sharjeelyunus/github-issues-dataset huggingface dataset:
Repository: vscode
Issue: `editor.action.clipboardPasteAction` doesn't work with `runCommands`
Labels: bug,runCommands

Type: <b>Bug</b>

1. Define following keybinding in keybindings.json.
```json
    {
        "key": "ctrl+p",
        "command": "runCommands",
        "args": {
            "commands": [
                { "command": "editor.action.clipboardPasteAction" },
                { "command": "type", "args": { "text": "," }}
            ]
        }
    },
```
2. Copy some string like 'hello' to the clipboard.
3. In a text editor, press Ctrl+P.

Expected behavior is `hello,`  inserted to the document.
Actual result is `,` only.


VS Code version: Code 1.81.1 (6c3e3dba23e8fadc360aed75ce363ba185c49794, 2023-08-09T22:22:42.175Z)
OS version: Windows_NT x64 10.0.19045
Modes:

<details>
<summary>System Info</summary>

|Item|Value|
|---|---|
|CPUs|AMD Ryzen Threadripper 3970X 32-Core Processor  (64 x 3693)|
|GPU Status|2d_canvas: enabled<br>canvas_oop_rasterization: disabled_off<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>video_decode: enabled<br>video_encode: enabled<br>vulkan: disabled_off<br>webgl: enabled<br>webgl2: enabled<br>webgpu: enabled|
|Load (avg)|undefined|
|Memory (System)|127.88GB (97.14GB free)|
|Process Argv|.|
|Screen Reader|no|
|VM|0%|
</details>Extensions: none
<!-- generated by issue reporter -->
Repository: PowerToys
Issue: enable PC set up and performance with time and day of week.
Labels: Idea-New PowerToy,Needs-Triage

### Description of the new feature / enhancement

At specific time span and specific day of week, set PC to:
Standard performance (cpu and GPU card), screen time out X min, sleep time X hours, 

### Scenario when this would be used?

I have home office, during the day I use PC frequently for queries, most of the time screen is off while playing music. 
After hours, I do programming and high CPU task demmanding, I need agressive power, and the screen need to stay on while I read or think.
night time I need to play with full horsepower :-)
today I change this manually every time.

### Supporting information

_No response_
Repository: PowerToys
Issue: Hovering highlighting
Labels: Idea-New PowerToy,Needs-Triage

### Description of the new feature / enhancement

It just occurred to me that it would be great to be able to display a highlighting line or box that hovers on top of whatever I have on screen and can be moved freely on screen. In such a way that helps me quickly identify the row/column I am reading from.

### Scenario when this would be used?

I work with spreadsheets. Most of them obviously in Excel; however, on other occasions I have to work with spreadsheets I can't manipulate nor create any kind of highlight or selecting rows/columns. Most of the time these are tables/spreadsheets cloud-based or could be on PDFs.

### Supporting information

_No response_
Repository: vscode
Issue: GitHub - "Create PR" button after forked a GitHub repo does nothing
Labels: bug,github

Does this issue occur when all extensions are disabled?: Yes

Version: 1.81.1 (user setup)
Commit: 6c3e3dba23e8fadc360aed75ce363ba185c49794
Date: 2023-08-09T22:22:42.175Z
Electron: 22.3.18
ElectronBuildId: 22689846
Chromium: 108.0.5359.215
Node.js: 16.17.1
V8: 10.8.168.25-electron.0
OS: Windows_NT x64 10.0.19045

This is an issue of the internal github extension. Steps to Reproduce:

0. Authorize your GitHub account first. 
1.  clone a repo that you does not own.
2. make some changes, save, make a commit and then click "Sync Changes".
3. vs code warns you that you don't have permission to push, do you want to create a fork, click "Create Fork".
4. After the fork is created, there is a popup at the bottom asking you to "Open on GitHub" or "Create PR". Click "Create PR".

Expected: it creates the PR.

Observed: after a brief "creating pull request..." progress bar, nothing happens. 

Video (the video is done without disabling extension; but I can confirm the bug persists even with `--disable-extensions` flag):

https://github.com/microsoft/vscode/assets/4130991/b8f808ed-0437-47d4-b2e0-cd525c2381e7

I tried to find the log to see what goes wrong, but there is literally no log whatsoever about it. The GitHub tab in output only shows the unhelpful:

```
2023-08-20 19:13:47.764 [info] Log level: Info
```

(And I don't even know where to change the log level:

![image](https://github.com/microsoft/vscode/assets/4130991/9cb587f0-2c9a-47ef-959c-2b84998265c8)
)

From the look of source code, I don't know if there is any log to begin with:

https://github.com/microsoft/vscode/blob/df7e41cc5ae63ac4f74258ba098deb070acf5ac1/extensions/github/src/pushErrorHandler.ts#L243
Repository: pytorch
Issue: Integer overflow when running torch.nn.functional.max_unpool2d
Labels: triaged,module: int overflow

### 🐛 Describe the bug

The implementation of torch.nn.functional.max_unpool2d throws:
```
numel: integer multiplication overflow
```
When feeding large input tensor or negative integer values.

The test case:

```
import torch
import numpy as np
arg_1_tensor = torch.neg(torch.rand([1, 1, 2, 2], dtype=torch.float32))
arg_1 = arg_1_tensor.clone()
arg_2_tensor = torch.randint(-4096,32,[1, 1, 2, 2], dtype=torch.int64)
arg_2 = arg_2_tensor.clone()
arg_3_0 = False
arg_3_1 = True
arg_3 = [arg_3_0,arg_3_1,]
arg_4_0 = -78819
arg_4_1 = -23458
arg_4 = [arg_4_0,arg_4_1,]
arg_5_0 = 0
arg_5_1 = 0
arg_5 = [arg_5_0,arg_5_1,]
arg_6 = None
try:
  res = torch.nn.functional.max_unpool2d(arg_1,arg_2,arg_3,arg_4,arg_5,arg_6,)
except Exception as e:
  print("Error:"+str(e))
```

### Versions

```
PyTorch version: 1.13.1
Is debug build: False
CUDA used to build PyTorch: 11.3
ROCM used to build PyTorch: N/A

OS: Ubuntu 22.04.1 LTS (x86_64)
GCC version: (Ubuntu 11.3.0-1ubuntu1~22.04) 11.3.0
Clang version: Could not collect
CMake version: Could not collect
Libc version: glibc-2.35

Python version: 3.9.15 (main, Nov 24 2022, 14:31:59) [GCC 11.2.0] (64-bit runtime)
Python platform: Linux-5.15.0-56-generic-x86_64-with-glibc2.35
Is CUDA available: True
CUDA runtime version: Could not collect
CUDA_MODULE_LOADING set to:
GPU models and configuration: GPU 0: NVIDIA GeForce GTX 1660 Ti
Nvidia driver version: 525.60.11
cuDNN version: Could not collect
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True

Versions of relevant libraries:
[pip3] numpy==1.23.5
[pip3] torch==1.12.0
[pip3] torchaudio==0.12.0
[pip3] torchvision==0.13.0
[conda] blas 1.0 mkl
[conda] cudatoolkit 11.3.1 h2bc3f7f_2
[conda] ffmpeg 4.3 hf484d3e_0 pytorch
[conda] mkl 2021.4.0 h06a4308_640
[conda] mkl-service 2.4.0 py39h7f8727e_0
[conda] mkl_fft 1.3.1 py39hd3c417c_0
[conda] mkl_random 1.2.2 py39h51133e4_0
[conda] numpy 1.23.5 py39h14f4228_0
[conda] numpy-base 1.23.5 py39h31eccc5_0
[conda] pytorch 1.12.0 py3.9_cuda11.3_cudnn8.3.2_0 pytorch
[conda] pytorch-mutex 1.0 cuda pytorch
[conda] torchaudio 0.12.0 py39_cu113 pytorch
[conda] torchvision 0.13.0 py39_cu113 pytorch
```
Repository: pytorch
Issue: Index out of bound when running torch.gather
Labels: triaged,module: advanced indexing

### 🐛 Describe the bug

Probably due to a very large negative input tensor.

```
import torch
arg_1_tensor = torch.randint(-128,32,[2, 2], dtype=torch.int64)
arg_1 = arg_1_tensor.clone()
arg_2 = 1
arg_3_tensor = torch.randint(-4096,4096,[2, 2], dtype=torch.int64)
arg_3 = arg_3_tensor.clone()
try:
  results["res_cpu"] = torch.gather(arg_1,arg_2,arg_3,)
except Exception as e:
  print("Error:"+str(e))
arg_1 = arg_1_tensor.clone().cuda()
arg_3 = arg_3_tensor.clone().cuda()
try:
  results["res_gpu"] = torch.gather(arg_1,arg_2,arg_3,)
except Exception as e:
  print("Error:"+str(e))
```

### Versions

```
PyTorch version: 1.13.1
Is debug build: False
CUDA used to build PyTorch: 11.3
ROCM used to build PyTorch: N/A

OS: Ubuntu 22.04.1 LTS (x86_64)
GCC version: (Ubuntu 11.3.0-1ubuntu1~22.04) 11.3.0
Clang version: Could not collect
CMake version: Could not collect
Libc version: glibc-2.35

Python version: 3.9.15 (main, Nov 24 2022, 14:31:59) [GCC 11.2.0] (64-bit runtime)
Python platform: Linux-5.15.0-56-generic-x86_64-with-glibc2.35
Is CUDA available: True
CUDA runtime version: Could not collect
CUDA_MODULE_LOADING set to:
GPU models and configuration: GPU 0: NVIDIA GeForce GTX 1660 Ti
Nvidia driver version: 525.60.11
cuDNN version: Could not collect
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True

Versions of relevant libraries:
[pip3] numpy==1.23.5
[pip3] torch==1.12.0
[pip3] torchaudio==0.12.0
[pip3] torchvision==0.13.0
[conda] blas 1.0 mkl
[conda] cudatoolkit 11.3.1 h2bc3f7f_2
[conda] ffmpeg 4.3 hf484d3e_0 pytorch
[conda] mkl 2021.4.0 h06a4308_640
[conda] mkl-service 2.4.0 py39h7f8727e_0
[conda] mkl_fft 1.3.1 py39hd3c417c_0
[conda] mkl_random 1.2.2 py39h51133e4_0
[conda] numpy 1.23.5 py39h14f4228_0
[conda] numpy-base 1.23.5 py39h31eccc5_0
[conda] pytorch 1.12.0 py3.9_cuda11.3_cudnn8.3.2_0 pytorch
[conda] pytorch-mutex 1.0 cuda pytorch
[conda] torchaudio 0.12.0 py39_cu113 pytorch
[conda] torchvision 0.13.0 py39_cu113 pytorch

```
Repository: pytorch
Issue: Integer overflow when running torch.nn.MaxUnpool2d
Labels: triaged,module: int overflow

### 🐛 Describe the bug

Due to feeding large negative integer value.

```
import torch
import numpy as np
arg_1 = -44717
arg_2 = 2
arg_class = torch.nn.MaxUnpool2d(arg_1,stride=arg_2,)
arg_3_0_tensor = torch.rand([1, 1, 2, 2], dtype=torch.float32)
arg_3_0 = arg_3_0_tensor.clone()
arg_3_1_tensor = torch.randint(-8,4096,[1, 1, 2, 2], dtype=torch.int64)
arg_3_1 = arg_3_1_tensor.clone()
arg_3 = [arg_3_0,arg_3_1,]
try:
  res = arg_class(*arg_3)
except Exception as e:
  print("Error:"+str(e))
```

### Versions

```
PyTorch version: 1.13.1
Is debug build: False
CUDA used to build PyTorch: 11.3
ROCM used to build PyTorch: N/A

OS: Ubuntu 22.04.1 LTS (x86_64)
GCC version: (Ubuntu 11.3.0-1ubuntu1~22.04) 11.3.0
Clang version: Could not collect
CMake version: Could not collect
Libc version: glibc-2.35

Python version: 3.9.15 (main, Nov 24 2022, 14:31:59) [GCC 11.2.0] (64-bit runtime)
Python platform: Linux-5.15.0-56-generic-x86_64-with-glibc2.35
Is CUDA available: True
CUDA runtime version: Could not collect
CUDA_MODULE_LOADING set to:
GPU models and configuration: GPU 0: NVIDIA GeForce GTX 1660 Ti
Nvidia driver version: 525.60.11
cuDNN version: Could not collect
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True

Versions of relevant libraries:
[pip3] numpy==1.23.5
[pip3] torch==1.12.0
[pip3] torchaudio==0.12.0
[pip3] torchvision==0.13.0
[conda] blas 1.0 mkl
[conda] cudatoolkit 11.3.1 h2bc3f7f_2
[conda] ffmpeg 4.3 hf484d3e_0 pytorch
[conda] mkl 2021.4.0 h06a4308_640
[conda] mkl-service 2.4.0 py39h7f8727e_0
[conda] mkl_fft 1.3.1 py39hd3c417c_0
[conda] mkl_random 1.2.2 py39h51133e4_0
[conda] numpy 1.23.5 py39h14f4228_0
[conda] numpy-base 1.23.5 py39h31eccc5_0
[conda] pytorch 1.12.0 py3.9_cuda11.3_cudnn8.3.2_0 pytorch
[conda] pytorch-mutex 1.0 cuda pytorch
[conda] torchaudio 0.12.0 py39_cu113 pytorch
[conda] torchvision 0.13.0 py39_cu113 pytorch

```
Repository: pytorch
Issue: Integer overflow when running torch.nn.AdaptiveAvgPool2d
Labels: triaged,module: int overflow

### 🐛 Describe the bug

Due to large integer value:

Reproducible code:
```
import torch
import numpy as np
arg_1 = 1250999896765
arg_class = torch.nn.AdaptiveAvgPool2d(arg_1,)
arg_2_0_tensor = torch.rand([128, 2048, 2, 2], dtype=torch.float32)
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:numel: integer multiplication overflow
```

### Versions

```
PyTorch version: 1.13.1
Is debug build: False
CUDA used to build PyTorch: 11.3
ROCM used to build PyTorch: N/A

OS: Ubuntu 22.04.1 LTS (x86_64)
GCC version: (Ubuntu 11.3.0-1ubuntu1~22.04) 11.3.0
Clang version: Could not collect
CMake version: Could not collect
Libc version: glibc-2.35

Python version: 3.9.15 (main, Nov 24 2022, 14:31:59) [GCC 11.2.0] (64-bit runtime)
Python platform: Linux-5.15.0-56-generic-x86_64-with-glibc2.35
Is CUDA available: True
CUDA runtime version: Could not collect
CUDA_MODULE_LOADING set to:
GPU models and configuration: GPU 0: NVIDIA GeForce GTX 1660 Ti
Nvidia driver version: 525.60.11
cuDNN version: Could not collect
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True

Versions of relevant libraries:
[pip3] numpy==1.23.5
[pip3] torch==1.12.0
[pip3] torchaudio==0.12.0
[pip3] torchvision==0.13.0
[conda] blas 1.0 mkl
[conda] cudatoolkit 11.3.1 h2bc3f7f_2
[conda] ffmpeg 4.3 hf484d3e_0 pytorch
[conda] mkl 2021.4.0 h06a4308_640
[conda] mkl-service 2.4.0 py39h7f8727e_0
[conda] mkl_fft 1.3.1 py39hd3c417c_0
[conda] mkl_random 1.2.2 py39h51133e4_0
[conda] numpy 1.23.5 py39h14f4228_0
[conda] numpy-base 1.23.5 py39h31eccc5_0
[conda] pytorch 1.12.0 py3.9_cuda11.3_cudnn8.3.2_0 pytorch
[conda] pytorch-mutex 1.0 cuda pytorch
[conda] torchaudio 0.12.0 py39_cu113 pytorch
[conda] torchvision 0.13.0 py39_cu113 pytorch
```
Repository: pytorch
Issue: Integer overflow when running torch.nn.ReplicationPad3d
Labels: triaged,module: int overflow

### 🐛 Describe the bug

Due to very large integer variable

```
import torch
import numpy as np
arg_1 = 1250999900000
arg_class = torch.nn.ReplicationPad3d(arg_1,)
arg_2_0_tensor = torch.rand([16, 3, 8, 320, 480], dtype=torch.float32)
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=[16, 3, 2501999800008, 2501999800320, 2501999800480]
```

### Versions

```
PyTorch version: 1.13.1
Is debug build: False
CUDA used to build PyTorch: 11.3
ROCM used to build PyTorch: N/A

OS: Ubuntu 22.04.1 LTS (x86_64)
GCC version: (Ubuntu 11.3.0-1ubuntu1~22.04) 11.3.0
Clang version: Could not collect
CMake version: Could not collect
Libc version: glibc-2.35

Python version: 3.9.15 (main, Nov 24 2022, 14:31:59) [GCC 11.2.0] (64-bit runtime)
Python platform: Linux-5.15.0-56-generic-x86_64-with-glibc2.35
Is CUDA available: True
CUDA runtime version: Could not collect
CUDA_MODULE_LOADING set to:
GPU models and configuration: GPU 0: NVIDIA GeForce GTX 1660 Ti
Nvidia driver version: 525.60.11
cuDNN version: Could not collect
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True

Versions of relevant libraries:
[pip3] numpy==1.23.5
[pip3] torch==1.12.0
[pip3] torchaudio==0.12.0
[pip3] torchvision==0.13.0
[conda] blas 1.0 mkl
[conda] cudatoolkit 11.3.1 h2bc3f7f_2
[conda] ffmpeg 4.3 hf484d3e_0 pytorch
[conda] mkl 2021.4.0 h06a4308_640
[conda] mkl-service 2.4.0 py39h7f8727e_0
[conda] mkl_fft 1.3.1 py39hd3c417c_0
[conda] mkl_random 1.2.2 py39h51133e4_0
[conda] numpy 1.23.5 py39h14f4228_0
[conda] numpy-base 1.23.5 py39h31eccc5_0
[conda] pytorch 1.12.0 py3.9_cuda11.3_cudnn8.3.2_0 pytorch
[conda] pytorch-mutex 1.0 cuda pytorch
[conda] torchaudio 0.12.0 py39_cu113 pytorch
[conda] torchvision 0.13.0 py39_cu113 pytorch
```
Repository: pytorch
Issue: Integer overflow when running torch.nn.functional.upsample
Labels: triaged,module: int overflow

### 🐛 Describe the bug

Due to large integer value.

```
import torch
import numpy as np
arg_1_tensor = torch.neg(torch.rand([1, 256, 14, 14], dtype=torch.float32))
arg_1 = arg_1_tensor.clone()
arg_2 = 1250999896766
arg_3 = "bilinear"
arg_4 = True
try:
  res = torch.nn.functional.upsample(arg_1,scale_factor=arg_2,mode=arg_3,align_corners=arg_4,)
except Exception as e:
  print("Error:"+str(e))
```

Log message:
```
Error:Storage size calculation overflowed with sizes=[1, 256, 17513998554724, 17513998554724
```

### Versions

PyTorch version: 1.13.1
Is debug build: False
CUDA used to build PyTorch: 11.3
ROCM used to build PyTorch: N/A

OS: Ubuntu 22.04.1 LTS (x86_64)
GCC version: (Ubuntu 11.3.0-1ubuntu1~22.04) 11.3.0
Clang version: Could not collect
CMake version: Could not collect
Libc version: glibc-2.35

Python version: 3.9.15 (main, Nov 24 2022, 14:31:59) [GCC 11.2.0] (64-bit runtime)
Python platform: Linux-5.15.0-56-generic-x86_64-with-glibc2.35
Is CUDA available: True
CUDA runtime version: Could not collect
CUDA_MODULE_LOADING set to:
GPU models and configuration: GPU 0: NVIDIA GeForce GTX 1660 Ti
Nvidia driver version: 525.60.11
cuDNN version: Could not collect
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True

Versions of relevant libraries:
[pip3] numpy==1.23.5
[pip3] torch==1.12.0
[pip3] torchaudio==0.12.0
[pip3] torchvision==0.13.0
[conda] blas 1.0 mkl
[conda] cudatoolkit 11.3.1 h2bc3f7f_2
[conda] ffmpeg 4.3 hf484d3e_0 pytorch
[conda] mkl 2021.4.0 h06a4308_640
[conda] mkl-service 2.4.0 py39h7f8727e_0
[conda] mkl_fft 1.3.1 py39hd3c417c_0
[conda] mkl_random 1.2.2 py39h51133e4_0
[conda] numpy 1.23.5 py39h14f4228_0
[conda] numpy-base 1.23.5 py39h31eccc5_0
[conda] pytorch 1.12.0 py3.9_cuda11.3_cudnn8.3.2_0 pytorch
[conda] pytorch-mutex 1.0 cuda pytorch
[conda] torchaudio 0.12.0 py39_cu113 pytorch
[conda] torchvision 0.13.0 py39_cu113 pytorch
Repository: pytorch
Issue: Integer overflow when running torch.nn.functional.upsample_bilinear
Labels: triaged,module: int overflow

### 🐛 Describe the bug

Due to a very large integer variable.


Code:

```
import torch
import numpy as np
arg_1_tensor = torch.neg(torch.rand([16, 512, 4, 4], dtype=torch.float32))
arg_1 = arg_1_tensor.clone()
arg_2_0 = 1250999896765
arg_2_1 = 1250999896766
arg_2 = [arg_2_0,arg_2_1,]
try:
  res = torch.nn.functional.upsample_bilinear(arg_1,size=arg_2,)
except Exception as e:
  print("Error:"+str(e))
```

Log message:

```
Error:Storage size calculation overflowed with sizes=[16, 512, 1250999896765, 1250999896766]
```a 

### Versions

PyTorch version: 1.13.1
Is debug build: False
CUDA used to build PyTorch: 11.3
ROCM used to build PyTorch: N/A

OS: Ubuntu 22.04.1 LTS (x86_64)
GCC version: (Ubuntu 11.3.0-1ubuntu1~22.04) 11.3.0
Clang version: Could not collect
CMake version: Could not collect
Libc version: glibc-2.35

Python version: 3.9.15 (main, Nov 24 2022, 14:31:59) [GCC 11.2.0] (64-bit runtime)
Python platform: Linux-5.15.0-56-generic-x86_64-with-glibc2.35
Is CUDA available: True
CUDA runtime version: Could not collect
CUDA_MODULE_LOADING set to:
GPU models and configuration: GPU 0: NVIDIA GeForce GTX 1660 Ti
Nvidia driver version: 525.60.11
cuDNN version: Could not collect
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True

Versions of relevant libraries:
[pip3] numpy==1.23.5
[pip3] torch==1.12.0
[pip3] torchaudio==0.12.0
[pip3] torchvision==0.13.0
[conda] blas 1.0 mkl
[conda] cudatoolkit 11.3.1 h2bc3f7f_2
[conda] ffmpeg 4.3 hf484d3e_0 pytorch
[conda] mkl 2021.4.0 h06a4308_640
[conda] mkl-service 2.4.0 py39h7f8727e_0
[conda] mkl_fft 1.3.1 py39hd3c417c_0
[conda] mkl_random 1.2.2 py39h51133e4_0
[conda] numpy 1.23.5 py39h14f4228_0
[conda] numpy-base 1.23.5 py39h31eccc5_0
[conda] pytorch 1.12.0 py3.9_cuda11.3_cudnn8.3.2_0 pytorch
[conda] pytorch-mutex 1.0 cuda pytorch
[conda] torchaudio 0.12.0 py39_cu113 pytorch
[conda] torchvision 0.13.0 py39_cu113 pytorch
Repository: neovim
Issue: guicursor should support inverse colors
Labels: enhancement,options

### Problem

This issue was reported in Neovide https://github.com/neovide/neovide/issues/1745

Some users want to make the cursor color the inverse of the text, but the cursor only supports one type of "inverse", the inverse of foreground and background color, which we interpret as the inverse of the default foreground and background colors in Neovide.

 

 


### Expected behavior

I think there should be a new style, `inversetext` (or similar) to support the other type of inverse colors. 

The alternative is to have a global option in the Gui implementation that controls the behaviour but I think a dedicated option would be better.
Repository: rust
Issue: LLVM does not properly construct proofs out of disjunctions.
Labels: A-LLVM,I-slow,C-bug

Consider the following code:

```rust
// This removes overflow and zero checks.
pub fn d1(num: i64, x: i64) -> i64 {
    unsafe {
        if x == -1 {
            std::hint::unreachable_unchecked()
        }
        if x == 0 {
            std::hint::unreachable_unchecked()
        }
    }
    num / x
}

// This doesn't.
pub fn d2(num: i64, x: i64) -> i64 {
    unsafe {
        if x == -1 || x == 0 {
            std::hint::unreachable_unchecked()
        }
    }
    num / x
}
```

which currently (Rust 1.71, -C opt-level=2) compiles to the following assembly:

```asm
example::d1:
        mov     rax, rdi
        mov     rcx, rdi
        or      rcx, rsi
        shr     rcx, 32
        je      .LBB0_1
        cqo
        idiv    rsi
        ret
.LBB0_1:
        xor     edx, edx
        div     esi
        ret

example::d2:
        push    rax
        test    rsi, rsi
        je      .LBB1_8
        movabs  rax, -9223372036854775808
        cmp     rdi, rax
        jne     .LBB1_3
        cmp     rsi, -1
        je      .LBB1_7
.LBB1_3:
        mov     rax, rdi
        or      rax, rsi
        shr     rax, 32
        je      .LBB1_4
        mov     rax, rdi
        cqo
        idiv    rsi
        pop     rcx
        ret
.LBB1_4:
        mov     eax, edi
        xor     edx, edx
        div     esi
        pop     rcx
        ret
.LBB1_8:
        lea     rdi, [rip + str.0]
        lea     rdx, [rip + .L__unnamed_1]
        mov     esi, 25
        call    qword ptr [rip + core::panicking::panic@GOTPCREL]
        ud2
.LBB1_7:
        lea     rdi, [rip + str.1]
        lea     rdx, [rip + .L__unnamed_1]
        mov     esi, 31
        call    qword ptr [rip + core::panicking::panic@GOTPCREL]
        ud2

.L__unnamed_2:
        .ascii  "/app/example.rs"

str.0:
        .ascii  "attempt to divide by zero"

str.1:
        .ascii  "attempt to divide with overflow"

.L__unnamed_1:
        .quad   .L__unnamed_2
        .asciz  "\017\000\000\000\000\000\000\000\025\000\000\000\005\000\000"
```

In the first version, proofs that `x` is neither zero or one are provided separately, and LLVM successfully elides corresponding checks.
In the second version, the proofs are provided using a disjunction, but the checks remain.
Ideally, `d2` compiles to the same assembly as `d1`.
Repository: TypeScript
Issue: type gets widened on declaration emit when inferred in destructuring context
Labels: Bug

### 🔎 Search Terms

declaration, widened, d.ts, destructuring

### 🕗 Version & Regression Information

- This is the behavior in every version I tried, and I reviewed the FAQ for entries

### ⏯ Playground Link

https://www.typescriptlang.org/play?jsx=0&module=1&ts=5.1.6#code/GYVwdgxgLglg9mABMOcAUBKAXIg3gTxwEYBfPAKESsQCcBTKEGpXRQxIxE878ugDwAOcGlEQQEAZzGt8iALyIADFwXJUmANxA

### 💻 Code

```ts
function foo(): {y: 1} {
    return { y: 1 }
}

export const { y = 0 } = foo();
```


### 🙁 Actual behavior

`y` is `number` in `d.ts` files, although the language service says `y` is `1|0`

### 🙂 Expected behavior

`y` is `1|0` in `d.ts` files.

### Additional information about the issue

Without the `= 0` assignment `y` properly becomes type `1` in d.ts