sharjeelyunus/github-issues-dataset huggingface dataset:
Repository: transformers
Issue: Improve batching speed for Whisper models using VAD based chunking
Labels: Feature request

### Feature request

This feature request aims to improve the speed of Whisper's batched version by adding a VAD model (such as pyannote or from NeMO or Silero) and merging chunks up to 30 sec, instead of relying on the Sliding window technique that takes up more time. 

### Motivation

In addition to the benefits stated above, the semantic chunks take care of the transcription at the 30 sec boundaries. 

### Your contribution

A similar batching has already been implemented in [faster-whisper project](https://github.com/SYSTRAN/faster-whisper/blob/c2a1da1bd94e002c38487c91c2f6b50a048000cf/faster_whisper/transcribe.py#L361) with Silero VAD. The WER and Speed on internal test data and [youtube-commons-asr-eval](https://huggingface.co/datasets/mobiuslabsgmbh/youtube-commons-asr-eval) (for long-form transcription) are better on this implementation than the current HF implementation.
Repository: tauri
Issue: [bug] http plugin does not store http-only cookies on cookie storage
Labels: type: bug,status: needs triage

### Describe the bug

I have a session cookie (http-only) returned as part of the authentication process, which is handled by Tauri's HTTP Client plugin. 
Any request that is handled by the client (within the current session), includes the received cookie, but:
- Using EventSource (SSE events) do not include the cookie, as none is found in the cookie storage within the dev tools
- Restarting the app forces a re-auth, as the cookie (with the JWT token) is not part of the storage.

### Reproduction

_No response_

### Expected behavior

HTTP Client should persist http-only cookies as part of the cookie storage.

I've set CSP settings to include the remote address, but that did not work either:

```
"security": {
  "csp": {
    "default-src": "'self' customprotocol: asset: https://api.server.com/",
    "connect-src": "ipc: http://ipc.localhost https://api.server.com/"
  }
}
```

### Full `tauri info` output

```text
> tauri info


[✔] Environment
    - OS: Arch Linux Rolling Release x86_64 (X64)
    ✔ webkit2gtk-4.1: 2.46.2
    ✔ rsvg2: 2.59.1
    ✔ rustc: 1.82.0 (f6e511eec 2024-10-15)
    ✔ cargo: 1.82.0 (8f40fc59f 2024-08-21)
    ✔ rustup: 1.27.1 (2024-05-07)
    ✔ Rust toolchain: stable-x86_64-unknown-linux-gnu (default)
    - node: 22.10.0
    - yarn: 1.22.22
    - npm: 10.9.0

[-] Packages
    - tauri 🦀: 2.0.6
    - tauri-build 🦀: 2.0.2
    - wry 🦀: 0.46.3
    - tao 🦀: 0.30.3
    - @tauri-apps/api : 2.0.3
    - @tauri-apps/cli : 2.0.5

[-] Plugins
    - tauri-plugin-fs 🦀: 2.0.3
    - @tauri-apps/plugin-fs : not installed!
    - tauri-plugin-shell 🦀: 2.0.2
    - @tauri-apps/plugin-shell : 2.0.1
    - tauri-plugin-http 🦀: 2.0.3
    - @tauri-apps/plugin-http : 2.0.1

[-] App
    - build-type: bundle
    - CSP: unset
    - frontendDist: ../../frontend/www
    - bundler: Vite
```


### Stack trace

_No response_

### Additional context

_No response_
Repository: PowerToys
Issue: [pt run] Add what program was run to logger for audit.  
Labels: Help Wanted,Product-PowerToys Run,Cost-Small,Run-Plugin

### Description of the new feature / enhancement

I love to use PowerToys Run. However, I accidentally ran an application uninstaller as the search unexpectedly included it as a top result. Pressing enter will execute the uninstall immediately without asking for confirmation, leading to the application being uninstalled without any way to abort. Some uninstallers ask for confirmation during startup, but not all. This is an even bigger problem as not all uninstallers have the application's name visible, making it hard to find out what was removed. The lack of a PowerToys Run execution log also adds to this problem.

A new option to exclude uninstallers would be the best solution (if possible), but I'm open to other solutions to the core problem. Another solution is a box where I can enter partial strings that would be excluded from the search result (adding "uninstall" would omit any result with that as part of the name). 

### Scenario when this would be used?

Not having to worry about accidentally running a destructive operation would speed up my workflow, as an incorrect Run search would not potentially cause an application to be removed.

### Supporting information

_No response_
Repository: pytorch
Issue: Triton pre_hooks are ignored by torch.compile
Labels: high priority,triaged,oncall: pt2,module: user triton

### 🐛 Describe the bug

`torch.compile` is ignoring the `pre_hook` argument defined in `triton.Config`, which makes models using some Triton kernels output wrong results. 
Here's a simple example to reproduce the issue: a Triton kernel that adds values (1 + 1), but it uses `atomic_add`, the output is initialized with 1. The pre_hook sets the output to zero, so if the hook is working properly the expected value should be 2, if the pre_hook is ignored the output would be 3: 

```Python
import torch
import triton
import triton.language as tl

def init_to_zero(name):
    return lambda nargs: nargs[name].zero_()

def get_default_config():
    config = triton.Config({'BLOCK_SIZE':1024}, num_warps=4, num_stages=2, pre_hook=init_to_zero("output_ptr"))
    return [config]

@triton.autotune(configs = get_default_config(), key=['n_elements'],)
@triton.jit
def add_kernel(x_ptr, y_ptr, output_ptr, n_elements, BLOCK_SIZE: tl.constexpr):

    pid = tl.program_id(axis=0)  

    block_start = pid * BLOCK_SIZE
    offsets     = block_start + tl.arange(0, BLOCK_SIZE)
    mask        = offsets < n_elements

    x = tl.load(x_ptr + offsets, mask=mask)
    y = tl.load(y_ptr + offsets, mask=mask)
    output = x + y
    tl.atomic_add(output_ptr + offsets, output, mask=mask)


def add(x: torch.Tensor, y: torch.Tensor) -> torch.Tensor:
    output     = torch.ones(x.shape, device=x.device, dtype=x.dtype)
    n_elements = output.numel()
    grid       = lambda meta: (triton.cdiv(n_elements, meta['BLOCK_SIZE']), )
    add_kernel[grid](x, y, output, n_elements)
    return output


x = torch.ones((4096,), device='cuda:0', dtype=torch.float16)
y = torch.ones((4096,), device='cuda:0', dtype=torch.float16)

assert add(x, y).mean() == 2, "Problem with add kernel"

for mode in ['reduce-overhead', 'max-autotune-no-cudagraphs']:
    add_compiled = torch.compile(add, mode=mode, fullgraph=True)  
    val = add_compiled(x, y).mean().item()  
    if(val != 2):
        print("pre_hook ignored with " + mode, 'expected 2, but found ' + str(val))


# pre_hook ignored with reduce-overhead expected 2, but found 3.0
# pre_hook ignored with max-autotune-no-cudagraphs expected 2, but found 3.0
```

The current workaround is to initialize the output via `torch.zeros` but that's much slower. To give you numbers with Llama2-7B on the 4090, the decoding speed is 184 tokens/sec with the pre-hook on and using `torch.empty` to initialize the output, vs 178 tokens/sec by using `torch.zeros` to initialize the output. 

### Versions

PyTorch version: 2.6.0.dev20241027+cu121
CUDA used to build PyTorch: 12.1

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 3.26.4
Libc version: glibc-2.35

[pip3] pytorch-triton==3.1.0+cf34004b8a
[pip3] triton==3.1.0

cc @ezyang @gchanan @zou3519 @kadeng @msaroufim @chauhang @penguinwu @oulgen @aakhundov @davidberard98
Repository: deno
Issue: deno cache doesn't discover all deps / deno test adds extra deps?
Labels: bug

Version: deno 2.0.3 (stable, release, aarch64-apple-darwin)

Minimal reproducible example:

* Clone https://github.com/brc-dd/deno-cache-not-stable
* Run:
  ```sh
  deno cache --reload --lock=deno.lock foo.test.ts
  ```
* Notice that there is no change in deno.lock.
* Now run:
  ```sh
  deno test
  ```
* It adds `npm:@types/node@*` to deno.lock.

Additional context:
* Doesn't happen if `deno.json` is not present.
* cliffy indeed has some  dynamic `node:` imports - https://github.com/search?q=repo:c4spar/deno-cliffy%20node:&type=code
* Likely an issue in deno_graph or are statically-analyzable dynamic imports not supported? 👀 

---

Posting contents for completeness:

```ts
// foo.test.ts
import {} from 'jsr:@cliffy/prompt@^1.0.0-rc.7'
```

```diff
diff --git a/deno.lock b/deno.lock
index 5332053..c9550de 100644
--- a/deno.lock
+++ b/deno.lock
@@ -10,7 +10,8 @@
     "jsr:@std/fmt@~1.0.2": "1.0.3",
     "jsr:@std/io@~0.224.9": "0.224.9",
     "jsr:@std/path@~1.0.6": "1.0.7",
-    "jsr:@std/text@~1.0.7": "1.0.8"
+    "jsr:@std/text@~1.0.7": "1.0.8",
+    "npm:@types/node@*": "22.5.4"
   },
   "jsr": {
     "@cliffy/ansi@1.0.0-rc.7": {
@@ -58,5 +59,16 @@
     "@std/text@1.0.8": {
       "integrity": "40ba34caa095f393e78796e5eda37b8b4e2cc6cfd6f51f34658ad7487b1451e4"
     }
+  },
+  "npm": {
+    "@types/node@22.5.4": {
+      "integrity": "sha512-FDuKUJQm/ju9fT/SeX/6+gBzoPzlVCzfzmGkwKvRHQVxi4BntVbyIwf6a4Xn62mrvndLiml6z/UBXIdEVjQLXg==",
+      "dependencies": [
+        "undici-types"
+      ]
+    },
+    "undici-types@6.19.8": {
+      "integrity": "sha512-ve2KP6f/JnbPBFyobGHuerC9g1FYGn/F8n1LWTwNxCEzd6IfqTwUQcNXgEtmmQ6DlRrC1hrSrBnCZPokRrDHjw=="
+    }
   }
 }
```
Repository: vscode
Issue: Option to enable `tsconfig.json` relative loading of TypeScript language service plugins
Labels: feature-request,typescript

<!-- ⚠️⚠️ 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. -->

<!-- Describe the feature you'd like. -->
Support resolving TypeScript language service plugins relative to the `tsconfig.json` that lists them. Right now only plugins relative to the TypeScript instance are (implicitly) allowed, which is problematic when using a strict package manager like pnpm.

To be clear, I'm not asking for this to be enabled by default. That would go against the existing VSCode defaults. It would be nice is VSCode created a notification when a plugin could not be resolved and local plugin loads was disabled, so that devs are aware and can make the necessary configuration changes, though that is a bigger ask.

As far as implementing this, TypeScript itself _can_ perform correct resolution (needs `allowLocalPluginLoads: true`) and the TS web implementation of the language server actually has this wired up partially.

https://github.com/microsoft/vscode/blob/a14300ec9f7d04fbbaa9f896d46626110baa2b90/extensions/typescript-language-features/web/src/webServer.ts#L51

## Example

* Workspace (VSCode Window) Root: `/Users/__/__/__/web/`
* Repo Root: `/Users/__/__/__/`
* TypeScript (apparent): `/Users/__/__/__/web/node_modules/typescript`
* TypeScript (resolved): `/Users/__/__/__/node_modules/.pnpm/typescript@5.5.4/node_modules/typescript`
* Plugin: `/Users/__/__/__/web/node_modules/@__/__-plugin`
* TS Config: `/Users/__/__/__/web/tsconfig.json`

In this scenario the workspace TypeScript version is being used. Since the resolved path for the TypeScript package is outside the `web/` directory, the plugin cannot be resolved.

To get around this issue we've added `@__/__-plugin` to pnpm's public hoist patterns (so it appears in `/Users/__/__/__/node_modules`) which isn't ideal. It's the same kind of issue as what ESLint (the tool itself, not the extension specifically) has had historically (a big enough issue that even in pnpm v9 `*eslint*` is a default public hoist pattern).

An alternative workaround is adding the plugin path (or the `node_modules` containing it) to `typescript.tsserver.pluginPaths` however this is an imperfect, brittle, and at worst incorrect (wrong plugin version could be resolved) solution.

## Related

* #45856
* #46443
Repository: angular
Issue: Injector Tree diagrams reset on every change detection
Labels: area: devtools

### Is this a bug report or a feature request?

- [x] Bug Report
- [ ] Feature Request

### Please provide the steps to reproduce the issue [Bug Report only]

1. Open the stackblitz [stackblitz](https://stackblitz.com/edit/buncow?file=src%2Fmain.ts), which does nothing except trigger a change detection every second.
2. Open the Angular devtools on the page.
3. Navigate to the injector tree tab in the Angular devtools.
4. Pan either the environment hierarchy or injector hierarchy diagrams. 
5. Observe that the view you panned resets after at most one second, when the change detection happens.

### Please provide the expected behavior vs the actual behavior you encountered [Bug Report only]

Actual behaviour: the diagrams move to the roots of the hierarchies whenever change detection happens.

Expected behaviour:
1. If the hierarchy doesn’t change at all, the current state of the diagram (panning and zoom) should stay as they were before the change detection.
2. It would be awesome (though probably hard to achieve) to not change the panning and zoom even if there are (some) changes to the hierarchy, though the exact expected behaviour is probably up to a lot of debate. This part is more of a feature request and probably out of scope for the bug fix, but I wanted to mention it.

### Please provide a screenshot if possible [Bug Report only]

_No response_

### Please provide the exception or error you saw [Bug Report only]

No error

### Is this a browser-specific issue? If so, please specify the device, browser, and version. [Bug Report only]

Reproducible in Firefox and chromium

### Description [Feature Request only]

_No response_

### Proposed solution [Feature Request only]

_No response_

### Alternatives considered [Feature Request only]

_No response_
Repository: godot
Issue: Godot editor becomes unresponsive when the WM_SETTINGCHANGE or WM_SYSCOLORCHANGE message is received
Labels: bug,platform:windows,topic:porting

### Tested versions

- Reproducible in: 4.3-stable [77dcf97]

### System information

Godot v4.3.stable (77dcf97d8) - Windows 10.0.19045 - Vulkan (Forward+) - dedicated NVIDIA GeForce RTX 2080 Super with Max-Q Design (NVIDIA; 32.0.15.6590) - Intel(R) Core(TM) i7-10750H CPU @ 2.60GHz (12 Threads)

### Issue description

I downloaded Godot 4.3 stable and while using it I noticed that it would periodically become unresponsive. After building from source I attached the debugger using Visual Studio and paused execution during one of these periods of unresponsiveness. It looks like the handling of WM_SETTINGCHANGE or WM_SYSCOLORCHANGE in DisplayServerWindows::WndProc can take a long time. Further up the callstack is EditorNode::_update_theme.

I have my Windows background set to a slide show, so I guess I was hitting this each time the slide changed.

I have 'Follow System Theme' disabled in my editor settings. Should the WM_SETTINGCHANGE or WM_SYSCOLORCHANGE messages be ignored in this case?

### Steps to reproduce

* Create a new project in the project manager
* Wait for the new project to load
* Open Settings from the Windows 10 start menu
* Open Personalisation > Background
* Change the background picture
* Click on the Godot Engine window. It will be unresponsive but will eventually recover
* If you have Visual Studio attached while the Godot window is unresponsive you can break and find a thead calling DisplayServerWindows::WndProc and handling a WM_SETTINGCHANGE or WM_SYSCOLORCHANGE message

Edit: Found out later that this will *not* repro if you have 'Automatically pick an accent colour from my background' disabled in your 'Personalisation > Colours' section of Windows Settings.

### Minimal reproduction project (MRP)

This can be reproduced in a new project created in the project manager.
Repository: ollama
Issue: Please update NuExtract to v1.5
Labels: model request

Please update [NuExtract](https://ollama.com/library/nuextract) to the newest version on [huggingface](https://huggingface.co/numind/NuExtract-v1.5/tree/main)
Repository: storybook
Issue: Svelte CSF issue with Save from Controls
Labels: bug,svelte,addon: controls,sveltekit,sev:S2

### Describe the bug

When a user tries to use the Save from Controls feature in a Svelte project with template syntax, it throws a cryptic error message without any helpful information to the user when he attempts to use any of the workflow controls (e.g., Update Story, Save new Story). This issue is reproducible in the latest Storybook version and also in the latest pre-release version.

Below is a recording of the issue:

https://github.com/user-attachments/assets/49cf4879-8fca-4b32-8f72-309d5da61363

As an aside, the documentation will be updated to reflect this limitation. However, it would be ideal to turn off the feature for Svelte projects until it is fully supported to avoid confusion or provide a more informative error message to the user when the feature is not supported in the current context.


cc @JReinhold 

### Reproduction link

https://stackblitz.com/edit/github-vbubyc?file=src%2Fstories%2FButton.stories.svelte

### Reproduction steps

1. Create a new Svelte project
2. Add Storybook to the project
3. Open a Svelte native template syntax story file (e.g., `Button.stories.svelte`)
4. Try to use any part of the feature (e.g., Update Story, Save new Story)


### System

```shelL
Storybook Environment Info:

  System:
    OS: macOS 15.0.1
    CPU: (8) arm64 Apple M3
    Shell: 5.9 - /bin/zsh
  Binaries:
    Node: 20.13.1 - ~/.nvm/versions/node/v20.13.1/bin/node
    Yarn: 1.22.21 - /usr/local/bin/yarn
    npm: 10.5.2 - ~/.nvm/versions/node/v20.13.1/bin/npm <----- active
    pnpm: 9.12.2 - /opt/homebrew/bin/pnpm
  Browsers:
    Chrome: 130.0.6723.70
    Edge: 130.0.2849.56
    Safari: 18.0.1
  npmPackages:
    @storybook/addon-essentials: ^8.3.6 => 8.3.6
    @storybook/addon-interactions: ^8.3.6 => 8.3.6
    @storybook/addon-links: ^8.3.6 => 8.3.6
    @storybook/addon-svelte-csf: ^5.0.0-next.8 => 5.0.0-next.8
    @storybook/blocks: ^8.3.6 => 8.3.6
    @storybook/svelte: ^8.3.6 => 8.3.6
    @storybook/sveltekit: ^8.3.6 => 8.3.6
    @storybook/test: ^8.3.6 => 8.3.6
    storybook: ^8.3.6 => 8.3.6
```

### Additional context

_No response_
Repository: yt-dlp
Issue: Convert slides/storyboards to video
Labels: enhancement,core:post-processor

### DO NOT REMOVE OR SKIP THE ISSUE TEMPLATE

- [X] I understand that I will be **blocked** if I *intentionally* remove or skip any mandatory\* field

### 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 have **updated yt-dlp to nightly or master** ([update instructions](https://github.com/yt-dlp/yt-dlp#update-channels))
- [X] I've searched [known issues](https://github.com/yt-dlp/yt-dlp/issues/3766) and 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)

### Provide a description that is worded well enough to be understood

Sometimes the slides may be higher quality than the video itself. Ideally, this could be combined with the audio from the video. However, the current mhtml implementation of slides does not allow this.

I envision that the slides could be shown sequentially, each running from the timestamp it appears until the next slide appears. Essentially this would be creating a video from the slides.

This would be useful for lectures as mediasite often saves video in very poor quality, but often takes high quality screenshots of the lecture and displays them instead of the video.

However, I do recognise that currently mediasite slide extraction is broken (per https://github.com/yt-dlp/yt-dlp/issues/10320) so instead YouTube could be used as a place to start as the current mhtml "storyboards" calculate the start and end time of each storyboard and the duration of each, so these values could be used to stitch them together.

### Provide verbose output that clearly demonstrates the problem

- [ ] Run **your** yt-dlp command with **-vU** flag added (`yt-dlp -vU <your command line>`)
- [ ] If using API, add `'verbose': True` to `YoutubeDL` params instead
- [ ] Copy the WHOLE output (starting with `[debug] Command-line config`) and insert it below

### Complete Verbose Output

_No response_
Repository: pytorch
Issue: Covert Conv3d to Conv2d, But output different
Labels: module: convolution,triaged

### 🐛 Describe the bug

I tried to convert a Conv3d to Conv2d by splitting 3D kernels by the temporal axis, but outputs from the two differ:
<img width="531" alt="image" src="https://github.com/user-attachments/assets/27a5e7fb-67fa-4fcb-a593-ccdaee44ba38">
<img width="1050" alt="image" src="https://github.com/user-attachments/assets/b7d6bc4e-a0c2-40be-b4de-851800ab5f96">
I expect output1 and output2 should be the same. Any details I've overlooked?

code:
```
t = torch.randn(1, 1, 4, 4, dtype=torch.float32)
conv3d = torch.nn.Conv3d(out_channels=1, in_channels=1, kernel_size=(2,2,2), stride=(2,2,2), bias=False, dtype=torch.float32)
# conv3d2 = torch.nn.Conv3d(out_channels=1, in_channels=1, kernel_size=(2,2,2), stride=(2,2,2), bias=False, dtype=torch.bfloat16)
# conv3d.weight.data = torch.ones(1, 1, 2, 2, 2, dtype=torch.bfloat16)
# conv3d2.weight.data = conv3d.weight.data
conv2d1 = torch.nn.Conv2d(in_channels=1, out_channels=1, kernel_size=(2,2), stride=(2,2), bias=False, dtype=torch.float32)
conv2d2 = torch.nn.Conv2d(in_channels=1, out_channels=1, kernel_size=(2,2), stride=(2,2), bias=False, dtype=torch.float32)
# conv2d3 = torch.nn.Conv2d(in_channels=3, out_channels=12, kernel_size=(14,14), stride=(14,14), bias=False)
# print(conv3d.weight.shape)
# conv2d1.weight = torch.nn.parameter.Parameter(conv3d.weight.detach().reshape(12, 6, 14, 14).contiguous())
# conv2d3.weight = torch.nn.parameter.Parameter(torch.mean(conv3d.weight.detach(), dim=2).squeeze(dim=2))

print(conv3d.weight.data.dtype)
conv2d1.weight.data = conv3d.weight.data[:,:, 0, :, :]
conv2d2.weight.data = conv3d.weight.data[:,:, 1, :, :]


input = torch.stack([t, t], dim=0).view(-1, 1, 2, 2, 2)
# print(input.shape)
output1 = conv3d(input).view(-1, 1)
output2 = (conv2d1(input[:, :, 0, :, :]) + conv2d2(input[:, :, 1, :, :])).view(-1, 1)
# output3 = conv3d2(input).view(-1, 1)
print(output1==output2)
```

### Versions

PyTorch version: 2.4.1
Is debug build: False
CUDA used to build PyTorch: None
ROCM used to build PyTorch: N/A

OS: macOS 15.0.1 (arm64)
GCC version: Could not collect
Clang version: 16.0.0 (clang-1600.0.26.3)
CMake version: version 3.28.1
Libc version: N/A

Python version: 3.10.13 (main, Sep 11 2023, 08:16:02) [Clang 14.0.6 ] (64-bit runtime)
Python platform: macOS-15.0.1-arm64-arm-64bit
Is CUDA available: False
CUDA runtime version: No CUDA
CUDA_MODULE_LOADING set to: N/A
GPU models and configuration: No CUDA
Nvidia driver version: No CUDA
cuDNN version: No CUDA
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True

CPU:
Apple M3 Max

Versions of relevant libraries:
[pip3] numpy==1.26.3
[pip3] torch==2.4.1
[pip3] torchaudio==2.4.1
[pip3] torchvision==0.19.1
[conda] numpy                     1.26.3                   pypi_0    pypi
[conda] torch                     2.4.1                    pypi_0    pypi
[conda] torchaudio                2.4.1                    pypi_0    pypi
[conda] torchvision               0.19.1                   pypi_0    pypi