sharjeelyunus/github-issues-dataset huggingface dataset:
Repository: react
Issue: [Compiler Bug]: A bug with i18n translation after react compiler
Labels: Type: Bug,Status: Unconfirmed,Component: Optimizing Compiler

### What kind of issue is this?

- [X] React Compiler core (the JS output is incorrect, or your app works incorrectly after optimization)
- [ ] babel-plugin-react-compiler (build issue installing or using the Babel plugin)
- [ ] eslint-plugin-react-compiler (build issue installing or using the eslint plugin)
- [ ] react-compiler-healthcheck (build issue installing or using the healthcheck script)

### Link to repro

https://github.com/YYGod0120/yyblog

### Repro steps

1. Change the var in `app/[language]/components/Typewrite.tsx` to const (use var to skip the compiler and fix the bug)
2. use `pnpm dev` to start project
3. Click twice on the `lanswitcher`  and find that the `Banner` is not translated after the second click.

### How often does this bug happen?

Every time

### What version of React are you using?

v19.0.0-rc-3f1436cca1-20240516
Repository: kubernetes
Issue: Comments that end up in OpenAPI descriptions should be CommonMark
Labels: sig/api-machinery,kind/feature,help wanted,wg/api-expression,triage/accepted

### What would you like to be added?

The `description` field is already defined as CommonMark. Now, all strings are acceptable as CommonMark, but this issue is asking for the strings to make obvious sense as CommonMark.

We could also add metadata to comments that are not yet useful CommonMark, and implement a simplification stage that makes such a comment into more renderable CommonMark during OpenAPI generation.

### Why is this needed?

At the moment, consumers of the OpenAPI - for example, generator code that updates https://kubernetes.io/docs/ have to use heuristics to work out whether descriptions are plain text, Markdown, or some hybrid of the two.

---

#### _original issue text was_

~For the OpenAPI specification, add a new field to any definition where a Markdown field description is available.~

- ~this means annotating the doc comments to indicate that they are Markdown~
- ~the `description` OpenAPI field can then either contain the Markdown source, which is kind-of human readable, or it can contain the Markdown transformed into plain text~
Repository: vscode
Issue: tmLanguage.json changes do not appear without resetting browser cache
Labels: bug,grammar,web,confirmation-pending

Please see downstream issue for `code-server` - https://github.com/coder/code-server/issues/6798. 
Could u please elaborate on whether the issue is in vscode or in code-server?
Repository: pytorch
Issue: _convert_input_to_fake doesn't work when there are no inputs
Labels: oncall: export

### 🐛 Describe the bug

Repro:

```
import torch 
import torch._dynamo

torch._dynamo.config.capture_scalar_outputs = True
        
class FooModel(torch.nn.Module):
    def forward(self):
        x = torch.randn(1)
        y = x.item()
        return x + y

exported_program = torch.export.export(FooModel(), args=())
```

fails with

```
  File "/data/users/ezyang/b/pytorch/torch/_subclasses/functional_tensor.py", line 467, in __torch_dispatch__
    outs_unwrapped = func._op_dk(
  File "/data/users/ezyang/b/pytorch/torch/utils/_stats.py", line 20, in wrapper
    return fn(*args, **kwargs)
  File "/data/users/ezyang/b/pytorch/torch/_subclasses/fake_tensor.py", line 962, in __torch_dispatch__
    return self.dispatch(func, types, args, kwargs)
  File "/data/users/ezyang/b/pytorch/torch/_subclasses/fake_tensor.py", line 1351, in dispatch
    return self._cached_dispatch_impl(func, types, args, kwargs)
  File "/data/users/ezyang/b/pytorch/torch/_subclasses/fake_tensor.py", line 1054, in _cached_dispatch_impl
    output = self._dispatch_impl(func, types, args, kwargs)
  File "/data/users/ezyang/b/pytorch/torch/_subclasses/fake_tensor.py", line 1631, in _dispatch_impl
    op_impl_out = op_impl(self, func, *args, **kwargs)
  File "/data/users/ezyang/b/pytorch/torch/_subclasses/fake_impls.py", line 150, in dispatch_to_op_implementations_dict
    return op_implementations_dict[func](fake_mode, func, *args, **kwargs)
  File "/data/users/ezyang/b/pytorch/torch/_subclasses/fake_impls.py", line 342, in local_scalar_dense
    raise DataDependentOutputException(func)
torch._subclasses.fake_tensor.DataDependentOutputException: aten._local_scalar_dense.default

While executing %item : [num_users=1] = call_method[target=item](args = (%x,), kwargs = {})
Original traceback:
  File "/data/users/ezyang/b/pytorch/u.py", line 9, in forward
    y = x.item()
```

The proximal cause of this is

```
def _convert_input_to_fake(gm, args, kwargs):
    params_buffers = _get_params_buffers(gm)
    fake_inps: List[torch.Tensor] = []
    for node in gm.graph.nodes:
        if node.op == "placeholder" and "val" in node.meta:
            fake_val = node.meta["val"]
            if fake_val is not None and isinstance(fake_val, torch.Tensor):
                fake_inps.append(fake_val)
        
    if detected_fake_mode := detect_fake_mode(fake_inps):
        fake_mode = detected_fake_mode
    else:
        fake_mode = FakeTensorMode(shape_env=ShapeEnv())
```

The fake mode is not successfully detect from Dynamo, and a fresh one is created that doesn't respect capture_scalar_outputs

This works if you add an argument to the model.

This repro was extracted from user report at https://github.com/pytorch/pytorch/issues/116336

cc @avikchaudhuri @gmagogsfm @zhxchen17 @tugsbayasgalan @angelayi @suo @ydwu4 @msaroufim @bdhirsh @anijain2305 @chauhang for routing

### Versions

main
Repository: pytorch
Issue: Give`wait_tensor()` a schema that reflects its side effect
Labels: oncall: distributed,triaged

`wait_tensor` currently has a [schema](https://github.com/pytorch/pytorch/blob/main/torch/csrc/distributed/c10d/Functional.cpp#L393) that advertises as functional/pure (it takes in a tensor, returns a fresh tensor) - but this is not really true:

(1) it has the side effect of waiting for a pending collective to finish
(2) it returns its input directly : https://github.com/pytorch/pytorch/blob/main/torch/csrc/distributed/c10d/Functional.cpp#L307

One reason this is error prone is that e.g. if you use this API as if it had a side effect (and discard the result, e.g. the bug [here](https://github.com/pytorch/pytorch/pull/125677)), then we will DCE it during tracing (unless we land [this PR](https://github.com/pytorch/pytorch/pull/126541)).

The more proper thing to do would be to: either:

(1) tell functionalization to explicitly **not** functionalize the op.

(2) update the schema of this op to mark it as mutating its input (to reflect the side effect), and add a functional variant of the op so we can functionalize it, and "de-functionalize" it in inductor (although to be fair, this all amounts to a giant no-op).

cc @mrshenli @pritamdamania87 @zhaojuanmao @satgera @gqchen @aazzolini @osalpekar @jiayisuse @H-Huang @kwen2501 @awgu @penguinwu @fegin @XilunWu @wanchaol @fduwjj @wz337 @tianyu-l @wconstab @yf225 @chauhang @d4l3k
Repository: vscode
Issue: Line Numbers: interval display incorrectly
Labels: feature-request,editor-core


Type: <b>Feature Request</b>

When setting `lineNumbers:"interval"` and folding code, 
there could be a long interval without displaying line numbers if the lines it would display are in folded code.

I propose that in such case, either:
- a line number is forced on every 10 displayed lines
- a line number is added on the fold start line if any folded line would display a line number

VS Code version: Code 1.89.1 (dc96b837cf6bb4af9cd736aa3af08cf8279f7685, 2024-05-07T05:16:23.416Z)
OS version: Linux x64 6.6.26-1-MANJARO
Modes:


<!-- generated by issue reporter -->
Repository: ollama
Issue: unsupported protocol scheme error with ollama pull
Labels: bug,networking

### What is the issue?

I am behind a corporate proxy. I have configured proxy using the below command:

```
sudo systemctl edit ollama

[Service]
Environment="https_proxy=http://x.x.x.x:xxxx/"
Environment="http_proxy=http://x.x.x.x:xxxx/"


systemctl daemon-reload

systemctl restart ollama
```

I am receiving the below error while pulling any model:

```
pulling manifest
Error: Get "?nonce=4Tzwhl8cqbwHyVbQ4jHiqw&scope=&service=&ts=1716299545": unsupported protocol scheme ""
```

I am running this on Ubuntu 22.04



### OS

Linux

### GPU

Nvidia

### CPU

Intel

### Ollama version

0.1.38
Repository: godot
Issue: setting a StyleBox bg_color with a @tool script makes the colour flicker to black
Labels: bug,topic:editor,needs testing,topic:gui

### Tested versions

4.3dev5

### System information

Windows 10

### Issue description

see title

### Steps to reproduce

something like this....

```swift
@tool

var stylebox = StyleBoxFlat.new()


@export var color: Color:
	set(value):
		stylebox.bg_color = value
```

### Minimal reproduction project (MRP)

/
Repository: PowerToys
Issue: Add shortcut to move an entry up or down
Labels: Idea-Enhancement,Needs-Triage,Product-Hosts File Editor

### Description of the new feature / enhancement

Hi,
When adding a new entry to the hosts file via the Hosts File Editor, it appears at the end. To more easily retrieve my IPs / hostnames when reading the hosts file, I am used to order them. With the Hosts File Editor, you can do this by right clicking on an entry and use the 'Move up' or 'Move down' items of the popup menu. But if you want to move up (or down) an entry for several positions, you have to repeat this action many times, which is not very handy. 
It would be helpful to be able to select an entry and use a shortcut to move it up or down.
As the up and down arrows keys are already used to move the "focus" on an entry (which is fine), I guess something like **CTRL + 'up arrow'** and **CTRL + 'down arrow'** could be used for that purpose.

Note: It would also be very handy to be able to drag and drop an entry directly at the desired position.

Thank you.

### Scenario when this would be used?

Add a new entry, which appears at the end of the list in the Editor.

Select the new entry.
Then use directly the shortcuts to move up and order this new entry at the position you want.
or
Directly drag and drop the entry at the desired position.

### Supporting information

_No response_
Repository: godot
Issue: Physics2D: Non-uniform scale warning on `CollisionObject2D` is missing compared to `CollisionObject3D`.
Labels: documentation,topic:physics,needs testing,topic:2d

### Tested versions

Godot v4.3.dev6.mono - Windows 10.0.17763 - Vulkan (Forward+) - dedicated NVIDIA GeForce RTX 4060 Ti (NVIDIA; 31.0.15.5222) - AMD Ryzen 9 5900X 12-Core Processor (24 Threads)

### System information

Godot v4.3.dev6.mono - Windows 10.0.17763 - Vulkan (Forward+) - dedicated NVIDIA GeForce RTX 4060 Ti (NVIDIA; 31.0.15.5222) - AMD Ryzen 9 5900X 12-Core Processor (24 Threads)

### Issue description

`CollisionObject3D` will [warn the user about non-uniform scaling](https://github.com/godotengine/godot/blob/master/scene/3d/physics/collision_object_3d.cpp#L739), however, [this does not apply](https://github.com/godotengine/godot/blob/master/scene/2d/physics/collision_object_2d.cpp#L584) to `CollisionObject2D`.

### Steps to reproduce

When opening the MRP, there is no warning about non-uniform scaling, and the physics behavior is weird.

https://github.com/godotengine/godot/assets/71481700/0fed5d3a-eb18-4448-9a99-1eae5ed672a0



### Minimal reproduction project (MRP)

[MRP_CharacterSliding.zip](https://github.com/godotengine/godot/files/15390944/MRP_CharacterSliding.zip)
Repository: angular
Issue: Add case insensitive (query) param map (CaseInsensitiveParamMap)
Labels: feature,freq1: low,area: router,P5

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

router

### Description

A [very common](https://stackoverflow.com/questions/50098153/how-to-take-the-values-from-the-case-sensitive-query-param-variables) [issue](https://stackoverflow.com/questions/56297471/case-insensitive-query-params-in-angular) seems to be to get a (query) parameter in a case insensitive way.

<details>
<summary>wrong hypothesis</summary>

~~More back-story: This seems to happen, because `this.router.navigate` also seems to lower-case all query parameters you pass it in:~~

```ts
    const queryParams = {LoGiN: "abc"} as Params;
    console.info('Triggering filter with data:', queryParams);

    this.router.navigate(
      [],
      {
        relativeTo: this.activatedRoute,
        queryParams: queryParams
      }
    );    
```

~~This results in `.../?login=abc` on the current page. (I may create a new bug for this, if that is not intentional.)
Anyway, there may be other reasons to ignore the casing. And I tried...~~
</details>

E.g. I want to use query parameters for filtering data with specific terms in my application, so I can do this:
```ts
    this.activatedRoute.queryParams
      .subscribe(params => {
          const paramMap = convertToParamMap(params);

          const filter = {
            login: paramMap.get("login")
            // ...
          };
          
          // ...
        });            
```

In contrast to using `params` (Params) directly, it does not throw,

Now, if I pass `...?login=blaBlub` this works, but if I do pass `...?Login=blaBlub` it does not as the usual `convertToParamMap`/param map is case-sensitive, apparently.

### Proposed solution

Full credit goes to [Bradley Carey](https://bradleycarey.com/posts/handling-case-insensitive-query-parameters-in-angular/), who has developed a `CaseInsensitiveParamMap` including test cases etc.

Maybe it can just be integrated in some way or another into Angular?

### Alternatives considered

Any similar solution could also be developed? Like adding a flag to the existing `ParamsAsMap` :
https://github.com/angular/angular/blob/87c5f3c521a373af41751a15bea0cd4f16bab23a/packages/router/src/shared.ts#L75

Also, it should probably support localization i.e. use [`toLocaleLowerCase`](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/String/toLocaleLowerCase) or the Angular equivalent.
Repository: vscode
Issue: In C# build output, I always have to Ctrl+Click at least twice to follow a code error/warning link.
Labels: bug,terminal-links

Type: <b>Bug</b>

1.  create a C# solution/project
2.  do something that creates a compile error (like remove a curly brace)
3.  build it.
4.  in the Terminal, Ctrl+Click on a code file link.

EXPECTED:
- navigates to file on first Ctrl+Click

ACTUAL:
- must Ctrl+Click _at least_ twice

VS Code version: Code 1.89.1 (dc96b837cf6bb4af9cd736aa3af08cf8279f7685, 2024-05-07T05:13:33.891Z)
OS version: Windows_NT x64 10.0.22631
Modes:

<details>
<summary>System Info</summary>

|Item|Value|
|---|---|
|CPUs|13th Gen Intel(R) Core(TM) i9-13900H (20 x 2995)|
|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|
|Load (avg)|undefined|
|Memory (System)|31.59GB (5.54GB free)|
|Process Argv|--crash-reporter-id c8e3650d-a133-42e9-901c-3aa8e8465629|
|Screen Reader|no|
|VM|0%|
</details><details><summary>Extensions (17)</summary>

Extension|Author (truncated)|Version
---|---|---
libman|adr|1.0.1
githistory|don|0.6.20
EditorConfig|Edi|0.16.4
vscode-drawio|hed|1.6.6
azure-pipelines|ms-|1.228.0
vscode-azureresourcegroups|ms-|0.9.0
vscode-bicep|ms-|0.27.1
blazorwasm-companion|ms-|1.1.4
csdevkit|ms-|1.5.20
csharp|ms-|2.28.11
vscode-dotnet-runtime|ms-|2.0.5
remote-containers|ms-|0.362.0
remote-wsl|ms-|0.88.2
azure-account|ms-|0.12.0
powershell|ms-|2024.2.2
vscode-xml|red|0.26.1
code-spell-checker|str|3.0.1


</details><details>
<summary>A/B Experiments</summary>

```
vsliv368cf:30146710
vspor879:30202332
vspor708:30202333
vspor363:30204092
tftest:31042121
vswsl492cf:30256860
vscorecescf:30445987
vscod805:30301674
binariesv615:30325510
vsaa593cf:30376535
py29gd2263:31024239
c4g48928:30535728
azure-dev_surveyone:30548225
962ge761:30959799
pythongtdpath:30769146
welcomedialog:30910333
pythonidxpt:30866567
pythonnoceb:30805159
asynctok:30898717
pythontestfixt:30902429
pythonregdiag2:30936856
pythonmypyd1:30879173
pythoncet0:30885854
h48ei257:31000450
pythontbext0:30879054
accentitlementst:30995554
dsvsc016:30899300
dsvsc017:30899301
dsvsc018:30899302
cppperfnew:31000557
dsvsc020:30976470
pythonait:31006305
chatpanelc:31048052
dsvsc021:30996838
jg8ic977:31013176
pythoncenvpt:31049070
fchga941:31046352
pythonprc:31047982
dwnewjupyter:31046869
26j00206:31048877

```

</details>

<!-- generated by issue reporter -->
Repository: rust
Issue: Bad interaction between never_type, try_blocks, and From/Into
Labels: T-lang,T-compiler,C-bug,F-never_type,F-try_blocks,S-has-mcve

The following code does not compile but the 2 commented alternatives compile:

```rust
#![feature(never_type)]
#![feature(try_blocks)]

fn bar(_: Result<impl Into<!>, u32>) {
// fn bar(_: Result<impl Into<()>, u32>) {
// fn bar(_: Result<!, u32>) {
    unimplemented!()
}

pub fn foo(x: Result<!, u32>) {
    bar(try { x? });
}
```

The error is:

```
error[E0277]: the trait bound `!: From<()>` is not satisfied
  --> src/lib.rs:11:9
   |
11 |     bar(try { x? });
   |     --- ^^^^^^--^^
   |     |   |     |
   |     |   |     this tail expression is of type `Result<(), u32>`
   |     |   the trait `From<()>` is not implemented for `!`, which is required by `(): Into<!>`
   |     required by a bound introduced by this call
   |
   = note: this error might have been caused by changes to Rust's type-inference algorithm (see issue #48950 <https://github.com/rust-lang/rust/issues/48950> for more information)
   = help: did you intend to use the type `()` here instead?
   = note: required for `()` to implement `Into<!>`
```

For some reason, rustc believes that the try block should return `()` instead of `!`.

### Meta

`rustc --version --verbose`:
```
rustc 1.80.0-nightly (7d83a4c13 2024-05-06)
binary: rustc
commit-hash: 7d83a4c131ab9ae81a74c6fd825c827d74a2881d
commit-date: 2024-05-06
host: x86_64-unknown-linux-gnu
release: 1.80.0-nightly
LLVM version: 18.1.4
```
Repository: pytorch
Issue: One complex number or boolean value of a 1D or more D tensor with `argmin()` and `dim=` works
Labels: triaged,actionable,module: edge cases

### 🐛 Describe the bug

One complex number or boolean value of a 1D or more D tensor with [argmin()](https://pytorch.org/docs/stable/generated/torch.argmin.html) gets the error as shown below:

One complex number with a 1D or 2D tensor:

```python
import torch

my_tensor = torch.tensor([7.+5.j])

torch.argmin(input=my_tensor) # RuntimeError: "argmin_cpu" not implemented for 'ComplexFloat'

my_tensor = torch.tensor([[7.+5.j]])

torch.argmin(input=my_tensor) # RuntimeError: "argmin_cpu" not implemented for 'ComplexFloat'
```

One boolean value with a 1D or 2D tensor:

```python
import torch

my_tensor = torch.tensor([True])

torch.argmin(input=my_tensor) # RuntimeError: "argmin_cpu" not implemented for 'Bool'

my_tensor = torch.tensor([[True]])

torch.argmin(input=my_tensor) # RuntimeError: "argmin_cpu" not implemented for 'Bool'
```

But one complex number or boolean value of a 1D or more D tensor with `argmin()` and `dim=` works as shown below:

One complex number with a 1D or 2D tensor:

```python
import torch

my_tensor = torch.tensor([7.+5.j])

torch.argmin(input=my_tensor, dim=0)
torch.argmin(input=my_tensor, dim=-1)
# tensor(0)

my_tensor = torch.tensor([[7.+5.j]])

torch.argmin(input=my_tensor, dim=0)
torch.argmin(input=my_tensor, dim=1)
torch.argmin(input=my_tensor, dim=-1)
torch.argmin(input=my_tensor, dim=-2)
# tensor([0])
```

One boolean value with a 1D or 2D tensor:

```python
import torch

my_tensor = torch.tensor([True])

torch.argmin(input=my_tensor, dim=0)
torch.argmin(input=my_tensor, dim=-1)
# tensor(0)

my_tensor = torch.tensor([[True]])

torch.argmin(input=my_tensor, dim=0)
torch.argmin(input=my_tensor, dim=1)
torch.argmin(input=my_tensor, dim=-1)
torch.argmin(input=my_tensor, dim=-2)
# tensor([0])
```

### Versions

```python
import torch

torch.__version__ # 2.2.1+cu121
```
Repository: pytorch
Issue: One complex number or boolean value of a 1D or more D tensor with `argmax()` and `dim=` works
Labels: triaged,actionable,module: edge cases

### 🐛 Describe the bug

One complex number or boolean value of a 1D or more D tensor with [argmax()](https://pytorch.org/docs/stable/generated/torch.argmax.html) gets the error as shown below:

One complex number with a 1D or 2D tensor:

```python
import torch

my_tensor = torch.tensor([7.+5.j])

torch.argmax(input=my_tensor) # RuntimeError: "argmax_cpu" not implemented for 'ComplexFloat'

my_tensor = torch.tensor([[7.+5.j]])

torch.argmax(input=my_tensor) # RuntimeError: "argmax_cpu" not implemented for 'ComplexFloat'
```

One boolean value with a 1D or 2D tensor:

```python
import torch

my_tensor = torch.tensor([True])

torch.argmax(input=my_tensor) # RuntimeError: "argmax_cpu" not implemented for 'Bool'

my_tensor = torch.tensor([[True]])

torch.argmax(input=my_tensor) # RuntimeError: "argmax_cpu" not implemented for 'Bool'
```

But one complex number or boolean value of a 1D or more D tensor with `argmax()` and `dim=` works as shown below:

One complex number with a 1D or 2D tensor:

```python
import torch

my_tensor = torch.tensor([7.+5.j])

torch.argmax(input=my_tensor, dim=0)
torch.argmax(input=my_tensor, dim=-1)
# tensor(0)

my_tensor = torch.tensor([[7.+5.j]])

torch.argmax(input=my_tensor, dim=0)
torch.argmax(input=my_tensor, dim=1)
torch.argmax(input=my_tensor, dim=-1)
torch.argmax(input=my_tensor, dim=-2)
# tensor([0])
```

One boolean value with a 1D or 2D tensor:

```python
import torch

my_tensor = torch.tensor([True])

torch.argmax(input=my_tensor, dim=0)
torch.argmax(input=my_tensor, dim=-1)
# tensor(0)

my_tensor = torch.tensor([[True]])

torch.argmax(input=my_tensor, dim=0)
torch.argmax(input=my_tensor, dim=1)
torch.argmax(input=my_tensor, dim=-1)
torch.argmax(input=my_tensor, dim=-2)
# tensor([0])
```


### Versions

```python
import torch

torch.__version__ # 2.2.1+cu121
```