: confirmed,documentation,topic:gui

### Godot version

3.4.stable

### System information

Windows 10, GLES3

### Issue description

SplitContainer dragger doesn't work in sub-viewport.

### Steps to reproduce

1. set up ViewportContainer - Viewport - HSplitContainer/VSplitContainer (or Use ViewportTexture on TexutreRect/Meshes and `viewport.input(event)` to forward inputs).
2. drag SplitContainer's dragger.
4. will not change size of SplitContainer's children.

### Minimal reproduction project

[SplitContainerBug.zip](https://github.com/godotengine/godot/files/7666161/SplitContainerBug.zip)
Repository: pytorch
Issue: `torch.sparse.softmax` and `torch.sparse.log_softmax` do not support negative dim.
Labels: module: sparse,triaged,Stale

## 🐛 Bug

`torch.sparse.softmax` and `torch.sparse.log_softmax` do not support negative dim like `torch.nn.functional.softmax`.
## To Reproduce

```python
import torch
input = torch.rand(torch.Size([2, 2]))
dim = -1
output = torch.nn.functional.softmax(input, dim=dim)
# succeed

input = input.to_sparse()
res2 = torch.sparse.softmax(input, dim=dim).to_dense()
# RuntimeError: : dim must be non-negative and less than input dimensions
```

```python
import torch
input = torch.rand(torch.Size([2, 2]))
dim = -1
output = torch.nn.functional.log_softmax(input, dim=dim)
# succeed

input = input.to_sparse()
res2 = torch.sparse.log_softmax(input, dim=dim).to_dense()
# RuntimeError: : dim must be non-negative and less than input dimensions
```

## Expected behavior

They should have the same behavior with `torch.nn.functional.`

## Environment

 - PyTorch Version (e.g., 1.0): 1.10.0
 - OS (e.g., Linux): MacOS
 - How you installed PyTorch (`conda`, `pip`, source): pip
 - Python version: 3.9.6
 - CUDA/cuDNN version: none
 - GPU models and configuration: none

## Additional context

<!-- Add any other context about the problem here. -->


cc @nikitaved @pearu @cpuhrsch @IvanYashchuk
Repository: pytorch
Issue: Feature Request: CUDA torch.histogram (and histogramdd)
Labels: module: bootcamp,feature,module: cuda,triaged,actionable,module: sorting and selection

## 🐛 Bug

<!-- A clear and concise description of what the bug is. -->

## To Reproduce

Steps to reproduce the behavior:

`torch.histogram(torch.tensor([1., 2, 3]).cuda(), bins=4)`

## Expected behavior

Execution without error

## Environment

Please copy and paste the output from our
[environment collection script](https://raw.githubusercontent.com/pytorch/pytorch/master/torch/utils/collect_env.py)
(or fill out the checklist below manually).

You can get the script and run it with:
```
PyTorch version: 1.10.0
Is debug build: False
CUDA used to build PyTorch: 11.3
ROCM used to build PyTorch: N/A

OS: Ubuntu 20.04.3 LTS (x86_64)
GCC version: (Ubuntu 9.3.0-17ubuntu1~20.04) 9.3.0
Clang version: Could not collect
CMake version: Could not collect
Libc version: glibc-2.31

Python version: 3.9.5 (default, Jun  4 2021, 12:28:51)  [GCC 7.5.0] (64-bit runtime)
Python platform: Linux-5.10.0-9-amd64-x86_64-with-glibc2.31
Is CUDA available: True
CUDA runtime version: Could not collect
GPU models and configuration:
GPU 0: NVIDIA GeForce RTX 3090

Nvidia driver version: 495.29.05
cuDNN version: Could not collect
HIP runtime version: N/A
MIOpen runtime version: N/A

Versions of relevant libraries:
[pip3] numpy==1.21.2
[pip3] torch==1.10.0
[pip3] torch-cluster==1.5.9
[pip3] torch-geometric==2.0.2
[pip3] torch-scatter==2.0.9
[pip3] torch-sparse==0.6.12
[pip3] torch-spline-conv==1.2.1
[pip3] torchaudio==0.10.0
[pip3] torchvision==0.11.1
[conda] blas                      1.0                         mkl
[conda] cudatoolkit               11.3.1               h2bc3f7f_2
[conda] ffmpeg                    4.3                  hf484d3e_0    pytorch
[conda] mkl                       2021.4.0           h06a4308_640
[conda] mkl-service               2.4.0            py39h7f8727e_0
[conda] mkl_fft                   1.3.1            py39hd3c417c_0
[conda] mkl_random                1.2.2            py39h51133e4_0
[conda] numpy                     1.21.2           py39h20f2e39_0
[conda] numpy-base                1.21.2           py39h79a1101_0
[conda] pyg                       2.0.2           py39_torch_1.10.0_cu113    pyg
[conda] pytorch                   1.10.0          py3.9_cuda11.3_cudnn8.2.0_0    pytorch
[conda] pytorch-cluster           1.5.9           py39_torch_1.10.0_cu113    pyg
[conda] pytorch-mutex             1.0                        cuda    pytorch
[conda] pytorch-scatter           2.0.9           py39_torch_1.10.0_cu113    pyg
[conda] pytorch-sparse            0.6.12          py39_torch_1.10.0_cu113    pyg
[conda] pytorch-spline-conv       1.2.1           py39_torch_1.10.0_cu113    pyg
[conda] torchaudio                0.10.0               py39_cu113    pytorch
[conda] torchvision               0.11.1               py39_cu113    pytorch
```


cc @ezyang @gchanan @zou3519 @ngimel
Repository: rust
Issue: Static Library with LTO option not working properly
Labels: A-LTO

Greatings!!

We are facing a strange issue while building rust static library with "-Clinker-plugin-lto". On linking the generated library to C base results in linker error as below.

Fatal error: L6120U: Member mylibv7a.mylibv7a.e0989cce-cgu.0.rcgu.o in library libmylibv7a.so cannot be loaded. It is an LLVM bitcode file but the linker only accepts bitcode wrapped in an ELF object file. 

When we checked more it is observed that the ELF header is corrupted in generated library. 

>arm-none-eabi-readelf -a liblib.a >test.out
readelf: Error: Not an ELF file - it has the wrong magic bytes at the start

Additional Details:
rustc --version
rustc 1.57.0 (f1edd0429 2021-11-29)

Build command:
rustc -Clinker-plugin-lto --crate-type=staticlib src/lib.rs --target=armv7a-none-eabi 

Looks like this issue is there with all targets, kindly please look into this issue on priority and suggest us a fix to resolve it.

Thanks
Siju
Repository: go
Issue: proposal: math: MinOf and MaxOf for generic numeric limits
Labels: Proposal

Currently when writing a function involving a generic numeric type, there's no easy way to determine the maximum or minimum possible value of that type, because the `math.Min*` and `math.Max*` constants are all type-specific.

I propose that we add the following functions to the `math` package:

```
// MinOf returns the minimum possible value of type T.
func MinOf[T contraints.Integer | constraints.Float]() T

// MaxOf returns the maximum possible value of type T.
func MaxOf[T contraints.Integer | constraints.Float]() T
```

It's currently not possible to write the above functions without using reflection until https://github.com/golang/go/issues/45380
is fixed, but here's an approximation:

https://gotipplay.golang.org/p/0i3Wc7i4dJs
Repository: create-react-app
Issue: Rebuilding linked package written in typescript breaks the dev server and you need to restart it every time
Labels: issue: proposal,needs triage

If you link some package with `yarn link`, written in typescript to your cra app and you start the dev server with `yarn start`, when you rebuild that package, it will break the dev server and you need to restart it again. The error looks like `Error: ENOENT: no such file or directory`. My question is, is there a way around this or some way to solve this?
Repository: pytorch
Issue: [feature request] Accepting python scalar inputs for torch.minimum/torch.maximum and friends
Labels: triaged,module: distance functions

It will simplify the user code and will allow to use some placeholder default values like float('inf') (btw torch.minimum could be nop in this case).

```python
>>> torch.rand(3, 4).mul(5.0)
# works

>>> torch.rand(3, 4).minimum(5.0)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
TypeError: minimum(): argument 'other' (position 1) must be Tensor, not float

>>> torch.rand(3, 4).minimum(torch.tensor(5.0))
# works
```
Repository: flutter
Issue: Update `flutter-dashboard`
Labels: team-infra,P3,triaged-infra

https://github.com/apps/flutter-dashboard should be updated

- description has broken link
- website is outdated, I think
- name is outdated
Repository: svelte
Issue: [Site]: Explain How to Format Inputs in the Tutorials
Labels: documentation

### Describe the problem

It's not readily apparent from the docs how to format `input`s (at least not for beginners). This can be a significant source of frustration/confusion. I think this is especially true for devs coming from other frameworks, where people are used to easily forcing inputs to adhere to state variables.

I've spent a good few hours between days trying to figure out how to make a money-formatted `input` element in `Svelte`. I almost opened a new issue in ignorance asking for one-way data-binding from `state` to `element` (like in React for `input`s) until I saw #6197, and then saw Rich mention masking in #2446.

### Describe the proposed solution

I believe the `Tutorials` would benefit greatly from a brief explanation on this. Intuitively, when I was trying to figure out how to format my `input`s, I searched the part of the tutorials that talked about inputs. Perhaps a new section could be added called `Formatted Inputs` or `Masked Inputs`. I know this is under the `binding`s section, but since it relates to `binding` and to the order of directives, I think this is a proper location.

Whatever comments are made, the markup would probably include something like
```html
<input type="text" on:input={handleInput} bind:value={value} />
```

with the script being something like

```js
let value;

function handleInput(event) {
  if (someConditionIsMet) {
    value = event.target.value; // or event.currentTarget.value
    // Maybe also apply formatting
    return;
  }

  // Do not change the input's value if condition is not met
  event.target.value = value;
}
```

### Alternatives considered

Alternatively, something like `action`s could be used in the tutorial... which might influence the location of this section. The important thing to me would be whatever makes things clearer/easier. I would think that the previous approach would require less of an established foundation for beginners.

This information could also be placed somewhere outside of the docs. But it would be great to have some kind of clear base example easily accessible for all people.

### Importance

would make my life easier
Repository: node
Issue: Project crashed after Worker.terminate()
Labels: windows,worker

### Version

14.6

### Platform

Windows 10

### Subsystem

_No response_

### What steps will reproduce the bug?

Not sure

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

I am working with the worker threads and it is working fine . i am able to execute stuff in worker thread but the problem is the worker thread is not getting exit on its own . so i am using process.exit(0) or worker.terminate() 
and it get exits also. 
but after that if i hit the api again then my project crashes with 
Process exited with code 3221225477

what is the issue

### What is the expected behavior?

_No response_

### What do you see instead?

_No response_

### Additional information

_No response_
Repository: flutter
Issue: Use gtk4 for linux desktop
Labels: c: new feature,engine,platform-linux,c: proposal,a: desktop,P3,team-linux,triaged-linux

<!-- Thank you for using Flutter!

     If you are looking for support, please check out our documentation
     or consider asking a question on Stack Overflow:
      * https://flutter.dev/
      * https://api.flutter.dev/
      * https://stackoverflow.com/questions/tagged/flutter?sort=frequent

     If you have found a bug or if our documentation doesn't have an answer
     to what you're looking for, then fill out the template below. Please read
     our guide to filing a bug first: https://flutter.dev/docs/resources/bug-reports
-->

## Use case

Currently linux desktop flutter apps are created with GTK3. GTK4 brings border-radius to the bottom windows and a bright window border in the dark theme. It would be nice to benefit from these visual changes in flutter linux desktop apps

## Proposal

<!--
     Briefly but precisely describe what you would like Flutter to be able to do.

     Consider attaching something showing what you are imagining:
      * images
      * videos
      * code samples

     Does this have to be provided by Flutter directly, or can it be provided
     by a package on pub.dev/flutter? If so, maybe consider implementing and
     publishing such a package rather than filing a bug.
-->

Upgrade the linux desktop flutter apps to use gtk4 or add a second option to create linux desktop windows with gtk4 instead.

Thanks in advance

CC @robert-ancell
Repository: pytorch
Issue: Extend composite compliant testing to backward formulas
Labels: triaged,Stale,module: __torch_dispatch__

## 🚀 Feature

"Composite compliant testing" checks that a composite operation works for Tensor-subclass-like Tensors (aka Tensor subclasses and Tensors without storage, like meta tensors). There are a class of backward formulas that are incompatible with Tensor subclasses due to the presence of in-place operations or .data_ptr() calls.

For example, consider the following:
```
torch.zeros(input.sizes(), grad.options()).diagonal().copy_(input)
```
If `input` is a Tensor subclass, but `grad` is a normal Tensor, then this operation will return us a regular Tensor as the gradient, not a Tensor subclass! In the past, both vmap and NestedTensor have faced this problem.

## Motivation

As Tensor subclasses become more common, we want more of PyTorch to work with them.

## Pitch

We should:
1. extend composite compliant testing to backward formulas
2. extend composite compliant testing to catch in-place operations that are incompatible with tensor subclasses.

## Alternatives

n/a


cc @albanD @zou3519
Repository: material-ui
Issue: [Snackbar] Screen reader not reading a snackbar when triggered from a button within a dialog
Labels: bug 🐛,accessibility,component: snackbar

### Duplicates

- [X] I have searched the existing issues

### Latest version

- [X] I have tested the latest version

### Current behavior 😯

When snackbars are triggered from a button within a dialog they are not read by the screen reader.

### Expected behavior 🤔

When snackbars are triggered from a button within a dialog they should be read by the screen reader.

### Steps to reproduce 🕹

**Steps**

1. User launches NVDA or JAWS
2. User opens https://codesandbox.io/s/dialog-snackbar-not-accessible-gzl5o?file=/demo.js in Chrome, Firefox or Edge
3. User clicks the "OPEN DIALOG" button and the dialog is launched
4. User clicks the "OPEN SNACKBAR" button within the dialog and the snackbar is launch
5. The screen reader does not read the snackbar and the user of the assistive technology is unaware the snackbar exists  

### Context 🔦

We are building forms and flows that combine the dialog and snackbar components. We need some none intrusive alerts that inform users their task was successful. Snackbars fit our need but are not accessible when triggered from a button within a dialog.  

### Your environment 🌎

<details>
  <summary>`npx @mui/envinfo`</summary>

```
  Don't forget to mention which browser you used.
  Output from `npx @mui/envinfo` goes here.
```
</details>
Repository: yt-dlp
Issue: ffmpeg command too long
Labels: bug,help-wanted,core:downloader

### Checklist

- [X] I'm reporting a bug unrelated to a specific site
- [X] I've verified that I'm running yt-dlp version **2021.12.01**. ([update instructions](https://github.com/yt-dlp/yt-dlp#update))
- [X] I've checked that all provided URLs are alive and playable in a browser
- [X] I've checked that all URLs and arguments with special characters are [properly quoted or escaped](https://github.com/ytdl-org/youtube-dl#video-url-contains-an-ampersand-and-im-getting-some-strange-output-1-2839-or-v-is-not-recognized-as-an-internal-or-external-command)
- [X] I've searched the [bugtracker](https://github.com/yt-dlp/yt-dlp/issues?q=) for similar issues including closed ones. DO NOT post duplicates
- [X] I've read the [guidelines for opening an issue](https://github.com/yt-dlp/yt-dlp/blob/master/CONTRIBUTING.md#opening-an-issue)

### Description

--embed-subs --all-subs at least on this video creates a long command that causes this error
ERROR: [WinError 206] The filename or extension is too long

### Verbose log

[log.txt](https://github.com/yt-dlp/yt-dlp/files/7669425/log.txt)
github kills the post if i post it not in a link

```shell
[debug] Command-line config: ['ZoolYwldrhY', '-vU', '--write-info-json', '--embed-metadata', '--embed-thumbnail', '--write-thumbnail', '--no-write-comments', '--console-title', '--embed-subs', '--write-auto-subs', '--all-subs', '--embed-chapters', '--write-annotations', '--continue', '--merge-output-format', 'mkv', '-o', './archives/%(title).70s [%(id)s].%(ext)s', '--exec', 'comments.py -i %(infojson_filename)q -o %(infojson_filename)q-COMMENTS.txt', '--exec', 'clean_json.py %(infojson_filename)q']
[debug] Encodings: locale cp1252, fs utf-8, out utf-8, err utf-8, pref cp1252
[debug] yt-dlp version 2021.12.01 [91f071a] (win_exe)
[debug] Python version 3.8.10 (CPython 64bit) - Windows-10-10.0.19043-SP0
[debug] exe versions: ffmpeg 4.4-full_build-www.gyan.dev (setts), ffprobe 4.4-full_build-www.gyan.dev
[debug] Optional libraries: Cryptodome, mutagen, sqlite, websockets
[debug] Proxy map: {}
Latest version: 2021.12.01, Current version: 2021.12.01
yt-dlp is up to date (2021.12.01)
[debug] [youtube] Extracting URL: ZoolYwldrhY
[youtube] ZoolYwldrhY: Downloading webpage
```
Repository: yt-dlp
Issue:  Multi-Threaded downloading and processing
Labels: enhancement,discussion/announcement,core:post-processor,core:downloader

### Checklist

- [X] I'm reporting a feature request
- [X] I've verified that I'm running yt-dlp version **2021.12.01**. ([update instructions](https://github.com/yt-dlp/yt-dlp#update))
- [X] I've searched the [bugtracker](https://github.com/yt-dlp/yt-dlp/issues?q=) for similar issues including closed ones. DO NOT post duplicates
- [X] I've read the [guidelines for opening an issue](https://github.com/yt-dlp/yt-dlp/blob/master/CONTRIBUTING.md#opening-an-issue)

### Description

## Problem
When instructed to download multiple URLs, yt-dlp works completely serially: it retrieves, extracts, and downloads the desired content (presumably saturating the network connection), then performs postprocessing (potentially saturating the CPU, among other things).

These tasks have broadly independent constraints: there is minimal CPU demand for downloading a video, and no network traffic while transcoding it. This leaves a lot of room for improvement, which is particularly noticeable with common tasks like downloading playlists.

## Fix
I propose a form of pipelining: when network-constrained tasks finish (that is, when downloading is complete), yt-dlp should move onto the next item’s network-constrained tasks. This means that the first item can be postprocessed while the second item is downloading.

If the second item finishes downloading before the first item is done with postprocessing, yt-dlp can add it to the postprocessing queue and move onto downloading the third item.

The result is that a downloading operation and a postprocessing operation can occur at the same time, substantially improving speed without incurring thrashing.

## Implementation
yt-dlp already draws a concrete distinction between downloading and postprocessing, which is used for some of the options. That should make it relatively seamless to decouple them for this purpose without breaking any custom plugins.

Moreover, this scheme would _never_ run more than one instance of a task at the same time (no task runs both before and after downloading is finished), so shared state is unlikely to be a concern.

The only thing that may be complicated by this proposal, then, is the UI. At worst, this could be dealt with by simply not displaying progress when run in this manner.
Repository: pytorch
Issue: [feature request] A rank-revealing SVD for better stability in backward.
Labels: module: numerical-stability,feature,module: autograd,triaged,module: linear algebra

## 🚀 Feature

It would be great to have a rank-revealing SVD decomposition which for a given input of size `m x n` returns factors of rank `r` with `r <= min(m, n)`. As a bonus, it might eliminate the need for the `matrix_rank` method as it uses SVD as its backbone.
An alternative would be able to get a rank-value + the SVD decomposition as a package deal.

## Motivation

The main motivation is backward stability. The current implementation of SVD makes backward unstable when the input has repeated and/or zero singular values. See, for example: https://github.com/pytorch/pytorch/issues/69531. This kills the possibility to use SVD.backward on low-rank inputs which sure have (repeated) zero singular values.

`torch.linalg.svd` could support additional parameters (like `tol`, and the name for the rank-revealing code path) to enable this feature.
No need to modify the `svd_backward`, as with reduced outputs the chance of backpropagating through zero singular values is significantly reduced.



cc @ezyang @albanD @zou3519 @gqchen @pearu @nikitaved @soulitzer @Lezcano @Varal7 @jianyuh @mruberry @walterddr @IvanYashchuk @xwang233
Repository: ant-design
Issue: Expanding the Tree component with Testing Library
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.

### Reproduction link
[![Edit on CodeSandbox](https://codesandbox.io/static/img/play-codesandbox.svg)](https://codesandbox.io/s/basic-antd-4-17-2-forked-4pd9y?file=/index.spec.js)

### Steps to reproduce
Create a tree component with two depths hierarchy.
With Testing Library, click on the two caret icons. 

### What is expected?
It should expand the two nodes, 

### What is actually happening?
The second node can't be expanded because it remains on a motion status.
When asking Testing-Library to wait for the end of the animation, it raises a timeout. 

| Environment | Info |
|---|---|
| antd | 4.17.2 |
| React | 17.0.2 |
| System | Windows 10 |
| Browser | Google Chrome 96.0.4664.45  |


<!-- generated by ant-design-issue-helper. DO NOT REMOVE -->