sharjeelyunus/github-issues-dataset huggingface dataset:
Repository: godot
Issue: Editor grid renders incorrectly when far away from the world origin, even with a `precision=double` build
Labels: bug,topic:rendering,topic:editor,topic:3d

### Tested versions

- Reproducible in: 4.2.2.stable, 4.3.rc 2f2d1a7e6

### System information

Godot v4.3.beta (2f2d1a7e6) - Fedora Linux 40 (KDE Plasma) - X11 - GLES3 (Compatibility) - NVIDIA GeForce RTX 4090 (nvidia; 555.58.02) - 13th Gen Intel(R) Core(TM) i9-13900K (32 Threads)

### Issue description

The editor grid renders incorrectly when far away from the world origin, even with a `precision=double` build. This is at X = 10,000,000:

https://github.com/user-attachments/assets/b5db557d-8cde-40a4-aba6-acc710fd93b9

I suppose it needs some kind of origin shifting logic to render correctly.

I noticed this while testing https://github.com/godotengine/godot/issues/94638.

### Steps to reproduce

- Compile an editor build with `precision=double`.
- Move very far way from the world origin in the 3D editor viewport. This can be done by adding a Node3D, setting its X transform to `10000000` then pressing <kbd>F</kbd> while the node is selected and the 3D editor viewport is focused.

### Minimal reproduction project (MRP)

[test_occlusion_culling_double_precision.zip](https://github.com/user-attachments/files/16368714/test_occlusion_culling_double_precision.zip)
*Select nodes in the Scene tree dock, then press <kbd>F</kbd> in the 3D viewport to focus on nodes that are far away from the world origin.*
Repository: vscode
Issue: Large `.cpuprofile` cannot be loaded in developer tools
Labels: debug,debt

Type: <b>Bug</b>

Does this issue occur when all extensions are disabled?: Yes

- VS Code Version: 1.92.0-insider
- OS Version: Windows 11

Steps to Reproduce:

0. Unzip the user-provided `.cpuprofile` files [here](https://file.io/GdDwL3YyadCA)
1. Launch VS Code
2. `Developer: Toggle Developer Tools`
3. Switch to the "Performance" tab.
4. Load `pylance_2024.7.1_bg_1_id_0.cpuprofile`

Result:

Initially the profile seems to be getting loaded:

![image](https://github.com/user-attachments/assets/73e93368-b529-4337-90fb-27e6e7ba8413)

After a minute or two, the window goes black and "never" (I waited 20-30 minutes) recovers. However, loading other, smaller files from the same ZIP succeeds. For example, `pylance_2024.7.1_fg_id_0.cpuprofile`.

![image](https://github.com/user-attachments/assets/e9eb97b2-33d8-48d4-8aeb-751b4bc798d5)



VS Code version: Code - Insiders 1.92.0-insider (5fe066f8ebb29e7e7697f240e3aac4e6d733d993, 2024-07-24T20:30:23.504Z)
OS version: Windows_NT x64 10.0.22631
Modes:

<details>
<summary>System Info</summary>

|Item|Value|
|---|---|
|CPUs|Intel(R) Core(TM) i7-8700 CPU @ 3.20GHz (12 x 3192)|
|GPU Status|2d_canvas: enabled<br>canvas_oop_rasterization: enabled_on<br>direct_rendering_display_compositor: disabled_off_ok<br>gpu_compositing: enabled<br>multiple_raster_threads: enabled_on<br>opengl: enabled_on<br>rasterization: enabled<br>raw_draw: disabled_off_ok<br>skia_graphite: disabled_off<br>video_decode: enabled<br>video_encode: enabled<br>vulkan: disabled_off<br>webgl: enabled<br>webgl2: enabled<br>webgpu: enabled<br>webnn: disabled_off|
|Load (avg)|undefined|
|Memory (System)|63.85GB (45.18GB free)|
|Process Argv|--disable-extensions --crash-reporter-id ea9101de-1db0-4418-be8b-d4d0b3c9b928|
|Screen Reader|no|
|VM|0%|
</details>Extensions disabled<details>
<summary>A/B Experiments</summary>

```
vsliv368cf:30146710
vspor879:30202332
vspor708:30202333
vspor363:30204092
vscod805cf:30301675
vsaa593:30376534
py29gd2263:31024238
c4g48928:30535728
2i9eh265:30646982
962ge761:30841072
pythongtdpath:30726887
welcomedialog:30812478
pythonnoceb:30776497
asynctok:30898717
dsvsc013:30777762
dsvsc014:30777825
dsvsc015:30821418
pythonregdiag2:30926734
pythonmypyd1:30859725
2e7ec940:31000449
pythontbext0:30879054
accentitlementst:30870582
dsvsc016:30879898
dsvsc017:30880771
dsvsc018:30880772
cppperfnew:30980852
pythonait:30973460
da93g388:31013173
a69g1124:31018687
dvdeprecation:31040973
dwnewjupyter:31046869
nb_pkg_only:31057982
nativerepl1:31093711
refactort:31084545
pythonrstrctxt:31093868
hdi1a554:31091669
flightc:31102344

```

</details>

<!-- generated by issue reporter -->
Repository: TypeScript
Issue: No completions for type parameters in generic function return type
Labels: Suggestion,Help Wanted

I feel like we must have an issue for this one, but I can't find it.

```ts
function invertKeysAndValues<K, V>(map: Map<K, V>): Map</**/
```

Request completions at `/**/`

Expected: The type parameter `V` is provided as a valid completion entry.
Actual: `VBArray` is the first provided completion entry. This means that a commit character like `,` after typing in `V` will commit `VBArray` as a type argument.
Repository: PowerToys
Issue: crash
Labels: Issue-Bug,Product-Settings,Needs-Triage,Severity-Medium

### Microsoft PowerToys version

0.82.1

### Installation method

Microsoft Store

### Running as admin

None

### Area(s) with issue?

Settings

### Steps to reproduce

错误应用程序名称: PowerToys.Settings.exe，版本: 0.82.1.0，时间戳: 0x666b0000
错误模块名称: KERNELBASE.dll，版本: 10.0.19041.4648，时间戳: 0x5a4af933
异常代码: 0xc000027b
错误偏移量: 0x000000000012d5d2
错误进程 ID: 0x768
错误应用程序启动时间: 0x01dade38f75293ba
错误应用程序路径:~\AppData\Local\PowerToys\WinUI3Apps\PowerToys.Settings.exe
错误模块路径: C:\WINDOWS\System32\KERNELBASE.dll
报告 ID: 18c2286f-dab3-4f08-9a99-40d26c0fc249
错误程序包全名: 
错误程序包相对应用程序 ID: 

### ✔️ Expected Behavior

no crash

### ❌ Actual Behavior

_No response_

### Other Software

_No response_
Repository: flutter
Issue: `SIGSEGV: Segfault` within libflutter
Labels: c: crash,platform-android,engine,a: production,P3,needs repro info,team-engine,triaged-engine

### Steps to reproduce

I don't know how to reproduce this, I got an alarm from Sentry with this:

<img width="799" alt="image" src="https://github.com/user-attachments/assets/880f6503-9ea1-407f-8b5b-6cf85d53bacb">

This app is running Flutter 3.22.2
Repository: ollama
Issue: Error: invalid file magic when trying to import gte-Qwen2-7B-instruct gguf model to ollama instance
Labels: bug

### What is the issue?

**I got this error:**
root@bccf6f1eb00f:/data/models# ollama create gte_qwen2:7b -f Modelfile
transferring model data 
Error: invalid file magic
**This is my ModelFile:**
FROM gte_qwen2.gguf
TEMPLATE "{{ if .Prompt }}
user
{{ .Prompt }}

{{ end }}
assistant
{{ .Response }}

"
PARAMETER stop 

PARAMETER stop 


I transferred and quantized by the latest llama.cpp. 
How can I import this model to ollama?


### OS

Linux

### GPU

Nvidia

### CPU

Intel

### Ollama version

0.1.48
Repository: stable-diffusion-webui
Issue: [Bug]: sd_hypernetwork_strength no longer present as an option in quicksettings list
Labels: bug-report

### Checklist

- [X] 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
- [X] The issue has not been reported before recently
- [ ] The issue has been reported before but has not been fixed yet

### What happened?

In the past, sd_hypernetwork_strength was an option in quicksettings list. But now, it isn't.

### Steps to reproduce the problem

1. Run SD as usual
2. Observe

### What should have happened?

The flag should still be available since it's useful to adjust the strength of the hypernetwork.

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

Microsoft Edge

### Sysinfo

[sysinfo-2024-07-25-03-18.json](https://github.com/user-attachments/files/16369745/sysinfo-2024-07-25-03-18.json)


### Console logs

```Shell
venv "F:\Stable Diffusion\stable-diffusion-webui\venv\Scripts\Python.exe"
Python 3.10.6 (tags/v3.10.6:9c7b4bd, Aug  1 2022, 21:53:49) [MSC v.1932 64 bit (AMD64)]
Version: v1.9.4
Commit hash: feee37d75f1b168768014e4634dcb156ee649c05
Launching Web UI with arguments: --administrator --autolaunch --opt-split-attention --opt-sdp-no-mem-attention --xformers
[AddNet] Updating model hashes...
0it [00:00, ?it/s]
[AddNet] Updating model hashes...
0it [00:00, ?it/s]
Loading weights [3e9211917c] from F:\Stable Diffusion\stable-diffusion-webui\models\Stable-diffusion\YesMix V1.6 (Original).safetensors
Creating model from config: F:\Stable Diffusion\stable-diffusion-webui\configs\v1-inference.yaml
Running on local URL:  http://127.0.0.1:7860
```


### Additional information

_No response_
Repository: pytorch
Issue: MPS gives incorrect result when torch.nn.functional.softplus follows moveaxis
Labels: triaged,module: correctness (silent),module: mps

### 🐛 Describe the bug

```
import torch
import torch.nn.functional as F

x_cpu = torch.linspace(-1, 1, 6, device=torch.device('cpu')).view((2, 3))
x_mps = torch.linspace(-1, 1, 6, device=torch.device('mps')).view((2, 3))

print(F.softplus(x_cpu.moveaxis(0, 1)))
print(F.softplus(x_cpu).moveaxis(0, 1))
print(F.softplus(x_mps.moveaxis(0, 1))
print(F.softplus(x_mps).moveaxis(0, 1))
```

The above outputs
```
tensor([[0.3133, 0.7981],
        [0.4375, 1.0375],
        [0.5981, 1.3133]])
tensor([[0.3133, 0.7981],
        [0.4375, 1.0375],
        [0.5981, 1.3133]])
tensor([[0., 0.],
        [0., 0.],
        [0., 0.]], device='mps:0')
tensor([[0.3133, 0.7981],
        [0.4375, 1.0375],
        [0.5981, 1.3133]], device='mps:0')
```
whereas one would expect all four tensors to have the same entries. I've noticed a few things:
- A similar problem seems to occur with F.selu, F.prelu, and F.threshold in place of softplus.
- The problem appears and disappears seemingly non-deterministically. For example, swapping the last two lines of the above gives a program that has the correct output about half the time, but gives an output with mixed up entries the other half of the time.
- As the above point suggests, the problem seems to be sensitive to tensor entries being previously accessed. For example, while ```print(F.softplus(x_mps).moveaxis(0, 1)); print(F.softplus(x_mps.moveaxis(0, 1)))``` results in wrong output about half the time, simply doubling the unproblematic line and writing ```print(F.softplus(x_mps).moveaxis(0, 1)); print(F.softplus(x_mps).moveaxis(0, 1)); print(F.softplus(x_mps.moveaxis(0, 1)))``` seems to always have correct output.

### Versions

```
Collecting environment information...
PyTorch version: 2.3.0.post100
Is debug build: False
CUDA used to build PyTorch: None
ROCM used to build PyTorch: N/A

OS: macOS 14.5 (arm64)
GCC version: Could not collect
Clang version:15.0.0 (clang-1500.3.9.4)
CMake version: Could not collect
Libc version: N/A

Python version: 3.11.9 (main, Apr 19 2024, 11:43:47) [Clang 14.0.6 ] (64-bit runtime)
Python platform: macOS-14.5-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 M2 Pro

Versions of relevant libraries:
[pip3] numpy==1.26.4
[pip3] torch==2.3.0.post100
[conda] numpy                     1.26.4          py311he598dae_0
[conda] numpy-base                1.26.4          py311hfbfe69c_0
[conda] pytorch                   2.3.0           gpu_mps_py311hc07fac7_100
```

cc @kulinseth @albanD @malfet @DenisVieriu97 @jhavukainen
Repository: pytorch
Issue: Intra-Node one-shot/two-shot low latency kernels for fp32
Labels: oncall: distributed

### 🚀 The feature, motivation and pitch

currently low latency kernels only work for all reduce sum and bf16. i am doing small msg size all reduce in fp32 and would like support for the low latency kernels to work with this dtype.

https://github.com/pytorch/pytorch/blob/f09c983399da63ad505620b0ae4303e8752ce6b0/test/distributed/test_c10d_nccl.py#L3140

### Alternatives

have higher latency

### Additional context

_No response_

cc @XilunWu @H-Huang @awgu @kwen2501 @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @c-p-i-o
Repository: go
Issue: proposal: runtime: add `GetEntryInfo` function
Labels: Proposal

### Proposal Details

Some time we want to get the entry info like module name. entry file path,  dpendent modules and so on.
before go1.23 these infos can be get from runtime.firstmoduledata, but after go1.23 runtime.firstmoduledata can not be access.

before go1.23
```go
// get path of the entry file, may be a /xx/xx_test.go or /xx/main.go
func getEntryFilePath() string {
	mainFile := getMainFile()
	if !isTestMode(mainFile) {
		return mainFile
	}
	firstModule := unsafe.Pointer(&firstmoduledata)
	fileTab := *(*[]byte)(reflection.Add(firstModule, filetabField.Offset))
	lastFiles := getLastFiles(fileTab)
	for _, file := range lastFiles {
		if isTestFile(file) {
			return file
		}
	}
	panic("can not found entry file path")
}
```
Repository: ant-design
Issue: 希望可以开放 <DatePicker._InternalPanelDoNotUseOrYouWillBeFired>
Labels: Inactive,unconfirmed

### What problem does this feature solve?

想日期选择直接显示页面上面,不需要一个 Picker 包装

### What does the proposed API look like?

和 DatePicker 一样就行, 不需要 open 相关的属性, 不需要有个 Input 在上面

<!-- generated by ant-design-issue-helper. DO NOT REMOVE -->
Repository: terminal
Issue: Configure block select to use ctrl, not alt
Labels: Issue-Feature,Area-Settings,Product-Terminal

<!-- 
🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨

I ACKNOWLEDGE THE FOLLOWING BEFORE PROCEEDING:
1. If I delete this entire template and go my own path, the core team may close my issue without further explanation or engagement.
2. If I list multiple bugs/concerns in this one issue, the core team may close my issue without further explanation or engagement.
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All good? Then proceed!
-->

# Description of the new feature/enhancement

Currently block select is possible with alt+mouse. Since I use AltDrag to do window management, alt is not a valid key binding for me. On Linux this is `ctrl+<mouse>` by default. I'd like it to be an option to flip the keybinding.

<!-- 
A clear and concise description of what the problem is that the new feature would solve.
Describe why and how a user would use this new functionality (if applicable).
-->

# Proposed technical implementation details (optional)

I dunno as keybindings don't seen like the right fit for this since mouse buttons is not valid in the keybinding syntax.

<!-- 
A clear and concise description of what you want to happen.
-->
Repository: rust
Issue: `allow_internal_unstable` can be used to bypass `incomplete_features` warning
Labels: A-lints,A-diagnostics,T-compiler,C-bug,F-allow_internal_unstable

The following example uses the incomplete `dyn_star` feature, which should trigger a warning, but the warning does not show:
```rust
#![feature(allow_internal_unstable)]
#![feature(decl_macro, staged_api, example)]
#![allow(internal_features)]
#![unstable(feature = "example", issue = "none")]

#[allow_internal_unstable(dyn_star)]
macro generate {
    ($name:ident) => {
        fn $name() {
            use std::fmt::Debug;
        
            let _x: dyn* Debug;
        }
    }
}

generate!(example);

fn main() {
    example();
}
```
This is a problem since we want to use the lint to enforce that e.g. std does not depend on incomplete features, and this issue could lead to us accidentally depending on incomplete features anyway!

We probably have to make the incomplete_features lint scan not just the module-level `#![feature]` declarations, but also the `allow_internal_unstable` (and `rustc_allow_const_fn_unstable`).

Or, alternatively, maybe `allow_internal_unstable` should only allow features that are enabled in the crate where the macro is declared? It seems a bit odd to say "ah yes this macro can internally use feature X anywhere it is expanded" when feature X is not even available in the current crate.
Repository: angular
Issue: Model inputs not working as expected
Labels: state: Needs Design,area: core,core: inputs / outputs,P3,bug,core: reactivity,cross-cutting: signals

### Which @angular/* package(s) are the source of the bug?

core

### Is this a regression?

No

### Description

Hi, the new model inputs are not working as expected for me.
When i change the model input from the parent component the change is not reflected in the child component.
In this example the parent component sets the `save` model input immediately to `false` again.
In the stackblitz you can the the `save` signals are getting out of sync

### Please provide a link to a minimal reproduction of the bug

https://stackblitz.com/edit/stackblitz-starters-pgh9xy?file=src%2Fmain.ts

### Please provide the exception or error you saw

_No response_

### Please provide the environment you discovered this bug in (run `ng version`)

```true
@angular/core: 18.1.1
```


### Anything else?

I want to implement a generic save component. This component sets the model input `save` to true and shows some loading indication as long as `save` is true.

This component is used from different parent component which intern either do http requests or just execute some code.
When they are finished they set the `save` model to `false` again. Then the loading animation should stop in the child component.
Repository: transformers
Issue: auto_find_batch_size for OOM during evaluation
Labels: Feature request,bug

### System Info

When running training and evaluation (`_inner_training_loop` in the HF `Trainer`), the auto-find-batch size tries to reduce the training batch size, even when the OOM happens during evaluation and not the training. It should distinguish whether the error comes from training or evaluation (`_maybe_log_save_evaluate`) and reduce the evaluation batch size if needed.
Also, it would be nice to report the finally chosen batch size (maybe this is already done).

### Who can help?

_No response_

### Information

- [ ] The official example scripts
- [ ] My own modified scripts

### Tasks

- [ ] An officially supported task in the `examples` folder (such as GLUE/SQuAD, ...)
- [ ] My own task or dataset (give details below)

### Reproduction

Choose a very large evaluation batch size, and a small training batch size.

### Expected behavior

Should reduce eval batch size, not just the training batch size
Repository: next.js
Issue: Vercel does not display not-found page on Next.js project
Labels: bug,Middleware,Navigation,Internationalization (i18n)

### Link to the code that reproduces this issue

https://github.com/Cuboctaedro/nextjs-notfound

### To Reproduce

1. Run the app locally.
2. Use the menu link for Page X. It should display a 404 page.
3. Deploy the app to Vercel.
4. Use the menu link for Page X. It does not display the 404 page.
5. Deploy the app to Netlify.
6. Use the menu link for Page X. It works as expected.

### Current vs. Expected behavior

When deploying to Vercel I expect to see a 404 page when using a link for a page that has not been built but I do not.

### Provide environment information

```bash
Operating System:
  Platform: win32
  Arch: x64
  Version: Windows 11 Home
  Available memory (MB): 16162
  Available CPU cores: 8
Binaries:
  Node: 20.10.0
  npm: N/A
  Yarn: N/A
  pnpm: N/A
Relevant Packages:
  next: 14.2.3
  eslint-config-next: 14.2.3
  react: 18.3.1
  react-dom: 18.3.1
  typescript: 5.4.5
Next.js Config:
  output: N/A
```


### Which area(s) are affected? (Select all that apply)

Internationalization (i18n), Middleware, Navigation

### Which stage(s) are affected? (Select all that apply)

Vercel (Deployed)

### Additional context

I have already reported this to Vercel:
https://github.com/orgs/vercel/discussions/7171#discussioncomment-10071762
I was adviced to report it here since they did reproduce it and it seems to be a bug.
Repository: pytorch
Issue: Coredump for pytorch ddp when job finished 
Labels: oncall: distributed,module: cuda

### 🐛 Describe the bug

This is not an inevitable error. It only appears with low probability when the job is finished.

image： nvcr.io/nvidia/pytorch:23.09-py3

Task ：image_detection
models ：faster_rcnn_R_50
Params ：forward_only=false，train_batchsizes=1，val_batchsizes=1，num_batches=10，data_name=imagenet，data_dir=real_data_dir

Error
![image](https://github.com/user-attachments/assets/02df8cf0-b088-45e0-8492-1661261e953a)

I have found that the error comes from the order for destructor between the Initializer and the WorkNccl. If the Initializer destructs first, the WorkNccl destructor will abort when it tries to destroy the cuda event in WorkNccl. In pytorch, there are no rules or codes to prevent the invalid order of destructor. If we want to reproduce the problem easily, we can add sleep code in CUDAEvent destroy. Then the probability of this coredump will raise.

Other Information
A. Initializer
![image](https://github.com/user-attachments/assets/eadce0eb-6515-447e-9fc9-0b5d32d9f084)

B. Coredump codes
![image](https://github.com/user-attachments/assets/1b9a7ce6-fbcd-4f6c-8b0f-d6da4d76525b)

C.  Error status. Initializer destructs first. Then comes the WorkNccl
![image](https://github.com/user-attachments/assets/a838160c-301f-4dc6-bf2f-9abdedf20db7)
![image](https://github.com/user-attachments/assets/e4787ff5-81fb-40d6-a581-9a7107b3d3a1)

D. Codes to increase the coredump probability
<img width="1098" alt="image" src="https://github.com/user-attachments/assets/2f07360e-036c-4653-9aa1-46f780f84944">
sleep 1000 us at the arrow in the image. Then coredump times will increase.

Another discussion is added for pytorch
https://discuss.pytorch.org/t/coredump-for-pytorch-ddp-when-job-finished/206835



### Versions


![image](https://github.com/user-attachments/assets/a0fa06e0-148a-445c-b352-834436fdfa3b)
![image](https://github.com/user-attachments/assets/eadadae8-4e37-4e93-b9ea-95e2c995c851)
![image](https://github.com/user-attachments/assets/38a52c8d-9caa-4da8-bb42-4fcc8f530511)
![image](https://github.com/user-attachments/assets/19e0f351-c74c-43f7-b8bf-79835ccb2ee1)




![image](https://github.com/user-attachments/assets/b349dbc7-8599-4d10-9c9b-6042dc6c44e0)


cc @XilunWu @H-Huang @awgu @kwen2501 @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @c-p-i-o @ptrblck @msaroufim
Repository: vscode
Issue: issue reporter dropdown is too large
Labels: bug,issue-reporter

> Type: Bug
> 
> 1. Open Help > Report Issue
> 
> The dropdowns are too large....

also make sure `"issueReporter.experimental.auxWindow": true`

the issue with the dropdown seems related to the aux window service. looks like in all zoom levels, it is at `current zoom level + 1`

might consider switching to the custom dropdowns (like we have in settings). 

_Originally posted by @kieferrm in https://github.com/microsoft/vscode/issues/223506_