sharjeelyunus/github-issues-dataset huggingface dataset:
Repository: flutter
Issue: TextField cursor jumps to beginning when the textfield contains`\r\n\r\n`
Labels: a: text input,framework,has reproducible steps,P2,found in release: 3.0,found in release: 3.1,team-framework,triaged-framework

我当前的Flutter版本为3.0.3

_translated using Google Translate_ 

My current Flutter version is 3.0.3

![VeryCapture_20220624230911](https://user-images.githubusercontent.com/30982989/175564379-aeaa3e67-23f4-40bf-9af0-8460e64360c0.gif)
Repository: pytorch
Issue: Support tensor subclasses as `UninitializedParameter`s
Labels: module: nn,triaged,enhancement,module: lazy,tensor subclass

Tensor subclass support as `Parameter`s within modules was added in #73459. A notable gap is support for lazy modules, which utilize `UninitializedParameter`s. We need a way to specify that the `UninitializedParameter` should become a particular subtype when materialized into a `Parameter`.

https://github.com/pytorch/pytorch/blob/35268bdc2a6f0be613b9fa0b5e3da6ae68ece67f/torch/nn/parameter.py#L92-L110

We can change the above, but this will notably require lazy modules (implementing `LazyModuleMixin`) to change slightly. Don't see any way around this change.

cc @albanD @mruberry @jbschlosser @walterddr @kshitij12345 @saketh-are
Repository: create-react-app
Issue: I caught an issue while creating react-app with the below command
Labels: needs triage,issue: bug report

C:\Users\vanishree.r>npx create-react-app sample-react-app
npx: installed 67 in 24.301s

Creating a new React app in C:\Users\vanishree.r\sample-react-app.

Installing packages. This might take a couple of minutes.
Installing react, react-dom, and react-scripts with cra-template...

Aborting installation.
Unexpected error. Please report it as a bug:
Error: spawn UNKNOWN
at ChildProcess.spawn (internal/child_process.js:403:11)
at spawn (child_process.js:667:9)
at Object.spawnWithSignal [as spawn] (child_process.js:871:17)
at spawn (C:\Users\vanishree.r\AppData\Roaming\npm-cache_npx\1628\node_modules\create-react-app\node_modules\cross-spawn\index.js:12:24)
at C:\Users\vanishree.r\AppData\Roaming\npm-cache_npx\1628\node_modules\create-react-app\createReactApp.js:383:19
at new Promise ()
at install (C:\Users\vanishree.r\AppData\Roaming\npm-cache_npx\1628\node_modules\create-react-app\createReactApp.js:334:10)
at C:\Users\vanishree.r\AppData\Roaming\npm-cache_npx\1628\node_modules\create-react-app\createReactApp.js:461:16
at processTicksAndRejections (internal/process/task_queues.js:95:5) {
errno: -4094,
code: 'UNKNOWN',
syscall: 'spawn'
}

Deleting generated file... package.json
Deleting sample-react-app/ from C:\Users\vanishree.r
Done.


node version - v14.17.5

npm version - 6.10.3
Repository: pytorch
Issue: [Prims+NVFuser] Aten2Prim refs tracking items
Labels: triaged,module: nvfuser,module: primTorch

- [ ] aten.div https://github.com/pytorch/pytorch/pull/77936 
- [ ] aten.amax
- [ ] aten.view
- [ ] aten.new_zero
- [ ] aten.conj_phsycial https://github.com/pytorch/pytorch/pull/81014
- [ ] aten.type_as
- [ ] aten.rand_like
- [ ] aten.var


cc @ezyang @mruberry @ngimel
Repository: pytorch
Issue: [Prims+NVFuser] Supports 0-sized inputs
Labels: triaged,module: nvfuser,module: primTorch

A potential fix for this issues is to add a guard to ensure inputs to nvFuser kernels are non-empty tensor. Fallback to eager for empty tensor. 


Invoked with: <torch._C._nvfuser.FusionDefinition object at 0x7f144038b430>, <class 'RuntimeError'>, RuntimeError('sizes[i] > 0 INTERNAL ASSERT FAILED at "/fsx/users/bahuang/repos/pytorch_fsx/torch/csrc/jit/codegen/cuda/python_frontend/python_bindings.cpp":225, **please report a bug to PyTorch. Size of 0 is not supported in nvFuser. Expected size > 0.**'), <traceback object at 0x7f1440767500>


cc @ezyang @mruberry @ngimel
Repository: material-ui
Issue: [typography] Built-in scrollMarginTop support
Labels: new feature,waiting for 👍,component: Typography,package: material-ui,package: joy-ui

### Duplicates

- [X] I have searched the existing issues

### Latest version

- [X] I have tested the latest version

### Summary 💡

Improve the scroll top integration of `scrollMarginTop` with the Typography.

### Examples 🌈

I'm not sure what's the best way to abstract this, but I wonder if it wouldn't make a lot of sense to, once/if the Typography component is moved to @mui/system, to:

1. Add a minimum value of scrollMarginTop to 8px so it doesn't scroll like this:

<img width="768" alt="Screenshot 2022-06-24 at 20 15 23" src="https://user-images.githubusercontent.com/3165635/175619942-80a45cd4-d067-454f-9b6d-373afb0d9e68.png">

but like this (better default when there are no sticky headers):

<img width="736" alt="Screenshot 2022-06-24 at 20 15 32" src="https://user-images.githubusercontent.com/3165635/175619791-49723ea7-3b9e-4f80-9dba-ac6658801c10.png">

2. Add a CSS variable to allow the header to self-declare the scroll it wants the headers to have, like here:

https://github.com/mui/material-ui/blob/fc3aee885444338ae9e4894595e2fbd509886ea7/docs/src/modules/brandingTheme.ts#L274-L276

https://github.com/mui/material-ui/blob/fc3aee885444338ae9e4894595e2fbd509886ea7/docs/src/layouts/AppHeader.tsx#L61-L68

3. Document the above.

### Motivation 🔦

- https://github.com/mui/material-ui/pull/33215/files#diff-1f70d27002ced619782b07207f4d92ac27c4918de9feaf515eb8a1728eb39c2bR275
- https://github.com/mui/mui-store/pull/175/files#diff-cc03b0651401729dd84b19c1c909328cfcc08ebfd95a0dd8e2f4355f736dd432R34
Repository: godot
Issue: MSVC mod by 0 warning in cowdata.h when compiling with `production=yes`
Labels: bug,topic:buildsystem

### Godot version

3.4.4-stable

### System information

Windows 10 64-bit Latest

### Issue description

When compiling with:
 `scons platform=windows tools=yes target=release_debug production=yes`
I will get this warning:
`core\cowdata.h(136) : warning C4724: potential mod by 0`
Without the `production=yes flag`, the warning does not seem to appear.

When using flags that Godot's Github Actions uses, from what I can glean:
`scons platform=windows target=release_debug tools=yes verbose=yes warnings=all debug_symbols=no`
But adding the `production=yes` flag this warning becomes and error, halting compiling, obviously:
```
core\cowdata.h(136) : error C2220: the following warning is treated as an error
core\cowdata.h(136) : warning C4724: potential mod by 0
```

### Steps to reproduce

Basically attempt to compile with the flags above.  Compiling with MSVC version 14.2,

### Minimal reproduction project

_No response_
Repository: pytorch
Issue: test_conv_backend tests OOMing in 10.2 slow_gradcheck CI
Labels: module: nn,module: ci,module: convolution,triaged

I have NOT disabled this test yet because it may just be transient. To disable the test, add DISABLED at the front of the issue title.

Platforms: linux

This test is failing on periodic jobs due to running out of memory ([recent examples](http://torch-ci.com/failure/test_conv_backend_cudnn3d_transposed_has_bias_False_strided_False_contiguous_True_cuda%2C%20TestNNDeviceTypeCUDA)).

https://hud.pytorch.org/pytorch/pytorch/commit/bab1ea8592f7308cded5d146e2d921ed2a6702dc 
```
2022-06-24T07:26:25.5421038Z RuntimeError: CUDA out of memory. Tried to allocate 20.00 MiB (GPU 0; 7.44 GiB total capacity; 6.88 GiB already allocated; 20.06 MiB free; 6.88 GiB reserved in total by PyTorch) If reserved memory is >> allocated memory try setting max_split_size_mb to avoid fragmentation.  See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF
```



cc @albanD @mruberry @jbschlosser @walterddr @kshitij12345 @saketh-are @seemethere @malfet @pytorch/pytorch-dev-infra
Repository: pytorch
Issue: Change c10d APIs in ProcessGroup to accept const std::vector<at::Tensor>&
Labels: oncall: distributed,triaged

Change c10d APIs in ProcessGroup to accept `const std::vector<at::Tensor>&` instead of `std::vector<at::Tensor>&`.

This is a follow up on #79669.

cc @pietern @mrshenli @pritamdamania87 @zhaojuanmao @satgera @rohan-varma @gqchen @aazzolini @osalpekar @jiayisuse @SciPioneer @H-Huang @kwen2501
Repository: pytorch
Issue: Write some torch.distributed.nn.* tests for the new dispatcher passable ops
Labels: oncall: distributed,triaged

Write some torch.distributed.nn.* tests for the new dispatcher passable ops. This is a follow up on #79669.

cc @pietern @mrshenli @pritamdamania87 @zhaojuanmao @satgera @rohan-varma @gqchen @aazzolini @osalpekar @jiayisuse @SciPioneer @H-Huang @kwen2501
Repository: yt-dlp
Issue: Support wget2 as an external downloader
Labels: enhancement,core:downloader

### Checklist

- [X] I'm requesting a feature unrelated to a specific site
- [X] I've looked through the [README](https://github.com/yt-dlp/yt-dlp#readme)
- [X] I've verified that I'm running yt-dlp version **2022.06.22.1** ([update instructions](https://github.com/yt-dlp/yt-dlp#update)) or later (specify commit)
- [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

[Wget2](https://gitlab.com/gnuwget/wget2) is a downloader similar to wget. It features aria2-like features such as split downloads with a configurable chunk-size. Unlike aria2, it also supports features like HTTP/2.

### Verbose log

_No response_
Repository: kubernetes
Issue: Missing test coverage for OIDC code
Labels: sig/auth,triage/accepted

/sig auth

xref #108794

---

I have been thinking about this change and the associated code, especially in regards to the on-going [quality discussion](https://groups.google.com/a/kubernetes.io/g/dev/c/6F3h0Z1QzVg/m/43tdYs_lAAAJ).

While I think this change is at least partially a move in the right direction, I believe further refactors are required to actually make this code understandable and maintainable (and correct in all configurations).

Thus before making changes to this code, I would like to see the following integration test coverage:

- Build a mock OIDC test server with the JWKs, well-known, and token endpoints
- Run a test API server
- Configure it to use a the mock OIDC test server (process local)
- Configure the client(s) based on the specific test scenario
- Make calls to the CSR API _and_ the token review API (with and without correct audience) and assert the user info is correct

Some scenarios that come to mind (this is not meant to be a complete list, and I suspect some will fail on the existing code):

1. ID token not expired
2. ID token expired
3. Refresh token does not change
4. Refresh token does change
5. Other aspects of the config change (i.e. client secret, CA data, etc)
6. Auth config persister does not actually persist
7. Refresh flow does not return ID token
8. ID token expires early due to JWK rotation
9. Distributed claim fetching for group data
10. ...

The above will likely need multiple permutations, in particular I would like to see both kubeconfig files as input (maybe even the same file concurrently across different round trippers) and `rest.Config` as inputs (with every weird config a code integrator could come up with).

In an ideal world we would have e2e tests in a similar vain as the above against an OIDC provider like Dex or Keycloak or UAA, but we can leave that off for now.

The API server OIDC support and the client-go OIDC support are two halves of the same feature, and both sides have no real integration test coverage when used in conjunction with an API server.  Lets fix that so that we can make changes with confidence.

_Originally posted by @enj in https://github.com/kubernetes/kubernetes/issues/108794#issuecomment-1126162050_
Repository: vscode
Issue: Allow registerTextEditorCommand callbacks to return a value
Labels: feature-request,api,editor-core

<!-- ⚠️⚠️ Do Not Delete This! feature_request_template ⚠️⚠️ -->
<!-- Please read our Rules of Conduct: https://opensource.microsoft.com/codeofconduct/ -->
<!-- Please search existing issues to avoid creating duplicates. -->

`vscode.commands.registerCommand` callbacks may return a value—see `callback: (...args: any[]) => any`, here):
````ts
export function registerCommand(command: string, callback: (...args: any[]) => any, thisArg?: any): Disposable;
````

These return values are accessible when executing commands programmatically:
````ts
vscode.commands.registerCommand('example', async () => 42);
const value = await vscode.commands.executeCommand('example');
console.log(value); // prints "42"
````

Unfortunately, `vscode.commands.registerTextEditorCommand` callbacks **may not** return a value—see `callback: (textEditor: TextEditor, edit: TextEditorEdit, ...args: any[]) => void`, here:
````ts
export function registerTextEditorCommand(command: string, callback: (textEditor: TextEditor, edit: TextEditorEdit, ...args: any[]) => void, thisArg?: any): Disposable;
````

Is there a reason for this discrepancy, or was this an oversight? Being able to return a value from one of my extension's text editor commands would simplify my code a bit. In the meantime, I'm working around this by using `registerCommand` instead of `registerTextEditorCommand` and checking whether there's an active editor manually. I'd love to use the correct type of command instead, however.

Thanks for your consideration! 🙏
Repository: rust
Issue: E0621 Dataflow can point to wrong location causing lifetime obligation
Labels: A-diagnostics,T-compiler

<!--
Thank you for filing a bug report! 🐛 Please provide a short summary of the bug,
along with any information you feel relevant to replicating the bug.

If you cannot produce a minimal reproduction case (something that would work in
isolation), please provide the steps or even link to a repository that causes
the problematic output to occur.
-->

[Given the following code:](https://play.rust-lang.org/?version=nightly&mode=debug&edition=2021&gist=df287459c190ec33a3039f27809383b8) <!-- Please provide a link to play.rust-lang.org -->

```rust
struct HasLife<'a>(&'a str);
struct Store<'a>(Vec<&'a HasLife<'a>>);

impl<'a> Store<'a> {
    pub fn run(x: &HasLife<'a>) -> &'a str {
        let mut store = Store(Vec::new());
        store.add_inner(x);
        store.0[0].0
    }
    
    fn add_inner(&mut self, x: &'a HasLife<'a>) {
        self.0.push(x);
    }
}
```

The current output is:

```
error[E0621]: explicit lifetime required in the type of `x`
 --> src/lib.rs:8:9
  |
5 |     pub fn run(x: &HasLife<'a>) -> &'a str {
  |                   ------------ help: add explicit lifetime `'a` to the type of `x`: `&'a HasLife<'a>`
...
8 |         store.0[0].0
  |         ^^^^^^^^^^^^ lifetime `'a` required
```

<!-- The following is not always necessary. -->
Ideally the output should look like:


```
error[E0621]: explicit lifetime required in the type of `x`
 --> src/lib.rs:8:9
  |
5 |     pub fn run(x: &HasLife<'a>) -> &'a str {
  |                   ------------ help: add explicit lifetime `'a` to the type of `x`: `&'a HasLife<'a>`
...
7 |         store.add_inner(x);
  |         ^^^^^^^^^^^^^^^^^^^ lifetime `'a` required
...
11|     fn add_inner(&mut self, x: &'a HasLife<'a>) 
  |                                ^^^^^^^^^^^^^^^^ help, because `Store::add_inner` requires `&'a HasLife<'a>`
```



[- If you remove the return from `Store::run` then it just works](https://play.rust-lang.org/?version=nightly&mode=debug&edition=2021&gist=9aaceefe329b4d48519f13548e6b9e53)
[- If you make `pub fn run(&mut self, x: &HasLife<'a>) {self.add_inner(x)}`, you get a good E0621 Error](https://play.rust-lang.org/?version=nightly&mode=debug&edition=2021&gist=f83dfd1e3ae633d5573933542c96d8a7)

Build using the Nightly version: 1.63.0-nightly (2022-06-23 43347397f7c5ca9a670a)
Repository: flutter
Issue: Correctly handle taps on desktop and clicks on mobile
Labels: framework,a: fidelity,c: proposal,a: mouse,P3,team-framework,triaged-framework

The text editing stack does not correctly handle mouse events on mobile platforms and tap events on desktop platforms.  We should survey the native behaviors in these situations and make sure Flutter behaves the same as native.

### Current behavior

Currently, Flutter's behavior in these situations is mostly a relic of adding desktop/mouse support to a framework that was previously mobile/touch only.

For an example of touch events on desktop, double tapping on any desktop platform will show the text selection toolbar ([code](https://github.com/flutter/flutter/blob/526ca0d498120e93efbdd25f8824825dd7b6b13f/packages/flutter/lib/src/widgets/text_selection.dart#L1463)).

An example of mouse events on mobile would be that right clicking always shows the text selection toolbar ([code](https://github.com/flutter/flutter/blob/526ca0d498120e93efbdd25f8824825dd7b6b13f/packages/flutter/lib/src/widgets/text_selection.dart#L1690)) even on all mobile platforms.

We should survey these cases on our supported platforms and make sure Flutter behaves correctly.

### Behaviors (todo)

| Behavior | Flutter app | Native app |
| --- | --- | --- |
| Right click on Android | Show menu | ? |
| Right click on iOS | Show menu | Nothing? |
| Double tap on Windows | Shows menu | Selects word, doesn't show menu |
| Double tap on Linux | Show menu | ? |
| Double tap on Mac | Show menu | ? |
| Long press on Windows | Show menu | Shows menu |
| Long press on Linux | Show menu | ? |
| Long press on Mac | Show menu | ? |

### Related

As of https://github.com/flutter/flutter/pull/104647, Flutter will strictly show the text selection menu based on the platform, not pointer type (tap vs. click).

CC @TahaTesser who I believe has discussed this problem with me before.
Repository: pytorch
Issue: [complex] dropout and it's variants should support complex tensors
Labels: feature,module: nn,triaged,module: complex

### 🐛 Describe the bug

```python
import torch
torch.nn.functional.dropout(torch.randn(3, 3, dtype=torch.cfloat))
```

Output
```
RuntimeError: "bernoulli_scalar_cpu_" not implemented for 'ComplexFloat'
```

List of Dropout Modules:
* [ ] Dropout
* [ ] Dropout2d
* [ ] Dropout3d
* [ ] AlphaDropout
* [ ] FeatureAlphaDropout


### Versions

master

cc @albanD @mruberry @jbschlosser @walterddr @kshitij12345 @saketh-are @ezyang @anjali411 @dylanbespalko @Lezcano @nikitaved
Repository: pytorch
Issue: Cudnn batch norm kernel (batchnorm_bwtr_nhwc_semiPersist) gets blocked by overlapping NCCL all_reduce calls
Labels: module: dependency bug,module: cudnn,triaged,module: nccl,module: memory format

### 🐛 Describe the bug

When cudnn + channels_last format is enabled, under distributed DDP, the backward pass of cudnn batchnorm backward can be stalled by the overlapped nccl all_reduce call. 

Sorry I don't have a code snippet for repro, but here are some screenshots of torch profiler

Blocking batch_norm_backward
![image](https://user-images.githubusercontent.com/1190730/175750442-13d30ee6-5c8b-4f59-bbcd-95027448af5b.png)

Neither the aten native implementation nor the NCHW version of cudnn kernel `bn_bw_1C11_singleread_specialized` shows this behavior. 

Technically this seems like a cuDNN bug, but I don't know where/how to file a cudnn bug, so filing it here instead. This issue is also reported on https://github.com/NVIDIA/nccl/issues/338 https://github.com/NVIDIA/nccl/issues/661


### Versions

```
Collecting environment information...
PyTorch version: 1.11.0a0+gitbc2c6ed
Is debug build: False
CUDA used to build PyTorch: 11.4
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: 14.0.5 (https://github.com/conda-forge/clangdev-feedstock 0f793d7b2ad6a3c631eb76429f4e4def37c890dd)
CMake version: version 3.19.1
Libc version: glibc-2.31

Python version: 3.8.13 | packaged by conda-forge | (default, Mar 25 2022, 06:04:10)  [GCC 10.3.0] (64-bit runtime)
Python platform: Linux-5.4.0-64-generic-x86_64-with-glibc2.10
Is CUDA available: True
CUDA runtime version: 11.4.120
GPU models and configuration: GPU 0: NVIDIA A100-SXM-80GB
Nvidia driver version: 470.57.02
cuDNN version: Could not collect
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True

Versions of relevant libraries:
[pip3] mypy-extensions==0.4.3
[pip3] numpy==1.19.5
[pip3] pytorch3d==0.6.1
[pip3] torch==1.11.0+bc2c6ed.cuda114.cudnn841.se02.ap
[pip3] torch-scatter==2.0.8
[pip3] torch-tb-profiler==0.4.0
[pip3] torchfile==0.1.0
[pip3] torchvision==0.9.0a0+8fb5838
[conda] magma-cuda111             2.5.2                         1    pytorch
[conda] mkl                       2020.4             h726a3e6_304    conda-forge
[conda] mkl-include               2022.1.0           h84fe81f_915    conda-forge
[conda] numpy                     1.19.5           py38h8246c76_3    conda-forge
[conda] pytorch3d                 0.6.1                    pypi_0    pypi
[conda] torch                     1.11.0+bc2c6ed.cuda114.cudnn841.se02.ap          pypi_0    pypi
[conda] torch-scatter             2.0.8                    pypi_0    pypi
[conda] torch-tb-profiler         0.4.0                    pypi_0    pypi
[conda] torchfile                 0.1.0                    pypi_0    pypi
[conda] torchvision               0.9.0a0+8fb5838          pypi_0    pypi
```

cc @csarofeen @ptrblck @xwang233 @VitalyFedyunin @jamesr66a
Repository: javascript
Issue: Add `Object.hasOwn` to Section 3.7 (Object.prototype methods)
Labels: pull request wanted

Hello, it seems that `Object.hasOwn` is now available in most major browsers (https://caniuse.com/mdn-javascript_builtins_object_hasown), so it might be worth adding it to section [3.7](https://github.com/airbnb/javascript#objects--prototype-builtins).
It seems to be recommended as a replacement for `Object.hasOwnProperty` (https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Object/hasOwn), so the section could be changed to something like this:

- [3.7](#objects--prototype-builtins) Do not call `Object.prototype` methods directly, such as `hasOwnProperty`, `propertyIsEnumerable`, and `isPrototypeOf`. eslint: [`no-prototype-builtins`](https://eslint.org/docs/rules/no-prototype-builtins)

    > Why? These methods may be shadowed by properties on the object in question - consider `{ hasOwnProperty: false }` - or, the object may be a null object (`Object.create(null)`). In modern browsers `Object.hasOwn` can be used, which works for null objects and objects, where `hasOwnProperty` has been overridden.

    ```javascript
    // bad
    console.log(object.hasOwnProperty(key));

    // good
    console.log(Object.prototype.hasOwnProperty.call(object, key));

    // better
    const has = Object.prototype.hasOwnProperty; // cache the lookup once, in module scope.
    console.log(has.call(object, key));
    // best
    console.log(object.hasOwn(key));
    /* or */
    import has from 'has'; // https://www.npmjs.com/package/has
    console.log(has(object, key));
    ```

There is also a rule for this available in eslint 8.5+ (https://eslint.org/docs/latest/rules/prefer-object-has-own).

Cheers