sharjeelyunus/github-issues-dataset huggingface dataset:
Repository: tauri
Issue: [feat] `alwaysOnTop` support for windows above the dock on macOS and above the taskbar on Windows
Labels: type: feature request

### Describe the problem

I don't know if tauri currently has a way to make it possible for windows to show above the Dock on macOS and above the taskbar on Windows, if not! Is there a quick way to make it happen?

### Describe the solution you'd like

electron's [setAlwaysOnTop](https://www.electronjs.org/zh/docs/latest/api/browser-window#winsetalwaysontopflag-level-relativelevel) Support for windows above the dock on macOS and above the taskbar on Windows.

### Alternatives considered

_No response_

### Additional context

_No response_
Repository: PowerToys
Issue: Accessibility: Add an option to Screen Ruler to accommodate users with 'Make Text Bigger' turned on in Windows Display Settings
Labels: Needs-Triage

### Description of the new feature / enhancement

When looking at the settings for Screen Ruler, a toggle is there, called 
"Adjust for Windows Settings' Display Scaling".
When you toggle it on, the Screen Ruler now automatically adjusts the pixels it measures to reduce the value from the literal pixels on the screen to the original, non-scaled pixels on the screen. 

### Scenario when this would be used?

A user has the setting Display: Make Text Bigger on. Let's say, 125%. 

When using Chrome's dev tools or a measurement browser plugin to view a web page, user sees that a div is 100px tall. The user had set the div as 100px tall with CSS. 

When the user  measure the same div with the Screen Ruler, it shows up as 125px tall. 

The user is confused by the discrepancy, and wonders if Screen Ruler is broken. The user looks at the Screen Ruler settings, and turns on "Adjust for Windows Settings' Display Scaling". 

Screen Ruler now measure that same div as 100px tall, just like the Chrome dev tools and the browser plugin does. It can now be part of this user's web dev work flow again.

### Supporting information

This is how I found out that the Windows setting "Make Text Bigger" scales up everything, even though that setting name doesn't imply it.

Another option that would work could be more manual - "Scaling: 75%" So the user could choose a % that the Ruler always multiplies its actual measured numbers by.
Repository: PowerToys
Issue: PowerToys UAC screen can come up on "We're getting things ready" screen
Labels: Issue-Bug,Area-Runner,Needs-Triage

### Microsoft PowerToys version

0.81.0

### Installation method

GitHub

### Running as admin

Yes

### Area(s) with issue?

General

### Steps to reproduce

1. Have PowerToys always starting as administrator
2. Start a Windows update
3. When the PC is shutdown during the update change the hardware, so it changes the security config (In a way Windows will forget UAC access for PowerToys)
4. While being on the "We're getting things ready" screen, PowerToys UAC will pop up
5. This will start "explorer.exe" while the update is still running

This shouldn't happen. I will look if I can reproduce this.

### ✔️ Expected Behavior

_No response_

### ❌ Actual Behavior

_No response_

### Other Software

_No response_
Repository: flutter
Issue: TextField should respect focus and a11yfocus semantics action
Labels: a: text input,a: accessibility,P2,team-framework,triaged-framework

### Steps to reproduce

The current code in TextField treats a11yfocus event from desktop as keyboard focus event

https://github.com/flutter/flutter/blob/39472d9b6193191b8d11728bbcaf5c287bbb08bb/packages/flutter/lib/src/material/text_field.dart#L1415

https://github.com/flutter/flutter/blob/39472d9b6193191b8d11728bbcaf5c287bbb08bb/packages/flutter/lib/src/cupertino/text_field.dart#L1279

This is not accurate since we can tell the difference now https://github.com/flutter/flutter/issues/83809

This is also blocked until desktop embedding starts to use the newly added `focus` semantic action https://github.com/flutter/flutter/issues/149750
Repository: flutter
Issue: macOS embedding should send correct focus semantics actions
Labels: a: accessibility,P2,team-macos,triaged-macos

desktop screen readers has option to sync a11y focus with keyboard focus or not

macOS for example
![image](https://github.com/flutter/flutter/assets/47866232/0f1bb616-b345-4568-93c6-3c5325de9623)

Right now we only send a11y focus and framework assume it means keyboard focus see https://github.com/flutter/flutter/issues/149748

We should update the embedding so that it based on the settings to send appropriate semantics actions
Repository: pytorch
Issue: Network module memory is not released in libtorch
Labels: module: binaries,module: cpp,module: memory usage,triaged

### 🐛 Describe the bug



I tested the example code in this issue https://github.com/pytorch/pytorch/issues/106255

I fixed forward as below
```
torch::Tensor forward(torch::Tensor x)
    {
        x = fc->forward(x);
        return x;
    }
```
Here is the result
```
Memory used: 382
Memory used: 766
Memory used: 1362
Memory used: 1362
Memory used: 978
```
Unlike the example code, Even after clearing the cache, some memory remains.

I just tried
```
cudaFree(input.data_ptr());
cudaFree(output.data_ptr());
```
result is
```
Memory used: 214
```
Still remains something Where is this from and how can I release this memory?

(full code)
```
#include <torch/torch.h>
#include <c10/cuda/CUDACachingAllocator.h>
#include <iostream>

using namespace std;

class Net : public torch::nn::Module
{
public:
    Net(int fc_size = 100)
    {
        fc = torch::nn::Linear(fc_size, fc_size);
        fc->to(torch::kCUDA);
        register_module("fc", fc);
    }

    torch::Tensor forward(torch::Tensor x)
    {
        x = fc->forward(x);
        return x;
    }

private:
    torch::nn::Linear fc = nullptr;
    torch::Tensor x_copy;
};

double get_cuda_memory_usage()
{
    size_t free_mem, total_mem;
    cudaMemGetInfo(&free_mem, &total_mem);
    size_t used_mem = total_mem - free_mem;

    double used_mem_mb = used_mem / (1024.0 * 1024.0);
    return used_mem_mb;
}

void print_cuda_memory_diff(double start_mem, double end_mem)
{
    cout << "Memory used: " << end_mem - start_mem << endl;
}

void memory_test(int size, double start_memory)
{
    // Create an empty tensor
    auto input = torch::empty({size, size}).to(torch::kCUDA);
    // GPU Memory: 1 * (input)
    print_cuda_memory_diff(start_memory, get_cuda_memory_usage());

    // Create a network with same size of tensor
    Net *net = new Net(size);
    // GPU Memory: 2 * (input)
    print_cuda_memory_diff(start_memory, get_cuda_memory_usage());

    // Pass the input through the network (cloning the input)
    auto output = net->forward(input);
    // GPU Memory: 3 * (input)
    print_cuda_memory_diff(start_memory, get_cuda_memory_usage());

    delete net;
    // GPU Memory: 3 * (input) (no change) (due to cache)
    print_cuda_memory_diff(start_memory, get_cuda_memory_usage());

    // Manually clear the cache and return all unused GPU memory (just for this example) (may not be recommended)
    c10::cuda::CUDACachingAllocator::emptyCache();
    // GPU Memory: 1 * (input)
    print_cuda_memory_diff(start_memory, get_cuda_memory_usage());

    cudaFree(input.data_ptr());
    cudaFree(output.data_ptr());
    print_cuda_memory_diff(start_memory, get_cuda_memory_usage());
}

int main()
{
    auto size = 10000;
    auto start_memory = get_cuda_memory_usage();

    memory_test(size, start_memory);

    return 0;
}

```


### Versions

ubuntu 18.04 
cuda 11.8
libtorch 2.3.0

cc @seemethere @malfet @osalpekar @atalman @jbschlosser
Repository: go
Issue: x/sys/unix: access to ELF auxiliary vector
Labels: Proposal,Proposal-Accepted

### Proposal Details

like ```os.Args``` and ```os.Environ```, I was wondering why there is neither an API to get ELF auxiliary vector nor Aux type. C does provide them in ```Elf.h```
Repository: godot
Issue: AnimationPlayer.seek does not work as documented (or logical at all) with call method tracks
Labels: discussion,documentation,topic:animation

### Tested versions

Reproducible in 4.2.2.stable
not Reproducible in 4.1.4.stable and 3.x

### System information

Godot v4.2.2.stable.mono - Ubuntu 22.04.4 LTS 22.04 - X11 - Vulkan (Forward+) - dedicated NVIDIA GeForce GTX 1050 Ti (nvidia; 535.171.04) - Intel(R) Core(TM) i5-6600 CPU @ 3.30GHz (4 Threads)

### Issue description

AnimationPlayer seeking does not work as described in the [documentation](https://docs.godotengine.org/en/stable/classes/class_animationplayer.html#class-animationplayer-method-seek) in regards to functions called via call method tracks (I have not tested other tracks).
Especially "Events between the current frame and seconds" are inconsistently not "skipped".
Seeking is done via AnimationPlayer.play() directly followed by AnimationPlayer.seek().
Methods at time 0 are always called when they never should.
Methods in between 0 and the 'seeked seconds' are skipped or not depending on the animation.
And btw if events are skipped anyways (per documentation), what does 'update_only' actually do?

### Steps to reproduce

It is easier to just look at the MRP than explaining it here.

### Minimal reproduction project (MRP)

4.2 version: 
[AnimPlayerBug_v4.2.zip](https://github.com/user-attachments/files/15593778/AnimPlayerBug_v4.2.zip)
Correctly working 4.1 version:
[AnimPlayer_v4.1.zip](https://github.com/user-attachments/files/15593782/AnimPlayer_v4.1.zip)
Repository: flutter
Issue: FlutterFragmentActivity support for predictive back
Labels: P2,team-text-input,triaged-text-input

Internal: b/242216228

### Use case

Several popular pub packages ([local_auth](https://pub.dev/packages/local_auth#android-integration), [health](https://pub.dev/packages/health#android-14)) require the use of FlutterFragmentActivity in apps. Apps that use those packages should be able to support predictive back, too.

### Proposal

Predictive back support was added to FlutterActivity in https://github.com/flutter/engine/pull/52302 and to FlutterFragment in https://github.com/flutter/engine/pull/52302. Support should also be added to FlutterFragmentActivity, including support for route transitions (https://github.com/flutter/engine/pull/49093).

### What is predictive back?

<details>

<summary>Gif</summary>

![217918109-945febaa-9086-41cc-a476-1a189c7831d8](https://github.com/flutter/flutter/assets/389558/e16a49eb-cca8-4b7d-9ad0-3e46cec2f530)

</details>

### What are predictive back route transitions?

<details>

<summary>Video</summary>

https://github.com/flutter/flutter/assets/8436039/96b6dc20-89c9-45db-b8b4-aec7e996477b

</details>
Repository: PowerToys
Issue: Add basic date math support
Labels: Needs-Triage

### Description of the new feature / enhancement

I often find myself wondering 'how long ago was x date'. It would be nice to have a command that supported `now - 2021-02-03`. The default response would be the largest unit that makes sense (e.g. years in this case) but have optional support to specific '2024-02-03 - 2024-01-03 in hours`.

### Scenario when this would be used?

When I need a quick way to find the difference between two dates or datetimes.

### Supporting information

_No response_
Repository: vscode
Issue: refresh rate in zenmode is not the same as main monitor
Labels: bug,freeze-slow-crash-leak,workbench-zen,confirmation-pending

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- VS Code Version: latest
- OS Version: windows 10

Steps to Reproduce:

1. Set monitor to 240hz
2. Enter zenmode
3. Move mouse fast and check
Repository: tauri
Issue: [bug] WindowBuilder::build() taking ~10s to finish
Labels: type: bug,status: needs triage

### Describe the bug

WindowBuilder::build() sometimes takes ~10s to finish.

### Reproduction

The way I currently trigger the bug is by 
1 . compiling the v2 branch of my app https://github.com/FFFFFFFXXXXXXX/league_record/tree/v2
2. start the app
3. start a League of Legends game (practice tool)
4. immediately after the end of the game double click the tray icon to trigger app::window::open_window(...)

And if I time it right the WindowBuilder::build() function takes ~10s to run line 350 in tauri-1.6.7/src/window.rs

```rust
    let window = match &mut self.runtime {
      RuntimeOrDispatch::Runtime(runtime) => runtime.create_window(pending),
      RuntimeOrDispatch::RuntimeHandle(handle) => handle.create_window(pending), // <-- this line here
      RuntimeOrDispatch::Dispatch(dispatcher) => dispatcher.create_window(pending),
    }
```


### Expected behavior

WindowBuilder::build() completes almost immediately

### Full `tauri info` output

```text
❯ cargo tauri info

[✔] Environment
    - OS: Windows 10.0.22631 X64
    ✔ WebView2: 125.0.2535.85
    ✔ MSVC: Visual Studio Community 2022
    ✔ rustc: 1.80.0-nightly (032af18af 2024-06-02)
    ✔ cargo: 1.80.0-nightly (7a6fad098 2024-05-31)
    ✔ rustup: 1.27.1 (54dd3d00f 2024-04-24)
    ✔ Rust toolchain: nightly-x86_64-pc-windows-msvc (environment override by RUSTUP_TOOLCHAIN)
    - node: 22.2.0
    - npm: 10.2.5
    - bun: 1.1.12

[-] Packages
    - tauri [RUST]: 1.6.7 (no manifest)
    - tauri-build [RUST]: 1.5.2 (no manifest)
    - wry [RUST]: 0.24.10 (no manifest)
    - tao [RUST]: 0.16.9 (no manifest)
    - tauri-cli [RUST]: 1.5.14
    - @tauri-apps/api : not installed!
    - @tauri-apps/cli [NPM]: 1.5.14

[-] App
    - build-type: bundle
    - CSP: unset
    - distDir: ../dist
    - devPath: http://localhost:1420/
    - bundler: Vite
```

### Additional context

Also discussed on the discord: https://discord.com/channels/616186924390023171/1244404416321425418
Repository: pytorch
Issue: `torch.compile` fails with customized Triton Operator on Triton 2.2
Labels: triaged,oncall: pt2,module: inductor,module: user triton

### 🐛 Describe the bug

I made a customized Triton operator with Triton 2.2. The code works normally but when I compile the model by `torch.compile`, it returns me the following error: 
```
torch._dynamo.exc.BackendCompilerFailed: backend='inductor' raised:
LoweringException: AttributeError: 'View' object has no attribute 'layout'
  target: triton_kernel_wrapper_functional
  kwargs: {'kernel_idx': 0, 'grid': [(688, 1, 1), (688, 1, 1), (688, 1, 1), (688, 1, 1), (688, 1, 1), (688, 1, 1), (688, 1, 1), (688, 1, 1), (688, 1, 1), (688, 1, 1), (344, 1, 1), (344, 1, 1), (344, 1, 1), (344, 1, 1), (344, 1, 1), (344, 1, 1), (344, 1, 1), (344, 1, 1), (344, 1, 1), (344, 1, 1), (172, 1, 1), (172, 1, 1), (172, 1, 1), (172, 1, 1), (172, 1, 1), (172, 1, 1), (172, 1, 1), (172, 1, 1), (172, 1, 1), (172, 1, 1)], 'kwargs': {'a_ptr': TensorBox(
    View(
      SliceView(
        StorageBox(
          ComputedBuffer(name='buf19', layout=FixedLayout('cuda', torch.float16, size=[1, 1, 4096], stride=[4096, 4096, 1]), data=Pointwise(
            'cuda',
            torch.float16,
            def inner_fn(index):
  ....

Set TORCH_LOGS="+dynamo" and TORCHDYNAMO_VERBOSE=1 for more information


You can suppress this exception and fall back to eager by setting:
    import torch._dynamo
    torch._dynamo.config.suppress_errors = True
```
The code I am referring to is [simple_static.py](https://gist.github.com/ArthurZucker/af34221def212259b43d55a2811d2dbb). I replaced some operators as
```
# take mlp for example
for layer in model.model.layers:
    layer.mlp = Triton_myMLP(layer.mlp)
```

### Versions

```
Collecting environment information...
PyTorch version: 2.2.2+cu121
Is debug build: False
CUDA used to build PyTorch: 12.1
ROCM used to build PyTorch: N/A

OS: Ubuntu 22.04.3 LTS (x86_64)
GCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
Clang version: Could not collect
CMake version: version 3.22.1
Libc version: glibc-2.35

Python version: 3.9.19 (main, Mar 21 2024, 17:11:28)  [GCC 11.2.0] (64-bit runtime)
Python platform: Linux-5.15.0-105-generic-x86_64-with-glibc2.35
Is CUDA available: True
CUDA runtime version: 12.2.91
CUDA_MODULE_LOADING set to: EAGER
....
Versions of relevant libraries:
[pip3] numpy==1.26.4
[pip3] torch==2.2.2
[pip3] triton==2.2.0
[conda] numpy                     1.26.4                   pypi_0    pypi
[conda] torch                     2.2.2                    pypi_0    pypi
[conda] triton                    2.2.0                    pypi_0    pypi
```

cc @ezyang @msaroufim @bdhirsh @anijain2305 @chauhang @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @peterbell10 @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 @ColinPeppler @amjames @desertfire @oulgen @aakhundov
Repository: pytorch
Issue: Request for in-place FFT
Labels: feature,triaged,module: fft

### 🚀 The feature, motivation and pitch

I'm working on scientific simulation (Simulation of wave optics) with PyTorch and would like in-place FFT to be possible in Pytorch. PyTorch helps me a lot in the differentiable part of inverse problem, and offers me an easy way to use GPU. But, for some simulation part of physics model, I need high-performance computing, and don't need to use autograd for the gradient. Among them, FFT is one of the most memory-intensive operation in the simulation (I think its may be general to many others simulation). I know cuFFT support in-place FFT, but it's very hard for me (a physics guy) to use. If PyTorch could support in-place FFT, I think it could be a big impact in scientific simulation.

### Alternatives

_No response_

### Additional context

_No response_

cc @mruberry @peterbell10
Repository: pytorch
Issue: Future LRScheduler implementation with Tensor support
Labels: triaged,actionable,module: LrScheduler

### 🚀 The feature, motivation and pitch

Future `LRScheduler` implementation goals
1. we want to maintain the same semantics as when the lr was a Python number and not a Tensor:
    a. no inplacing -> we should not have any `fill_` in our LRScheduler math/compute. Instead we should assign with `group["lr"] = ...`.
    b. this goes hand-in-hand with cloning a copy during computation to assign back to the optimizer to avoid ever tangling the values.
2. we want to ensure that the LRScheduler preserves the "Tensorness" of the optimizer's hyperparams. In other words, if the Optimizer has a Tensor LR, the LRScheduler should always be giving it a Tensor LR to work with.

_Originally posted by @janeyx99 in https://github.com/pytorch/pytorch/issues/126854#issuecomment-2139963804_

### Alternatives

_No response_

### Additional context

_No response_
Repository: rust
Issue: Tracking Issue for `unsigned_signed_diff`
Labels: T-libs-api,C-tracking-issue

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Feature gate: `#![feature(unsigned_signed_diff)]`

This is a tracking issue for https://github.com/rust-lang/libs-team/issues/381

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### Public API

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impl uX {
        pub const fn overflowing_signed_diff(self, rhs: Self) -> (iX, bool);
	pub const fn saturating_signed_diff(self, rhs: Self) -> iX;
	pub const fn checked_signed_diff(self, rhs: Self) -> Option<iX>;
}
```

### Steps / History

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- [x] Implementation: https://github.com/rust-lang/rust/pull/126042
- [ ] Final comment period (FCP)[^1]
- [ ] Stabilization PR

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- None yet.

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Repository: vscode
Issue: Cannot backspace lines on Android
Labels: bug,editor-input,android

When a line is blank, pressing backspace on an external keyboard doesn't seem to do anything on a Codespace, which means it's impossible to get rid of empty lines. Can't select the gap using Shift + arrow keys either.

Version: 1.89.1
Commit: dc96b837cf6bb4af9cd736aa3af08cf8279f7685
User Agent: Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/125.0.0.0 Safari/537.36
Embedder: codespaces

<!-- generated by web issue reporter -->
Repository: material-ui
Issue: [material-ui][Select] Cycle On Focus Without Having Options Open
Labels: new feature,component: select,package: material-ui

### Summary

When using the Select as a drop down, it would be nice to be able to cycle through the options by typing in the first letter of the options that you'd like to cycle through. Right now it's possible to do the cycle while the options are open, but once the options are closed, hitting the keys doesn't cycle it.

### Examples

To test out the current behavior, you can go to https://mui.com/material-ui/react-select/#basic-select and click on the select to focus on it, then close the options selector. Then try and cycle through the options with the `T` key.

Here's Amazon's version of one that works as this issue states: 
https://github.com/mui/material-ui/assets/10539109/81592f3e-81ed-44bf-97cf-b752e6711afa

I was cycling by just pressing the `A` key.


### Motivation

This is a feature available on a lot of other libraries(see ChakraUI: https://v2.chakra-ui.com/docs/components/select) and just on the web in general so a similar feature on MUI would be nice.

**Search keywords**: cycle select