sharjeelyunus/github-issues-dataset huggingface dataset:
Repository: tauri
Issue: [bug] Importing javascript for webworker does not work on Mac OS webview for prod build
Labels: type: bug,status: needs triage

### Describe the bug

When I try to import a webworker in prod build, the worker script fails to parse. It looks like the server is responding with HTML, not the javascript file, and I see error "SyntaxError: Unexpected token '<'" in the dev tools console.

In dev build everything works as expected. Is there a bug here, or am I importing the worker incorrectly?

### Reproduction

Link to minimal tauri app for reproduction: https://github.com/mattijauhiainen/WebWorkerRepro/commit/2f14494d429f969d5ae0389cc30a68b3f06d3bd1

To reproduce
1. Run the app with `npm run tauri build`
2. Observe the error in dev tools

Reproduces on Mac OS, have not tested on other platforms.

### Expected behavior

Expected behaviour is the worker script to parse and execute the log statement.

### Full `tauri info` output

```text
> webworkerrepro@0.0.0 tauri /Users/matti/work/WebWorkerRepro
> tauri "info"


[✔] Environment
    - OS: Mac OS 14.5.0 X64
    ✔ Xcode Command Line Tools: installed
    ✔ rustc: 1.72.0 (5680fa18f 2023-08-23)
    ✔ cargo: 1.72.0 (103a7ff2e 2023-08-15)
    ✔ rustup: 1.26.0 (5af9b9484 2023-04-05)
    ✔ Rust toolchain: stable-aarch64-apple-darwin (default)
    - node: 18.18.2
    - pnpm: 8.15.4
    - npm: 9.8.1
    - bun: 1.0.3

[-] Packages
    - tauri [RUST]: 1.6.7
    - tauri-build [RUST]: 1.5.2
    - wry [RUST]: 0.24.10
    - tao [RUST]: 0.16.9
    - @tauri-apps/api [NPM]: 1.5.6
    - @tauri-apps/cli [NPM]: 1.5.14

[-] App
    - build-type: bundle
    - CSP: unset
    - distDir: ../dist
    - devPath: http://localhost:1420/
    - bundler: Vite

```
```


### Stack trace

_No response_

### Additional context

_No response_
Repository: transformers
Issue: Add support for non-CUDA architectures at the same time Bitsandbytes is doing it
Labels: Feature request

### Feature request

Currently, the helper/setup functions explicitly check for CUDA support:
https://github.com/huggingface/transformers/blob/8685b3c5d2dd2550527773d2a02499495a759e31/src/transformers/quantizers/quantizer_bnb_4bit.py#L60-L63

BNB is currently doing a project to enable support for other GPU backends:
[ALPHA TESTERS WANTED](https://github.com/TimDettmers/bitsandbytes?tab=readme-ov-file#alpha-testers-wanted-multi-backend-refactor-amd-gpu--intel-cpugpu-specific-bnb-backend-implementations)

### Motivation

Apple MPS support is being added for so many major players, it'd be great for the biggest one of all to support it as its dependencies do. Also would be good to not hard-code this kind of limitation so that code updates aren't necessary as dependent libraries update themselves...

### Your contribution

idea done
Repository: pytorch
Issue: [inductor] Unlinked nodes in IR graph of hf_BigBird
Labels: triaged,oncall: pt2,module: inductor

### 🐛 Describe the bug

To reproduce:
```bash
TORCH_COMPILE_DEBUG=1  TORCH_LOGS="+inductor" INDUCTOR_POST_FUSION_SVG=1   python benchmarks/dynamo/torchbench.py  --performance  -dcuda --inference --inductor --bfloat16  --disable-cudagraphs  --only hf_BigBird
```
For performance testing, a portion of the generated IR graph is shown below. The buf16 is used by buf17 and there is an arrow between them. 
<img width="783" alt="image" src="https://github.com/pytorch/pytorch/assets/3823240/278dc342-a330-4b02-86a1-19c84f1c52c7">

However, if I changed `--performance` to `--accuracy`, this portion is changed to the below. 

<img width="805" alt="image" src="https://github.com/pytorch/pytorch/assets/3823240/83b0e421-f1b8-4f85-8ce5-9349f64c643f">

Buf16 doesn't have users anymore, and there are no other connections with any other nodes. I guess it is supposed to be removed by deadcode remove stage, but somehow it fails. 


### Versions

nightly

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
Repository: tauri
Issue: [V2] DragDrop content between webviews
Labels: type: feature request

### Describe the problem

Trying to drag an image from a Tauri webview ( web page ) to another Tauri webview ( Tauri UI ) in the same window.

It fires a drop event - with no file path ( as dragged from one Tauri webview to another ) - it would be nice to drop any content ( image / text / html / files / etc ) and get the content directly in Rust.

..in harmony with "drop on tray" event as requested here --> ( https://github.com/tauri-apps/tauri/issues/7894 )

### Describe the solution you'd like

Catch items like text / image / file / source etc when I drag from one webview to another ( or drop on the tray )

### Alternatives considered

I can disable Rust filedrop - and handle everything via webview JS - now I can do image, text, HTML, files...  ..but have to juggle things in JS to get it to Rust.
 
_No response_

### Additional context

_No response_
Repository: vscode
Issue: Expected pattern to be a non-empty string
Labels: bug,search

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Does this issue occur when all extensions are disabled?: No

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- VS Code Version: Version: 1.89.1
Commit: dc96b837cf6bb4af9cd736aa3af08cf8279f7685
Date: 2024-05-07T05:17:15.788Z (4 wks ago)
Browser: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/125.0.0.0 Safari/537.36 Edg/125.0.0.0
- OS Version: Microsoft Edge Version 125.0.2535.67 (Official build) (arm64)

Steps to Reproduce:

1. Go to settings.json
2. Add an empty string to `files.exclude` like so 
```json
 "files.exclude": {
        "": true
        }
```

3. Hit `cmd`+`shift`+`f`
 or open project wide search from side panel.
4. Search something and it will show you an error message.

<img width="246" alt="image" src="https://github.com/microsoft/vscode/assets/13527277/b9c0dcb7-16f2-45c1-b795-c4084169a1c7">
Repository: next.js
Issue: Flask + NextJs works locally but Flask api do not work on Vercel
Labels: create-next-app,bug,Script (next/script)

### Link to the code that reproduces this issue

https://github.com/arnaud0617/nextjs-boilerplate

### To Reproduce

1. I deployed the NexJS-boilerplate on vercel : it works

2. I added flask and it works locally 
    http://localhost:3000/api/hello > return the right message "Hello! This is Arnaud, from Flask"

2. I uploaded in Vercel and get the error
"https://****-projects.vercel.app/" is still working
"https://***-projects.vercel.app/api/hello" is not working

I get the following error
404: NOT_FOUND
Code: DNS_HOSTNAME_RESOLVED_PRIVATE
ID: sfo1::n8s7h-1717543156736-e703ce3d0392


**index.py**
from flask import Flask
app = Flask(__name__)

@app.route('/api/hello', methods=['GET'])
def hello_world():
    return "Hello! This is Arnaud, from Flask"

if __name__ == '__main__':
    app.run(debug=True, port=5328)

**next.config.js**
module.exports = {
    async rewrites() {
      return [
        {
          source: '/api/:path*',
          destination: 'http://localhost:5328/api/:path*', // Proxy to Backend
        },
      ]
    },
  }

**requirements.txt**
Flask==3.0.3


### Current vs. Expected behavior

1. I deployed the NexJS-boilerplate on vercel : it works

2. I added flask and it works locally 
    http://localhost:3000/api/hello > return the right message "Hello! This is Arnaud, from Flask"

2. I uploaded in Vercel and I does not work. I get the error
404: NOT_FOUND
Code: DNS_HOSTNAME_RESOLVED_PRIVATE
ID: sfo1::n8s7h-1717543156736-e703ce3d0392


**index.py**
from flask import Flask
app = Flask(__name__)

@app.route('/api/hello', methods=['GET'])
def hello_world():
    return "Hello! This is Arnaud, from Flask"

if __name__ == '__main__':
    app.run(debug=True, port=5328)

**next.config.js**
module.exports = {
    async rewrites() {
      return [
        {
          source: '/api/:path*',
          destination: 'http://localhost:5328/api/:path*', // Proxy to Backend
        },
      ]
    },
  }

**requirements.txt**
Flask==3.0.3

### Provide environment information

```bash
npx --no-install next info

Operating System:
  Platform: win32
  Arch: x64
  Version: Windows 11 Pro
  Available memory (MB): 16245
  Available CPU cores: 8
Binaries:
  Node: 20.13.1
  npm: N/A
  Yarn: N/A
  pnpm: N/A
Relevant Packages:
  next: 14.2.3 // Latest available version is detected (14.2.3).
  eslint-config-next: 14.2.3
  react: 18.2.0
  react-dom: 18.2.0
  typescript: 5.4.5
Next.js Config:
  output: N/A
```


### Which area(s) are affected? (Select all that apply)

Not sure, create-next-app, Script (next/script)

### Which stage(s) are affected? (Select all that apply)

Vercel (Deployed)

### Additional context

_No response_
Repository: vscode
Issue: Installer Automatically Selects Drive Not There
Labels: bug,install-update,windows

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<!-- 🔧 Launch with `code --disable-extensions` to check. -->
It always go to the E:\ drive and I don't know how to reset the installer

Does this issue occur when all extensions are disabled?: No, as it takes place in the installer

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- VS Code Version: 1.89.1
- OS Version: Windows 11
Repository: awesome-mac
Issue: 🎉 Add 1Break(一休)
Labels: addition

### 🪩 Provide a link to the proposed addition

https://apps.apple.com/cn/app/id6467176005

### 😳 Explain why it should be added

1Break is a break reminder tool that can help Mac users take regular breaks, protect their eyes, and improve work efficiency.
The 20-20-20 rule is used by default, and users can also customize their rest plans.

### 📖 Additional context

![Frame 2-2](https://github.com/jaywcjlove/awesome-mac/assets/9877154/af05ffed-c0b0-47f7-a306-13665ebd5bd5)
![Frame 3-2](https://github.com/jaywcjlove/awesome-mac/assets/9877154/9070a7a9-9383-41ec-8e46-e935a288766c)
![Frame 4-2](https://github.com/jaywcjlove/awesome-mac/assets/9877154/d83f4577-5100-48a4-ba3d-8493f16bb3a2)
![Frame 5-2](https://github.com/jaywcjlove/awesome-mac/assets/9877154/c2eb4c48-3bde-43ec-a620-af62ce8cd184)


### 🧨 Issue Checklist

- [X] I have checked for other similar issues
- [X] I have explained why this change is important
- [X] I have added necessary documentation (if appropriate)
Repository: ollama
Issue: I encountered this error when converting the Tongyi-Finance-14B-Chat-Int4-AWQ model
Labels: bug

### What is the issue?

`(.venv) [root@bastion ollama]# python llm/llama.cpp/convert-hf-to-gguf.py ./model  --outtype f16 --outfile converted.bin
INFO:hf-to-gguf:Loading model: model
INFO:gguf.gguf_writer:gguf: This GGUF file is for Little Endian only
INFO:hf-to-gguf:Set model parameters
INFO:hf-to-gguf:Set model tokenizer
Traceback (most recent call last):
  File "/root/model/ollama/llm/llama.cpp/convert-hf-to-gguf.py", line 2865, in <module>
    main()
  File "/root/model/ollama/llm/llama.cpp/convert-hf-to-gguf.py", line 2850, in main
    model_instance.set_vocab()
  File "/root/model/ollama/llm/llama.cpp/convert-hf-to-gguf.py", line 1592, in set_vocab
    self._set_vocab_qwen()
  File "/root/model/ollama/llm/llama.cpp/convert-hf-to-gguf.py", line 530, in _set_vocab_qwen
    assert len(merged) == 2
AssertionError
`

### OS

Linux

### GPU

Nvidia

### CPU

Intel

### Ollama version

0.1.41
Repository: godot
Issue: ResourceLoader.CACHE_MODE_REPLACE does not work
Labels: discussion,topic:core

### Tested versions

Godot Engine v4.3.dev6.official.89850d553

### System information

Windows 11, Vulkan API 1.3.205 - Forward+ - Using Vulkan Device #0: NVIDIA - NVIDIA GeForce RTX 3060 Ti

### Issue description

Load a resource, then modify this resouce, then load the resource again with `ResourceLoader.load(path, "", ResourceLoader.CACHE_MODE_REPLACE)`, it returns the same resource as before.

```
func _ready() -> void:
	var path = "res://test.txt"
	var file = FileAccess.open(path, FileAccess.WRITE)
	file.store_string("00000000")
	file.flush()
	
	var mt = load(path) as MyTxt # MyTxt is a custom Resource loaded by a custom ResourceFormatLoader
	printt("before", mt, mt.content)
	
	file.store_string("yyyyyyyyyyyyyyy")
	file.flush()
	
	var mt2 = ResourceLoader.load(path, "", ResourceLoader.CACHE_MODE_REPLACE)
	printt("after using replace", mt2, mt2.content)
	
	var mt3 = ResourceLoader.load(path, "", ResourceLoader.CACHE_MODE_IGNORE)
	printt("after using ignore", mt3, mt3.content)
	
	print()
	print("Another case load an image...")
	
	var icon = load("res://icon.svg")
	printt("icon before", icon)
	var icon2 = ResourceLoader.load("res://icon.svg", "", ResourceLoader.CACHE_MODE_REPLACE)
	printt("icon after replace", icon2)
	var icon3 = ResourceLoader.load("res://icon.svg", "", ResourceLoader.CACHE_MODE_IGNORE)
	printt("icon after ignore", icon3)
```
output：
```
before	<Resource#-9223372008383838972>	00000000
after using replace	<Resource#-9223372008383838972>	00000000
after using ignore	<Resource#-9223372008115403521>	00000000yyyyyyyyyyyyyyy

Another case load an image...
icon before	<CompressedTexture2D#-9223372007981185787>
icon after replace	<CompressedTexture2D#-9223372007981185787>
icon after ignore	<CompressedTexture2D#-9223372007461092088>
```

I think`mt2` and `mt` should be two different Object, and  `icon2` and `icon` should be two different Object. Am I correct?

### Steps to reproduce

1. open MRP
2. run project.

### Minimal reproduction project (MRP)

[test_resouce_load.zip](https://github.com/user-attachments/files/15572638/test_resouce_load.zip)
Repository: pytorch
Issue: Tensor subclass constructor via autograd function is error prone re mutation
Labels: module: autograd,triaged,needs design,tensor subclass

### 🐛 Describe the bug

```
import torch
from torch.utils._pytree import tree_map_only

class T(torch.Tensor):
    def __new__(cls, inner, *, requires_grad=False):
        res = torch.Tensor._make_wrapper_subclass(
            cls,
            size=inner.size(),
            strides=inner.stride(),
            storage_offset=inner.storage_offset(),
            dtype=inner.dtype,
            layout=inner.layout,
            device=inner.device,
            requires_grad=requires_grad,
        )
        res.inner = inner
        return res

    def __torch_dispatch__(self, func, types, args=(), kwargs=None):
        if kwargs is None:
            kwargs = {}
        inner_args, inner_kwargs = tree_map_only(T, lambda t: t.inner, (args, kwargs))
        inner_res = func(*inner_args, **inner_kwargs)
        return tree_map_only(torch.Tensor, T, inner_res)

    def __repr__(self):
        return f"T({self.inner})"

class MakeT(torch.autograd.Function):
    @staticmethod
    def forward(ctx, x):
        return T(x)

    @staticmethod
    def backward(ctx, grad_out):
        return grad_out.inner

x = torch.randn(1, requires_grad=True)
x2 = x * 2
# y = x2[:]
y = MakeT.apply(x2)
x2.mul_(3)
y.backward()
print(x.grad)
```

This prints

```
tensor([2.])
```

But if you replace `y = MakeT.apply(x2)` with `y = x2[:]`, you get 6, the correct gradient. The problem is that y is a view of x2, but autograd.Function has failed to track it.

If you try to implement this without a tensor subclass, autograd.Function will report an error saying that you can't access the grad_fn of y after mutating x2 because the grad_fn is no longer valid for custom autograd subclass. But we need to look into the inner members of generated tensor subclasses to find less obvious aliasing.

It is likely that DTensor suffers from this problem.

cc @albanD @gqchen @pearu @nikitaved @soulitzer @Lezcano @Varal7 @msaroufim @bdhirsh 

### Versions

main
Repository: rust
Issue: llvm error:  `SmallVector unable to grow. Requested capacity (4294967296) is larger than maximum value for size type (4294967295)`
Labels: A-LLVM,I-ICE,T-compiler,C-bug

<!--
[31mICE[0m: Rustc ./a.rs '-Zunstable-options --edition=2024 -ooutputfile -Zdump-mir-dir=dir' 'rustc-LLVM ERROR: SmallVector unable to grow. Requested capacity (4294967296) is larger than maximum value for size type (4294967295)', 'rustc-LLVM ERROR: SmallVector unable to grow. Requested capacity (4294967296) is larger than maximum value for size type (4294967295)'
File: /tmp/im/a.rs
-->

auto-reduced (treereduce-rust):
````rust
use std::arch::{asm, global_asm};

macro_rules! wrap {
    () => {
        macro_rules! _a {
            () => {
                "i-"
            };
        }
    };
}

wrap!();

use _a as a;

fn main() {}

global_asm!(a!());


````

original:
````rust
//@only-aarch64
//@check-pass
//@edition: 2018

// https://github.com/rust-lang/rust/issues/98291

use std::arch::{asm, global_asm};

macro_rules! wrap {
    () => {
        macro_rules! _a {
            () => {
                "i-"
            };
        }
    };
}

wrap!();

use _a as a;

fn main() {
    unsafe { asm!(a!()); }
}

global_asm!(a!());

````

Version information
````
rustc 1.80.0-nightly (44701e070 2024-06-04)
binary: rustc
commit-hash: 44701e070c8453df10df1984944258018ac21610
commit-date: 2024-06-04
host: x86_64-unknown-linux-gnu
release: 1.80.0-nightly
LLVM version: 18.1.6

````

Command:
`/home/matthias/.rustup/toolchains/master/bin/rustc -Zunstable-options --edition=2024`

<!--
Include a backtrace in the code block by setting `RUST_BACKTRACE=1` in your
environment. E.g. `RUST_BACKTRACE=1 cargo build`.
-->
<details><summary><strong>Program output</strong></summary>
<p>

```
warning: unused import: `asm`
 --> /tmp/icemaker_global_tempdir.Wtk05IMuNYhF/rustc_testrunner_tmpdir_reporting.fOHm0ahY7sgf/mvce.rs:1:17
  |
1 | use std::arch::{asm, global_asm};
  |                 ^^^
  |
  = note: `#[warn(unused_imports)]` on by default

rustc-LLVM ERROR: SmallVector unable to grow. Requested capacity (4294967296) is larger than maximum value for size type (4294967295)

```

</p>
</details>

<!--
query stack:

-->
Repository: transformers
Issue: Adaptive Decoding Support
Labels: Feature request,Generation

### Feature request

Adaptive decoding balances the diversity and coherence of open-ended text generation, making it an excellent method compared to top-k, top-p, and other decoding algorithms. For more details, the paper is available [here](https://arxiv.org/abs/2402.18223), and the code can be accessed [here](https://github.com/zwhong714/adaptive_decoding).

### Motivation

During the generation process, the distribution predicted by the language model generally falls into two categories. The first is a flattened distribution, indicating that the LM has multiple potential choices for the next token. The second is a sharp distribution, suggesting that the model's options are more limited. Ensuring that the model dynamically understands the current state is crucial for generating highly diverse and coherent sentences.

### Your contribution

idea done.
Repository: pytorch
Issue: Rule-based reconfig-and-recompile
Labels: triaged,module: cuda graphs,oncall: pt2

### 🚀 The feature, motivation and pitch

Hi, is it possible to recompile with new configs when hitting a certain type of exception in previous attempt?

Here's an example from discussion with @BoyuanFeng and @Yuzhen11 on recent cudagraph support for some input mutation functions. 
 `_inductor.config.cudagraph_support_input_mutation` can be set True at beginning.  As long as it throws a certain exception type, we turn it off and retry.  

1. We can try some aggressive settings at beginning and gradually fall back to something more conservative without starting over.  This can make those heavy internal workflows more robust.
2. Rule-based interface can be like a list of `[(exception type 1, config mutation 1), ...]`

Thank you!

### Alternatives

_No response_

### Additional context

_No response_

cc @mcarilli @ezyang @eellison @peterbell10 @bdhirsh @anijain2305 @chauhang @msaroufim
Repository: angular
Issue: computed efficieny improvement
Labels: area: core,core: reactivity,cross-cutting: signals

### Which @angular/* package(s) are relevant/related to the feature request?

core

### Description

Hi
Right now, computed re evaluates every time any of the underlying signal's properties change, regardless of whether the computed is accessing this property or not, which leads to unnecessary computations and possible re renders.

Coming from MobX, which also has computed but works as described above, makes computed very efficient and performant.
I hope you can consider this improvement, since especially in expensive computations will have a major impact in performance.

Below is an example of the scenario I described
https://stackblitz.com/edit/stackblitz-starters-pjevlf?file=src%2Fapp%2Fservice.ts

Every time the signal's name updates, the computed that calculates the total price re evaluates, although the computed only reads the price property and never accesses the name property.

Regards

### Proposed solution

computed should re evaluate only when the signal properties it accesses, change.

### Alternatives considered

None