sharjeelyunus/github-issues-dataset huggingface dataset:
Repository: godot
Issue: Vulkan: Faces on objects with several surfaces disappear under some angles
Labels: bug,topic:rendering,topic:import,topic:3d

### Godot version

4.0 Beta 10

### System information

Linux Mint 21, Vulkan, Intel Iris Xe (Intel i5-1135G7)

### Issue description

Faces disappear under certain angles on some imported glTF meshes, both in editor, and in built projects. Issue seems to be worse on lower target resolutions, and on larger meshes.
It's visible on large meshes with many surfaces, once you delete some of them, issue disappears.
Issue doesn't exist when the same meshes are viewed through other glTF viewer apps.

![1](https://user-images.githubusercontent.com/65317076/210123335-ba40bc2f-7c07-4277-b906-6c3759438f14.png)
![2](https://user-images.githubusercontent.com/65317076/210123336-dad94886-a91a-4173-91f6-377d12d1df90.png)


### Steps to reproduce

1. Create a large mesh with several surfaces in Blender
2. Import it
3. View in editor or build project

### Minimal reproduction project

[test_surfaces.zip](https://github.com/godotengine/godot/files/10326774/test_surfaces.zip)
Repository: PowerToys
Issue: Microphone Communication with Teammates in DotA 2 Causes Windows 11 Taskbar to Override Always on Top
Labels: Issue-Bug,Product-Always On Top,Priority-2

### Microsoft PowerToys version

0.65.0

### Installation method

PowerToys auto-update

### Running as admin

Yes

### Area(s) with issue?

Always on Top

### Steps to reproduce

1. Make the huge mistake of installing Windows 11, which has no vertical taskbar.

2. Launch Dota 2 (available for free on Steam). Set the game to run in Display Mode: Borderless Window (I am using 2560x1440 on an ultrawide monitor).

3. Pin the Dota 2 window to be always on top using the key shortcut so the taskbar doesn't interrupt anything.

4. Enter a solo game with other players. (Strangely, it doesn't seem to happen when playing in a party).

5. Use the Push-To-Talk button to communicate with your teammates.

[PowerToysReport_2022-12-30-23-35-12.zip](https://github.com/microsoft/PowerToys/files/10326811/PowerToysReport_2022-12-30-23-35-12.zip)

### ✔️ Expected Behavior

The Taskbar should continue to be hidden by always on top, even after communicating with teammates.

### ❌ Actual Behavior

For some incredibly cryptic reason, Always-On-Top stops working, and the taskbar begins to display over the Dota 2 window when the mouse is moved to the bottom of the screen.

After disabling and then re-enabling Always-On-Top, functionality works as expected until communicating again.

### Other Software

DotA 2, whatever is currently on Steam. This bug has been present for at least six months, since I upgraded to Windows 11.
Repository: node
Issue: Unexpected output of `Intl.NumberFormat#formatRange` with `percent` style for same values
Labels: i18n-api

### Version

v19.3.0

### Platform

Microsoft Windows NT 10.0.22621.0 x64

### Subsystem

_No response_

### What steps will reproduce the bug?

```js
const percentFormatter = new Intl.NumberFormat("en-US", { style: "percent" });

console.log(percentFormatter.formatRange(0.5, 0.55));
console.log(percentFormatter.formatRange(0.5, 0.5));
```

### How often does it reproduce? Is there a required condition?

all the time for all locales

### What is the expected behavior?

```
50% – 55%
~50%
```
Similar to:
```js
const numberFormatter = new Intl.NumberFormat("en-US");

console.log(numberFormatter.formatRange(50_000, 55_000)); // 50,000–55,000
console.log(numberFormatter.formatRange(50_000, 50_000)); // ~50,000
```

### What do you see instead?

```
50% – 55%
~5,000%
```

### Additional information

`maximumFractionDigits` behavior:
```js
> percentFormatter = new Intl.NumberFormat("en-US", { style: 'percent' });
NumberFormat [Intl.NumberFormat] {}
> percentFormatter.formatRange(0.1234, 0.1234)
~1,200%

> percentFormatter = new Intl.NumberFormat("en-US", { style: 'percent', maximumFractionDigits:10 });
NumberFormat [Intl.NumberFormat] {}
> percentFormatter.formatRange(0.1234, 0.1234)
~1,234%
```
Repository: go
Issue: x/build/devapp/owners: document responsibilities of primary and secondary code owners
Labels: Documentation,Builders,NeedsInvestigation

Go Code Owners page https://dev.golang.org/owners lists primary and secondary code owners by project. The page should explain what this information means -- what are the responsibilities of code owners? https://go.dev/doc/contribute doesn't mention code owners at all.

It should also explain the difference between primary and secondary owners. It looks like Gerrit https://go-review.googlesource.com/ automatically adds primaries as reviewers. Are there any other differences?
Repository: neovim
Issue: The `serverlist()` function only returns the current instance's server name
Labels: bug,server,remote

### Neovim version (nvim -v)

v0.8.2

### Vim (not Nvim) behaves the same?

no, serverlist is a different thing in Vim

### Operating system/version

Arch Linux

### Terminal name/version

rxvt-unicode (urxvt) v9.30 - released: 2021-11-27

### $TERM environment variable

xterm-color

### Installation

Arch linux community package

### How to reproduce the issue

In separate terminals:

nvim --clean --listen /tmp/neovim
nvim --clean --listen /tmp/neovim2

### Expected behavior

I would expect that `:echo serverlist()` in either of these nvim instances would print `['/tmp/neovim', 'tmp/neovim2']`

### Actual behavior

Running `:echo serverlist()` in these two instances only returns their own server names -- `['/tmp/neovim']` and `['/tmp/neovim2']`. This also happens with TCP, e.g. `127.0.0.1:5001`.
Repository: pytorch
Issue: Adding label smoothing option to `nn.BCELoss`  and `nn.BCEWithLogitsLoss`?
Labels: module: nn,module: loss,triaged,actionable

### 🚀 The feature, motivation and pitch

Hello, I was looking at BCELoss and CrossEntropyLoss and found that while the latter has the option to add label_smoothing, the former does not. 

### Alternatives

Seeing as how the reasoning used for performing label smoothing (i.e. the logit values having to go to $\pm\infty$ to approach 1 or 0) should also apply to sigmoid functions (which are used with BCELoss), it stands to reason that label smoothing can and should be implemented with BCELoss? (i.e. for ex :  if the label value is 1, with label smoothing of 0.2, the value should be 0.8?)

### Additional context

_No response_

cc @albanD @mruberry @jbschlosser @walterddr @kshitij12345 @saketh-are
Repository: opencv
Issue: Outdated caption and screenshot on wiki
Labels: category: documentation

### Descripe the doc issue

Outdated caption and screenshot on wiki `Windows_7_and_TortoiseGit_contribution_guide` article.
![Itseez_OpenCV](https://user-images.githubusercontent.com/59748404/210131074-b985da07-a8e0-48ea-b318-672947fa16ed.PNG)


### Fix suggestion

1. Change text to `Open the [OpenCV page](https://github.com/opencv/opencv).`
2. And screenshot to
![Снимок](https://user-images.githubusercontent.com/59748404/210131224-7c4f523d-c1ae-42eb-a03c-ca8663a1a891.PNG)
Repository: yt-dlp
Issue: Allow downloading all Twitter Spaces hosted by username/Twitter handle
Labels: site-enhancement,triage

### DO NOT REMOVE OR SKIP THE ISSUE TEMPLATE

- [X] I understand that I will be **blocked** if I remove or skip any mandatory\* field

### Checklist

- [X] I'm requesting a site-specific feature
- [X] I've verified that I'm running yt-dlp version **2022.11.11** ([update instructions](https://github.com/yt-dlp/yt-dlp#update)) or later (specify commit)
- [X] I've checked that all provided URLs are playable in a browser with the same IP and same login details
- [X] I've searched 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)
- [X] I've read about [sharing account credentials](https://github.com/yt-dlp/yt-dlp/blob/master/CONTRIBUTING.md#are-you-willing-to-share-account-details-if-needed) and I'm willing to share it if required

### Region

_No response_

### Example URLs

https://twitter.com/robinw (should include https://twitter.com/i/spaces/1RDGlabMNOgJL for example)

### Provide a description that is worded well enough to be understood

`yt-dlp https://twitter.com/<handle>` should download all Twitter Spaces

### Provide verbose output that clearly demonstrates the problem

- [X] Run **your** yt-dlp command with **-vU** flag added (`yt-dlp -vU <your command line>`)
- [X] Copy the WHOLE output (starting with `[debug] Command-line config`) and insert it below

### Complete Verbose Output

```console
$ yt-dlp https://twitter.com/robinw
[generic] robinw: Downloading webpage
WARNING: [generic] Falling back on generic information extractor
[generic] robinw: Extracting information
ERROR: Unsupported URL: https://twitter.com/robinw
```
Repository: godot
Issue: AnimationTree is not showing new node names in Mandarin language
Labels: bug,topic:editor,topic:animation

### Godot version

v4.0.beta10.official [d0398f62f]

### System information

Windows10, RX580, R5 2400G

### Issue description

AnimationTree is not showing another node when the mandarin language

![problem](https://user-images.githubusercontent.com/54935689/210136292-e8d601b2-7506-4a24-8ccf-ae1d2d48262b.gif)


### Steps to reproduce

see the gif

### Minimal reproduction project

N/A
Repository: material-ui
Issue: [SwipeableDrawer] Swipe to close only works on touch devices
Labels: new feature,waiting for 👍,component: SwipeableDrawer

### Duplicates

- [X] I have searched the existing issues

### Latest version

- [X] I have tested the latest version

### Steps to reproduce 🕹

Link to live example: https://codesandbox.io/s/flamboyant-fast-3ynzp2?file=/src/App.tsx

Steps:

1. Open the link above in a browser (not on mobile!)
2. Click on the "open" button
3. Try to drag down the drawer to dismiss it


### Current behavior 😯

A drawer will appear which cannot be dismissed by dragging it down, this is **only** possible for devices which have touch targets (so basically mobile).

### Expected behavior 🤔

When using the SwipeableDrawer, I would expect the drawer to be swipeable whether I am on a touch target device or when I'm using it on a desktop.

### Context 🔦

I use the SwipeableDrawer to create a Material Bottom Sheet, where I would like to dismiss the sheet by dragging it down, whether I'm using a phone or a desktop. I noticed that users are trying to drag down the sheet (which is expected because we are providing a "handle") but they are unable to do so because they are using it on a desktop.

### Your environment 🌎

<details>
  <summary><code>npx @mui/envinfo</code></summary>

```
  System:
    OS: Windows 10 10.0.22621
  Binaries:
    Node: 17.5.0 - C:\Program Files\nodejs\node.EXE
    Yarn: 1.22.18 - C:\Program Files\nodejs\yarn.CMD
    npm: 8.19.2 - C:\Program Files\nodejs\npm.CMD
  Browsers:
    Chrome: Not Found
    Edge: Spartan (44.22621.963.0), Chromium (108.0.1462.54)
```
</details>
Repository: pytorch
Issue: Overflow when running torch.nn.AdaptiveMaxPool2d
Labels: triaged,module: pooling,module: edge cases

### 🐛 Describe the bug

Overflow when running  torch.nn.AdaptiveMaxPool2d with very large list elements:

```
import torch
import numpy as np
arg_1_0 = 125091515651
arg_1_1 = 125091515651
arg_1 = [arg_1_0,arg_1_1,]
arg_class = torch.nn.AdaptiveMaxPool2d(arg_1,)
arg_2_0_tensor = torch.rand([1, 3, 5, 6], dtype=torch.float64)
arg_2_0 = arg_2_0_tensor.clone()
arg_2 = [arg_2_0,]
try:
  res = arg_class(*arg_2)
except Exception as e:
  print("Error:"+str(e))
```

The log message is:

```
Error:Storage size calculation overflowed with sizes=[1, 3, 125091515651, 125091515651]
```

### Versions

Collecting environment information...
PyTorch version: 1.12.0+cu102
Is debug build: False
CUDA used to build PyTorch: 10.2
ROCM used to build PyTorch: N/A

OS: Ubuntu 18.04.6 LTS (x86_64)
GCC version: (Ubuntu 7.5.0-3ubuntu1~18.04) 7.5.0
Clang version: 6.0.0-1ubuntu2 (tags/RELEASE_600/final)
CMake version: version 3.22.6
Libc version: glibc-2.27

Python version: 3.8.16 (default, Dec  7 2022, 01:12:13)  [GCC 7.5.0] (64-bit runtime)
Python platform: Linux-5.10.133+-x86_64-with-glibc2.27
Is CUDA available: False
CUDA runtime version: 11.2.152
CUDA_MODULE_LOADING set to: N/A
GPU models and configuration: Could not collect
Nvidia driver version: Could not collect
cuDNN version: Probably one of the following:
/usr/lib/x86_64-linux-gnu/libcudnn.so.8.1.1
/usr/lib/x86_64-linux-gnu/libcudnn_adv_infer.so.8.1.1
/usr/lib/x86_64-linux-gnu/libcudnn_adv_train.so.8.1.1
/usr/lib/x86_64-linux-gnu/libcudnn_cnn_infer.so.8.1.1
/usr/lib/x86_64-linux-gnu/libcudnn_cnn_train.so.8.1.1
/usr/lib/x86_64-linux-gnu/libcudnn_ops_infer.so.8.1.1
/usr/lib/x86_64-linux-gnu/libcudnn_ops_train.so.8.1.1
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True

Versions of relevant libraries:
[pip3] numpy==1.21.6
[pip3] torch==1.12.0
[pip3] torchaudio==0.13.0+cu116
[pip3] torchsummary==1.5.1
[pip3] torchtext==0.14.0
[pip3] torchvision==0.14.0+cu116
[conda] Could not collect
Repository: pytorch
Issue: Segmentation fault when running torch.nn.AdaptiveMaxPool2d
Labels: triaged,module: edge cases

### 🐛 Describe the bug

If torch.nn.AdaptiveMaxPool2d is given very large list elements, it results in segmentation fault:

```
import torch
import numpy as np
arg_1_0 = 125091515651
arg_1_1 = 125091515651
arg_1 = [arg_1_0,arg_1_1,]
arg_class = torch.nn.AdaptiveMaxPool2d(arg_1,)
arg_2_0_tensor = torch.rand([1, 3, 5, 6], dtype=torch.float64)
arg_2_0 = arg_2_0_tensor.clone()
arg_2 = [arg_2_0,]
try:
  res = arg_class(*arg_2)
except Exception as e:
  print("Error:"+str(e))
```

The log message is:

```
Segmentation fault (core dumped)
```

Here is the link to [gist](https://colab.research.google.com/gist/nimashiri/973e5abe10001083c7ebce01171a11da/tensorflow-python-ops-gen_list_ops-tensor_list_from_tensor.ipynb)

### Versions

Collecting environment information...
PyTorch version: 1.8.0
Is debug build: False
CUDA used to build PyTorch: 10.2
ROCM used to build PyTorch: N/A

OS: Ubuntu 20.04.3 LTS (x86_64)
GCC version: (Ubuntu 9.4.0-1ubuntu1~20.04.1) 9.4.0
Clang version: Could not collect
CMake version: version 3.24.3
Libc version: glibc-2.31

Python version: 3.8.10 (default, Nov 14 2022, 12:59:47)  [GCC 9.4.0] (64-bit runtime)
Python platform: Linux-5.15.0-56-generic-x86_64-with-glibc2.29
Is CUDA available: True
CUDA runtime version: 11.0.194
CUDA_MODULE_LOADING set to: 
GPU models and configuration: GPU 0: NVIDIA GeForce GTX 1660 Ti
Nvidia driver version: 510.108.03
cuDNN version: Probably one of the following:
/usr/local/cuda-11.0/targets/x86_64-linux/lib/libcudnn.so.8.1.1
/usr/local/cuda-11.0/targets/x86_64-linux/lib/libcudnn_adv_infer.so.8.1.1
/usr/local/cuda-11.0/targets/x86_64-linux/lib/libcudnn_adv_train.so.8.1.1
/usr/local/cuda-11.0/targets/x86_64-linux/lib/libcudnn_cnn_infer.so.8.1.1
/usr/local/cuda-11.0/targets/x86_64-linux/lib/libcudnn_cnn_train.so.8.1.1
/usr/local/cuda-11.0/targets/x86_64-linux/lib/libcudnn_ops_infer.so.8.1.1
/usr/local/cuda-11.0/targets/x86_64-linux/lib/libcudnn_ops_train.so.8.1.1
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True

Versions of relevant libraries:
[pip3] mypy-extensions==0.4.3
[pip3] numpy==1.19.5
[pip3] pytorch-lightning==1.5.6
[pip3] pytorch-ranger==0.1.1
[pip3] torch==1.8.0
[pip3] torch-geometric==2.0.4
[pip3] torch-tb-profiler==0.4.0
[conda] Could not collect
Repository: pytorch
Issue: Overflow when running torch.nn.AdaptiveMaxPool3d on torch 1.12.0 and 1.13.1
Labels: triaged,module: edge cases

### 🐛 Describe the bug

When running torch.nn.AdaptiveMaxPool3d, it overflows with very large elements in input lists. 

```
import torch
import numpy as np
arg_1_0 = 125091515651
arg_1_1 = 125091515651
arg_1_2 = 125091515651
arg_1 = [arg_1_0,arg_1_1,arg_1_2,]
arg_class = torch.nn.AdaptiveMaxPool3d(arg_1,)
arg_2_0_tensor = torch.rand([2, 3, 5, 6, 7], dtype=torch.float64)
arg_2_0 = arg_2_0_tensor.clone()
arg_2 = [arg_2_0,]
try:
  res = arg_class(*arg_2)
except Exception as e:
  print("Error:"+str(e))
```

Log message:

```
Error:Storage size calculation overflowed with sizes=[2, 3, 125091515651, 125091515651, 125091515651]
```

### Versions

Collecting environment information...
PyTorch version: 1.13.0+cu116
Is debug build: False
CUDA used to build PyTorch: 11.6
ROCM used to build PyTorch: N/A

OS: Ubuntu 18.04.6 LTS (x86_64)
GCC version: (Ubuntu 7.5.0-3ubuntu1~18.04) 7.5.0
Clang version: 6.0.0-1ubuntu2 (tags/RELEASE_600/final)
CMake version: version 3.22.6
Libc version: glibc-2.27

Python version: 3.8.16 (default, Dec  7 2022, 01:12:13)  [GCC 7.5.0] (64-bit runtime)
Python platform: Linux-5.10.133+-x86_64-with-glibc2.27
Is CUDA available: False
CUDA runtime version: 11.2.152
CUDA_MODULE_LOADING set to: N/A
GPU models and configuration: Could not collect
Nvidia driver version: Could not collect
cuDNN version: Probably one of the following:
/usr/lib/x86_64-linux-gnu/libcudnn.so.8.1.1
/usr/lib/x86_64-linux-gnu/libcudnn_adv_infer.so.8.1.1
/usr/lib/x86_64-linux-gnu/libcudnn_adv_train.so.8.1.1
/usr/lib/x86_64-linux-gnu/libcudnn_cnn_infer.so.8.1.1
/usr/lib/x86_64-linux-gnu/libcudnn_cnn_train.so.8.1.1
/usr/lib/x86_64-linux-gnu/libcudnn_ops_infer.so.8.1.1
/usr/lib/x86_64-linux-gnu/libcudnn_ops_train.so.8.1.1
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True

Versions of relevant libraries:
[pip3] numpy==1.21.6
[pip3] torch==1.12.0
[pip3] torchaudio==0.13.0+cu116
[pip3] torchsummary==1.5.1
[pip3] torchtext==0.14.0
[pip3] torchvision==0.14.0+cu116
[conda] Could not collect
Repository: pytorch
Issue: Segmentation fault when running torch.nn.AdaptiveMaxPool3d
Labels: triaged,module: edge cases

### 🐛 Describe the bug

If torch.nn.AdaptiveMaxPool3d is given very large list elements, it results in segmentation fault.

```
import torch
import numpy as np
arg_1_0 = 125091515651
arg_1_1 = 125091515651
arg_1_2 = 125091515651
arg_1 = [arg_1_0,arg_1_1,arg_1_2,]
arg_class = torch.nn.AdaptiveMaxPool3d(arg_1,)
arg_2_0_tensor = torch.rand([2, 3, 5, 6, 7], dtype=torch.float64)
arg_2_0 = arg_2_0_tensor.clone()
arg_2 = [arg_2_0,]
try:
  res = arg_class(*arg_2)
except Exception as e:
  print("Error:"+str(e))
```

The log message is:

```
Segmentation fault (core dumped)
```

### Versions

Collecting environment information...
PyTorch version: 1.8.0
Is debug build: False
CUDA used to build PyTorch: 10.2
ROCM used to build PyTorch: N/A

OS: Ubuntu 18.04.6 LTS (x86_64)
GCC version: (Ubuntu 7.5.0-3ubuntu1~18.04) 7.5.0
Clang version: 6.0.0-1ubuntu2 (tags/RELEASE_600/final)
CMake version: version 3.22.6
Libc version: glibc-2.27

Python version: 3.8.16 (default, Dec  7 2022, 01:12:13)  [GCC 7.5.0] (64-bit runtime)
Python platform: Linux-5.10.133+-x86_64-with-glibc2.27
Is CUDA available: False
CUDA runtime version: 11.2.152
CUDA_MODULE_LOADING set to: N/A
GPU models and configuration: Could not collect
Nvidia driver version: Could not collect
cuDNN version: Probably one of the following:
/usr/lib/x86_64-linux-gnu/libcudnn.so.8.1.1
/usr/lib/x86_64-linux-gnu/libcudnn_adv_infer.so.8.1.1
/usr/lib/x86_64-linux-gnu/libcudnn_adv_train.so.8.1.1
/usr/lib/x86_64-linux-gnu/libcudnn_cnn_infer.so.8.1.1
/usr/lib/x86_64-linux-gnu/libcudnn_cnn_train.so.8.1.1
/usr/lib/x86_64-linux-gnu/libcudnn_ops_infer.so.8.1.1
/usr/lib/x86_64-linux-gnu/libcudnn_ops_train.so.8.1.1
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True

Versions of relevant libraries:
[pip3] numpy==1.21.6
[pip3] torch==1.8.0
[pip3] torchaudio==0.13.0+cu116
[pip3] torchsummary==1.5.1
[pip3] torchtext==0.14.0
[pip3] torchvision==0.14.0+cu116
[conda] Could not collect
Repository: pytorch
Issue: `torch::jit::optimize_for_inference` doesn't preserve exported methods when calling `freeze`
Labels: oncall: jit

I came across this issue while trying to optimize a JIT scripted model from python in my C++ app. I'm developing against `libtorch==1.13.1` and using `torch==1.13.1` in python in the CUDA+cuDNN dev container. The model was converted with `torch.jit.script` and had an additional `torch.jit.export` exported method named "inference".

When trying to run `torch::jit::optimize_for_inference(model, {"inference"})` in my C++ app, I get an error saying:
```
terminate called after throwing an instance of 'c10::Error'
  what():  Method 'inference' is not defined.
```
This stems from the fact that during model optimization, the model is frozen but the vector `other_methods` is not passed into the `preserved_attrs` parameter of `freeze`. I don't have a full `libtorch` development environment set up but have written my own version of `optimize_for_inference` with the proposed change of `frozen_mod = freeze(module, other_methods, true);` and it appears to work well. If I have time/can get a dev environment set up before you all get to it, I'm happy to make a PR.

https://github.com/pytorch/pytorch/blob/77c2a8a11f7b5164c255b5b49dbc66a3f6533e9d/torch/csrc/jit/api/module.cpp#L502

cc @EikanWang @jgong5 @wenzhe-nrv @sanchitintel
Repository: neovim
Issue: UI:  exotic text decorations
Labels: enhancement,gui,ui,ui-extensibility,marks

### Feature already in Vim?

_No_

### Feature description

I use a piece of software called [Cursorless](https://github.com/cursorless-dev/cursorless) which enables efficient structural editing by defining a meta language for targeting elements which depends on always on text decorations. The decorations could be anything, but in practice they tend to be SVGs of different colors that are placed on top of characters to allow the user to reference a particular element with minimal work. Cursorless is most widely used by the voice coding community. See [this gif](https://github.com/cursorless-dev/cursorless/blob/1a0616521bbc6d264f22fdad41e9a7773f9b0bee/images/bringArgueAirAndEachAfterDrum.gif) for an example of what the text decorations look like.

It would be great if neovim GUIs could support this type of text decoration, but I imagine it will require some server side changes.

Cross linking some related issues for posterity:
- https://github.com/neovim/neovim/issues/1767
- https://github.com/neovide/neovide/issues/1144
- https://github.com/neovide/neovide/issues/669
- https://github.com/neovide/neovide/issues/850