sharjeelyunus/github-issues-dataset huggingface dataset:
Repository: rust
Issue: weird behavior from `-Fdead_code` vs `-Funused`
Labels: A-lints,C-bug,A-clippy,L-dead_code,L-unused_imports

running `cargo clippy -- -Dwarnings -Fdead_code` in my binary produces two errors and no warnings. both errors are coming from `clap`.

```
error[E0453]: allow(dead_code) incompatible with previous forbid
  |
  | #[derive(Parser, Debug, Clone)]
  |          ^^^^^^ overruled by previous forbid
  |
  = note: `forbid` lint level was set on command line
  = note: this error originates in the derive macro `Parser` (in Nightly builds, run with -Z macro-backtrace for more info)
```

however, running `cargo clippy -- -Dwarnings -Funused` produces 1158 warnings and no errors. and example of one of the warnings is

```
warning: allow(unused_imports) incompatible with previous forbid
    |
    |         info!("a log message");
    |         ^^^^^^^^^^^^^^^^^^^^^^^^^^^ overruled by previous forbid
    |
    = warning: this was previously accepted by the compiler but is being phased out; it will become a hard error in a future release!
    = note: for more information, see issue #81670 <https://github.com/rust-lang/rust/issues/81670>
    = note: `forbid` lint level was set on command line
    = note: this warning originates in the macro `$crate::valueset` which comes from the expansion of the macro `info` (in Nightly builds, run with -Z macro-backtrace for more info)
```

1. i thought since `dead_code` is a subset of the `unused` lint group that if `-Fdead_code` produced errors that `-Funused` should produce at least the same number of errors.
2. why is that a warning? shouldn't `warning: allow(unused_imports) incompatible with previous forbid` be an error since i added a forbid?
Repository: pytorch
Issue: Make `torch.autograd.Function` support `vmap`
Labels: module: autograd,triaged,topic: docs,module: functorch

### 📚 The doc issue

I am trying to extend `pytorch3d` classes to work with `torch.func.jacrev`, e.g., [_PointFaceDistance](https://github.com/facebookresearch/pytorch3d/blob/4ae25bfce7eb42042a34585acc3df81cf4be7d85/pytorch3d/loss/point_mesh_distance.py#L28). They are `torch.grad.Function`.

In the docs I am able to find so far ([here](https://pytorch.org/docs/stable/notes/extending.func.html) and [here](https://github.com/pytorch/pytorch/blob/71e684bfae9d6ba5d779d2c6e68e6f23e310bc99/functorch/writing_batching_rules.md)), the most relevant suggestion is the sentence below:

> For example, [torch.func.jacrev()](https://pytorch.org/docs/stable/generated/torch.func.jacrev.html#torch.func.jacrev) performs [vmap()](https://pytorch.org/docs/stable/generated/torch.vmap.html#torch.vmap) over the backward pass. So if you’re only interested in using [torch.func.jacrev()](https://pytorch.org/docs/stable/generated/torch.func.jacrev.html#torch.func.jacrev), only the [backward()](https://pytorch.org/docs/stable/generated/torch.autograd.Function.backward.html#torch.autograd.Function.backward) staticmethod needs to be vmappable.

My current effort to make `backward()` vmappable:
1. Adjusted the C++ code that is called by `backward` so that it can work with vmapped parameters. The actual value it returns is correct but this introduces an extra batched axis.
2. Given that new batched axis, `vmap` will unwrap that. The call [here](https://github.com/pytorch/pytorch/blob/main/torch/_functorch/vmap.py#L221-L226) introduces a odd duplication that copies gradient values row by row. This results in a dense 2D vector that has identical values row by row. 

Can someone suggest how to exactly make `backward()` vmappable? If there is an example, it would be great too. Thanks! 

### Suggest a potential alternative/fix

_No response_

cc @ezyang @albanD @gqchen @pearu @nikitaved @soulitzer @Lezcano @Varal7 @zou3519 @Chillee @samdow @kshitij12345 @janeyx99
Repository: PowerToys
Issue: Cannot search files anymore
Labels: Issue-Bug,Needs-Triage

### Microsoft PowerToys version

0,81.1

### Installation method

GitHub

### Running as admin

Yes

### Area(s) with issue?

PowerToys Run

### Steps to reproduce

1. Use Alt + space to open powertoys run.
2. input file names or input ? file name.
3. get nothing
![image](https://github.com/microsoft/PowerToys/assets/60914359/65f4f601-0de9-4160-948a-fbff2714871a)
![image](https://github.com/microsoft/PowerToys/assets/60914359/3b5a2fb0-09df-48e3-b9d3-bc6b7ae1f109)
![image](https://github.com/microsoft/PowerToys/assets/60914359/fbbe176d-4401-4e47-af8c-4b446de40939)


### ✔️ Expected Behavior

I can get search result.


### ❌ Actual Behavior

get no search result.
![image](https://github.com/microsoft/PowerToys/assets/60914359/65f4f601-0de9-4160-948a-fbff2714871a)
![image](https://github.com/microsoft/PowerToys/assets/60914359/3b5a2fb0-09df-48e3-b9d3-bc6b7ae1f109)
[PowerToysReport_2024-06-05-20-55-10.zip](https://github.com/user-attachments/files/15587277/PowerToysReport_2024-06-05-20-55-10.zip)


### Other Software

_No response_
Repository: stable-diffusion-webui
Issue: [Bug]: The SadTalker extension hasn't been working for months.
Labels: asking-for-help-with-local-system-issues

### Checklist

- [ ] The issue exists after disabling all extensions
- [X] The issue exists on a clean installation of webui
- [ ] The issue is caused by an extension, but I believe it is caused by a bug in the webui
- [X] The issue exists in the current version of the webui
- [ ] The issue has not been reported before recently
- [X] The issue has been reported before but has not been fixed yet

### What happened?

SadTalker last worked for me under version 1.7.0 and hasn't worked since. Has anyone found a solution for this or does anyone still have version 1.7.0 and could make it available for download?

I used a new installation of stable-diffusion-webui and encounter errors as soon as I install SadTalker. I am using "Installation on Windows 10/11 with NVidia-GPUs using release package" and Python 3.10.6.

Errors like: AttributeError: module 'numpy' has no attribute 'complex'.
np.complex was a deprecated alias for the builtin complex. To avoid this error in existing code, use complex by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use np.complex128 here.
The alias was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:
https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations

The error seems to occur because SadTalker hasn't been updated for many months.

Who can help?

### Steps to reproduce the problem

clean installation
Try to install SadTalker with webui.

### What should have happened?

SadTalker should have worked.

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

_No response_

### Sysinfo

All requirements are met.

### Console logs

```Shell
All requirements are met.
```


### Additional information

_No response_
Repository: material-ui
Issue: [joy-ui][Tooltip] Not working with custom sub-components
Labels: on hold,component: tooltip,package: joy-ui

### Steps to reproduce

```
import {Tooltip} from '@mui/joy';

export function TooltipBug() {
  return <>
    <Tooltip title="foo">
      <div>f</div>
    </Tooltip>
    <Tooltip title="bar">
      <CustomComponent />
    </Tooltip>
  </>;
}

function CustomComponent() {
  return <div>b</div>;
}
```

shows "foo" but does not show "bar".

### Current behavior

Yields:

```
<div aria-label="foo" class="">f</div>
<div>b</div>
```

### Expected behavior

```
<div aria-label="foo" class="">f</div>
<div aria-label="bar" class="">b</div>
```

### Context

i want to use components

### Your environment

Browser: Mozilla Firefox 126.0.1


<details>
  <summary><code>npx @mui/envinfo</code></summary>
```
  System:
    OS: Linux 5.19 Manjaro Linux
  Binaries:
    Node: 18.18.2 - ~/.nvm/versions/node/v18.18.2/bin/node
    npm: 9.8.1 - ~/.nvm/versions/node/v18.18.2/bin/npm
    pnpm: Not Found
  Browsers:
    Chrome: Not Found
```
</details>


**Search keywords**: tooltip
Repository: opencv
Issue: opencv-java 4.10.0 win11 加载yolov10 onnx报错
Labels: bug,category: dnn (onnx)

### System Information

opencv-java 4.10.0
yolo export model=yolov10n.pt format=onnx  simplify
win11

### Detailed description

[ERROR:0@0.264] global onnx_importer.cpp:1038 cv::dnn::dnn4_v20240521::ONNXImporter::handleNode DNN/ONNX: ERROR during processing node with 2 inputs and 2 outputs: [TopK]:(onnx_node!/model.23/TopK) from domain='ai.onnx'
Exception in thread "main" CvException [org.opencv.core.CvException: cv::Exception: OpenCV(4.10.0) C:\GHA-OCV-1\_work\ci-gha-workflow\ci-gha-workflow\opencv\modules\dnn\src\onnx\onnx_importer.cpp:1057: error: (-2:Unspecified error) in function 'cv::dnn::dnn4_v20240521::ONNXImporter::handleNode'
> Node [TopK@ai.onnx]:(onnx_node!/model.23/TopK) parse error: OpenCV(4.10.0) C:\GHA-OCV-1\_work\ci-gha-workflow\ci-gha-workflow\opencv\modules\dnn\src\net_impl.hpp:108: error: (-2:Unspecified error) Can't create layer "onnx_node!/model.23/TopK" of type "TopK" in function 'cv::dnn::dnn4_v20240521::Net::Impl::getLayerInstance'
> ]
	at org.opencv.dnn.Dnn.readNetFromONNX_0(Native Method)
	at org.opencv.dnn.Dnn.readNetFromONNX(Dnn.java:566)
	at com.test.demo.YoloTest.dnn(YoloTest.java:31)
	at com.test.demo.YoloTest.main(YoloTest.java:22)

### Steps to reproduce

yolo export model=yolov10n.pt format=onnx  simplify
 String onnxFile = path + "/yolov10n.onnx";//modified_best.onnx best.onnx
 Net net= Dnn.readNetFromONNX(onnxFile);

### Issue submission checklist

- [X] I report the issue, it's not a question
- [ ] I checked the problem with documentation, FAQ, open issues, forum.opencv.org, Stack Overflow, etc and have not found any solution
- [X] I updated to the latest OpenCV version and the issue is still there
- [ ] There is reproducer code and related data files (videos, images, onnx, etc)
Repository: kubernetes
Issue: kubelet: add flag for upconverting a component config
Labels: area/kubelet,sig/node,kind/feature,lifecycle/frozen,needs-triage

### What would you like to be added?

introduce a mechanism (flags) in the kubelet for up-converting a user file that has the kubelet component config structure to the latest version of the kubelet API.

the active API in the kubelet has been v1beta1 for a while, but notably a v1 package has been introduced too already:
https://github.com/kubernetes/kubelet/tree/master/config

this work must take into account the recent introduction of drop-in instance specific config directory
- https://github.com/kubernetes/enhancements/issues/3983

### Why is this needed?

other components in the ecosystem have such a user "migration" mechanism:

- `kubeadm config migrate`
- `kube-proxy --config ... --write-config-to ...`, see [here](https://github.com/kubernetes/enhancements/blob/master/keps/sig-network/784-kube-proxy-component-config/README.md#upgrade--downgrade-strategy)
- `kube-scheduler --config ... --write-config-to ...`
- `kubectl convert` for core APIs

if the kubelet releases / enables another component config API, it should be possible to upconvert with an automated mechanism the existing kubelet older user configuration on disk.

suggestion:
- add the flag `--write-config-to` like `kube-proxy` / `kube-scheduler`
- use the API machinery decoders to do a old->internal->new.
Repository: opencv
Issue: Python return types in 4.10 break type checking due to not depending on input types
Labels: bug,category: python bindings,effort: ∞

### System Information

- opencv-python-headless 4.10.0.82
- numpy 1.26.4
- mypy 1.10.0
- MacOS 14.5
- Python 3.12.2

### Detailed description

Many return types in common OpenCV functions have a return type of `cv2.typing.MatLike`. The problem is that when an array with a specific `dtype` is passed in, the resulting output type does not consider this and instead returns a looser type.



### Steps to reproduce

As one example, consider `cv2.putText`. 

> Note: This is just one example, but the underlying problem is pervasive across many OpenCV Python function return type annotations.

```py
import numpy as np
import cv2

image = np.zeros((100, 100, 3), dtype=np.uint8)
image = cv2.putText(image, "Text", (20, 20), cv2.FONT_HERSHEY_SIMPLEX, 1.0, (0, 255, 0), 1)
```

Running Mypy:

```
$ mypy main.py      
main.py:5: error: Incompatible types in assignment (expression has type "ndarray[Any, dtype[integer[Any] | floating[Any]]]", variable has type "ndarray[Any, dtype[unsignedinteger[_8Bit]]]")  [assignment]
Found 1 error in 1 file (checked 1 source file)
```

This is blocking us from upgrading from OpenCV 4.8 to 4.10 (upgrading to 4.9 was similarly blocked on other type checking problems):

- #24803

We cannot update to OpenCV 4.10 because every time we pass in a `uint8` dtype array into OpenCV, the type checker loses this specific type on the return of the OpenCV function, which generates lots of downstream type checking errors when we pass these results into other functions or dataclasses where we restrict the type annotation to a specific `dtype` (e.g., `ndarray[Any, np.uint8]`).

Mypy configuration:

```toml
[tool.mypy]
strict = true
plugins = [
    "numpy.typing.mypy_plugin",
]
```

### Issue submission checklist

- [X] I report the issue, it's not a question
- [X] I checked the problem with documentation, FAQ, open issues, forum.opencv.org, Stack Overflow, etc and have not found any solution
- [X] I updated to the latest OpenCV version and the issue is still there
- [X] There is reproducer code and related data files (videos, images, onnx, etc)
Repository: PowerToys
Issue: Quick Accent: Input errors when used with Chinese, Japanese, & Korean IME
Labels: Issue-Bug,Needs-Triage

### Microsoft PowerToys version

0.70.0

### Installation method

GitHub, PowerToys auto-update

### Running as admin

None

### Area(s) with issue?

Quick Accent

### Steps to reproduce

1. Turn on Quick Accent in Powertoys, Use space as activation key, and switch IME to Microsoft Pinyin ( which is default simplified Chinese IME on Windows).
2. Rapidly alternating between pressing a character key and space key. ( Such as, press [d] [space] [d] [space] [d] [space] ... as fast as you can, it simulate a fast input scenario. ) 

### ✔️ Expected Behavior

Every time you press [d], the IME shows candidates, and when you press [space], first candidate will be input. ( For key [d], the character your input is "的" in normal. ) So, you can get a series of identical Chinese characters, like:

```
的的的的的的的的的的的的的的的的的的的的的的的的的的的的的
```

### ❌ Actual Behavior

Quick Accent will "eat" some [space], and release them after a short delay. So you will see consecutive Spaces and the same number of Chinese characters pop up at the same time, as follows: 

```
的的的的的的  得到的的的    顶顶顶顶的的的的的的的    顶顶顶顶
```

Note that combinations such as `"  得到"` and `"    顶顶顶顶"` pop up together after entering the spaces that follow them, which is not possible in normal input, because the leading spaces will not trigger the IME candidates box, just show immediately.

If turn off Quick Accent, or use Left/Right as activation key, everything is OK.

### Other Software

Windows version: 22H2 (19045.4474)

### Related issues

It seems this problem also occurs in other languages IME, such as Japanese (#22452, #23132) and Korean(#23464).

#30716 also report that Quick Accent will "eat" some space, and #23464 reports the leading spaces problem.

### Possible solutions

Is there a way to detect IME status? If so, trigger quick accent only when typing English or Latin characters maybe a good choice.
Repository: ollama
Issue: Feature request: Model metadata should list capabilities
Labels: feature request

As the number of different models grow it would be great to add some sort of `capabilities` property to /tags response.
This property should contain information about what kind of input a model can have:
* since ollama now also includes modes that are able to accept process images (think llava)
* some models can only be used to generate embeddings
* some models are good with code, others are better at story telling
* in the future there might be modes that can also return images as part of the response
* etc
This would insure a UI front-end is able to know whether users should be allowed to send certain types of data to a model
Repository: rust
Issue: rustc complains about unused code if item is used in `#[automatically_derived]` context
Labels: A-diagnostics,P-low,T-compiler,regression-from-stable-to-stable,C-bug

<!--
Thank you for filing a regression report! 🐛 A regression is something that changed between versions of Rust but was not supposed to.

Please provide a short summary of the regression, along with any information you feel is relevant to replicate it.
-->

### Code

I tried this code:

```rust
use std::fmt::{Debug, Display};

struct Identity<T>(T);

impl<T> Display for Identity<T>
where
    T: Display,
{
    fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
        write!(f, "{}", self.0)
    }
}

struct Thing {}

#[automatically_derived]
impl Debug for Thing {
    fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
        write!(f, "{}", Identity("Thing"))
    }
}

fn main() {
    let hello = Thing {};
    println!("{hello:?}");
}
```

I expected to see this happen: The code compiles without any warnings since, the `Identity` struct is clearly used.

Instead, this happened: The compiler emits a `dead_code` lint, telling me that the struct is never constructed

Example where this can occur: when using the `derive_more` crate to derive a specialized `Debug` implementation, and the usage of `derive_more::Debug` utilizes a formatter struct to avoid allocating into an intermediate heap allocated buffer

[Real-world example](https://github.com/CosmWasm/cosmwasm/blob/6bdfd9c9cfa91cafc40d9a0f90633883143e42fe/packages/std/src/results/cosmos_msg.rs#L168-L197)

### Version it worked on

<!--
Provide the most recent version this worked on, for example:

It most recently worked on: Rust 1.47
-->

It most recently worked on: Rust 1.77.2

### Version with regression

<!--
Provide the version you are using that has the regression.
-->

`rustc --version --verbose`:
```
rustc 1.78.0 (9b00956e5 2024-04-29)
binary: rustc
commit-hash: 9b00956e56009bab2aa15d7bff10916599e3d6d6
commit-date: 2024-04-29
host: x86_64-unknown-linux-gnu
release: 1.78.0
LLVM version: 18.1.2
```

@rustbot modify labels: +regression-from-stable-to-stable -regression-untriaged


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Repository: vscode
Issue: `launch` setting UI is bugged for the workspace tab
Labels: bug,settings-editor,confirmed

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Does this issue occur when all extensions are disabled?: idk

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- VS Code Version: Visual Studio Code
Version: 1.89.1
Commit: dc96b837cf6bb4af9cd736aa3af08cf8279f7685
Date: 2024-05-07T05:17:15.788Z (4 wks ago)
Browser: Mozilla/5.0 (X11; CrOS x86_64 14541.0.0) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/126.0.0.0 Safari/537.36

Steps to Reproduce:

1. Go to Settings
2. Find the `launch` setting in the "workspace" tab
3. Observe that the UI shows that it has been modified, and when clicking on "Reset Setting", it create a blank `.vscode/settings.json` and a `.vscode/launch.json` with a boilerplate

![image](https://github.com/microsoft/vscode/assets/76160668/3e44d989-5272-4e5b-99ae-f32634c9bdb5)
Repository: go
Issue: dl: golang.org/dl/go1.n.m wrappers always force own GOROOT, even overwriting another value in the environment
Labels: NeedsInvestigation

When invoking `cmd/go` from `golang.org/dl`, it will always set `GOROOT` to the directory where it was installed (`$HOME/sdk/version`), even if the environment variable `GOROOT` is already set to a different value:

    $ GOROOT=/tmp go1.22.4 env GOROOT
    /home/cespedes/sdk/go1.22.4

It is set in file `internal/version/version.go`, function `runGo()`, line 67:
https://github.com/golang/dl/blob/bbd4740e98dac76d3abebb6f77bfb4f082899a23/internal/version/version.go#L67

In my opinion, it is not necessary to set `GOROOT` at all or, at least, do not set it if it is already in the environment.
Repository: go
Issue: build: make.bash failures
Labels: NeedsInvestigation

```
#!watchflakes
default <- repo == "vuln" && (pkg == "" && test == "make.bash" || pkg == "make.bash")
```

Issue created automatically to collect these failures.

Example ([log](https://ci.chromium.org/b/8746018250631701441)):

    Building Go cmd/dist using /Users/swarming/.swarming/w/ir/cache/tools/go_bootstrap. (go1.20.6 darwin/amd64)
    Building Go toolchain1 using /Users/swarming/.swarming/w/ir/cache/tools/go_bootstrap.
    Building Go bootstrap cmd/go (go_bootstrap) using Go toolchain1.
    Building Go toolchain2 using go_bootstrap and Go toolchain1.
    Building Go toolchain3 using go_bootstrap and Go toolchain2.
    Building packages and commands for darwin/amd64.
    # testing
    unexpected fault address 0xc000c09e00
    fatal error: fault
    [signal SIGBUS: bus error code=0x2 addr=0xc000c09e00 pc=0xc000c09e00]
    ...
    	runtime/chan.go:489 +0x12 fp=0xc0000507b8 sp=0xc000050790 pc=0x7507572
    runtime.unique_runtime_registerUniqueMapCleanup.func1(...)
    	runtime/mgc.go:1732
    runtime.unique_runtime_registerUniqueMapCleanup.gowrap1()
    	runtime/mgc.go:1735 +0x2f fp=0xc0000507e0 sp=0xc0000507b8 pc=0x751e08f
    runtime.goexit({})
    	runtime/asm_amd64.s:1700 +0x1 fp=0xc0000507e8 sp=0xc0000507e0 pc=0x7585601
    created by unique.runtime_registerUniqueMapCleanup in goroutine 1
    	runtime/mgc.go:1730 +0x96
    go tool dist: FAILED: /Users/swarming/.swarming/w/ir/x/w/goroot/pkg/tool/darwin_amd64/go_bootstrap install cmd: exit status 1


— [watchflakes](https://go.dev/wiki/Watchflakes)
Repository: flutter
Issue: Skia->engine auto-roller did not close a roll PR that failed CI
Labels: team-infra,P3,triaged-infra

The Skia->engine auto-roller was stuck for a few days because a pending roll PR failed CI:
   https://github.com/flutter/engine/pull/53162

The `linux_web_engine` CI check failed on this PR, and the auto-roller should close the PR and start a new roll.  But in this case the PR remained open.  Creation of new roll PRs did not happen until the failing PR was closed manually.
Repository: PowerToys
Issue: Use the Fancy Zones layout editor once and allow those settings to stick
Labels: Needs-Triage

### Description of the new feature / enhancement

Once the FancyZones layout editor is used, don't require those layouts to be re-created every couple of times the PC is booted up. in the current version (0.81.1) I use the layout edit and everything works fine for a little while. Maybe one or two time when I boot up my laptop. But perhaps on the third time, my screens are scrambled and I have to use the layout edit again.

### Scenario when this would be used?

Anytime you boot the PC, FancyZones already retains its prior established layouts.

### Supporting information

_No response_