sharjeelyunus/github-issues-dataset huggingface dataset:
Repository: godot
Issue: Debugger Evaluator format issue on division 
Labels: bug,topic:editor

### Tested versions

4.4.dev (since it was added https://github.com/godotengine/godot/pull/97647)

### System information

Windows 10.0.22631 - Multi-window, 1 monitor - Vulkan (Forward+) - dedicated NVIDIA GeForce RTX 2070 (NVIDIA; 32.0.15.6603) - Intel(R) Core(TM) i7-10750H CPU @ 2.60GHz (12 threads)

### Issue description

When using a forward slash `/` to divide in the REPL expression evaluator, a group header is created holding and separates the operands:

![Screenshot 2024-10-31 200822](https://github.com/user-attachments/assets/a8b94e44-ed54-4bf5-9a0c-6e7db09fa472)

This can be nested as well with multiple `/`.

Also right clicking on a previously evaluated expression to copy it does not work as expected.
Copying `property path` (though it isn't a property) copies `Evaluated/` before the actual expression.
Copying the `value` does not work.

![image](https://github.com/user-attachments/assets/693e46a6-2d32-40ec-b270-b39afa1a9d47)



### Steps to reproduce

1. Open the Debugger Evaluator and break on something
2. Enter an expression with `/` to divide some numbers or variables, like `10/2`


### Minimal reproduction project (MRP)

N/A
Repository: pytorch
Issue: registering op through function does not work
Labels: triaged,module: custom-operators,oncall: pt2,module: pt2-dispatcher

### 🐛 Describe the bug

a very strange bug:

```python
import torch
from torch.library import Library

def silly_attention(q: torch.Tensor, k: torch.Tensor, v: torch.Tensor,
                    out: torch.Tensor) -> None:
    out.copy_(q)
    out += k
    out += v

def silly_attention_fake(q: torch.Tensor, k: torch.Tensor, v: torch.Tensor,
        out: torch.Tensor) -> None:
    return

def direct_register_custom_op(
    library_name: str,
    op_name: str,
    op_func,
    mutates_args,
    fake_impl = None,
):
    schema_str = torch.library.infer_schema(op_func, mutates_args=mutates_args)
    my_lib = Library(library_name, "FRAGMENT")
    my_lib.define(op_name + schema_str)
    my_lib.impl(op_name, op_func, "CUDA")
    if fake_impl is not None:
        my_lib._register_fake(op_name, fake_impl)


# does not work
direct_register_custom_op(
    "silly",
    "attention",
    silly_attention,
    ["out"],
    silly_attention_fake,
)

# it works
from torch.library import Library
my_lib = Library("silly", "FRAGMENT")
my_lib.define("attention(Tensor q, Tensor k, Tensor v, Tensor(a3!) out) -> ()")
my_lib.impl("attention", silly_attention, "CUDA")
my_lib._register_fake("attention", silly_attention_fake)

print(torch.ops.silly.attention)
```

If I directly run the registration code, it works.

If I call it through a function, it does not work. The op cannot be found.

cc @ezyang @chauhang @penguinwu @zou3519 @bdhirsh @yf225 

### Versions

2.5.0+cu124
Repository: tensorflow
Issue: `tf.math.floormod` not throwing `Integer division by zero` error on GPU for tensor of int64 dtype
Labels: stat:awaiting tensorflower,type:bug,comp:ops,TF 2.18

### Issue type

Bug

### Have you reproduced the bug with TensorFlow Nightly?

No

### Source

source

### TensorFlow version

2.18

### Custom code

Yes

### OS platform and distribution

Linux Ubuntu 20.04

### Mobile device

_No response_

### Python version

3.10

### Bazel version

_No response_

### GCC/compiler version

_No response_

### CUDA/cuDNN version

12.3

### GPU model and memory

_No response_

### Current behavior?

Running `tf.math.floormod` with a tensor containing zeroes in the denominator tensor on GPU does not throw a division by zero error when the tensor has a dtype of `int64`.

[colab](https://colab.research.google.com/drive/1e053_hcmu0sHQcMPop-_WZR6ya1bw6dy?usp=sharing)

### Standalone code to reproduce the issue

```shell
import tensorflow as tf
A = tf.constant([[2,2],[2,2]], dtype=tf.int64)
B = tf.constant([[0,0],[0,0]], dtype=tf.int64)

with tf.device("/gpu:0"):
    output_gpu = tf.math.floormod(A, B) # No error
    print(f"\nGPU: {output_gpu}\n") # GPU: [[2 2] [2 2]]

with tf.device("/cpu:0"):
    output_cpu = tf.math.floormod(A, B) 
    # InvalidArgumentError: Integer division by zero
```


### Relevant log output

```shell
GPU: [[2 2]
 [2 2]]

---------------------------------------------------------------------------
InvalidArgumentError                      Traceback (most recent call last)
<ipython-input-2-ba17e88e7095> in <cell line: 9>()
      8 
      9 with tf.device("/cpu:0"):
---> 10     output_cpu = tf.math.floormod(A, B)
     11     # InvalidArgumentError: Integer division by zero

2 frames
/usr/local/lib/python3.10/dist-packages/tensorflow/python/framework/ops.py in raise_from_not_ok_status(e, name)
   5981 def raise_from_not_ok_status(e, name) -> NoReturn:
   5982   e.message += (" name: " + str(name if name is not None else ""))
-> 5983   raise core._status_to_exception(e) from None  # pylint: disable=protected-access
   5984 
   5985 

InvalidArgumentError: {{function_node __wrapped__FloorMod_device_/job:localhost/replica:0/task:0/device:CPU:0}} Integer division by zero [Op:FloorMod] name:
```
Repository: rust
Issue: Inlining `-Cinstrument-coverage` code into a uninstrumented crate causes problems
Labels: T-compiler,A-code-coverage

`-Cinstrument-coverage` is a per-crate setting, which makes it possible for instrumented and uninstrumented crates to be mixed during compilation.

This must be supported to some extent, because the standard libraries are built without coverage instrumentation, and instrumenting them would be unwanted in most cases. And we would also like to support instrumenting a project without instrumenting its dependencies, though cargo currently doesn't have a good way to actually set different rustflags for dependencies. Fortunately, inlining uninstrumented code into an instrumented crate mostly works, though in some cases it might end up being unexpectedly instrumented.

The more difficult case is when instrumented code gets inlined into an uninstrumented crate. This is an unusual configuration, but it can occur in practice, e.g. when building doctests as in https://github.com/rust-lang/rust/pull/132395#issuecomment-2449638516. When this happens, two problems can arise:

- Inlined MIR might contain `StatementKind::Coverage` statements, despite the current crate being built without coverage instrumentation. When codegen sees coverage statements, it cannot assume that coverage instrumentation is enabled.
- If the inlined code isn't instrumented, then executing it won't increase coverage counts, despite its original crate having been built with instrumentation.

---

For now, the workaround is to quietly discard any coverage statements that make their way into an uninstrumented crate. This avoids the ICE seen in #132395, but doesn't solve the problem of that code not being instrumented as a result.
Repository: flutter
Issue: [Linux] Make FlView an interface
Labels: engine,platform-linux,c: proposal,P3,team-linux,triaged-linux

### Use case

This would allow for some compatibility with existing plugins inside of a custom embedder but on Linux. If a plugin wishes to have access to the GTK side of things, they should check via `GTK_IS_WIDGET(view)`.

### Proposal

1. Make `FlView` an interface
2. Move the existing `FlView` to be a derivative of the interface and call it `FlViewWidget` or something similar.

Implementation can be found here: https://github.com/RossComputerGuy/flutter-engine/commit/32cb2d43cae804846692ace0c17cbceee6c5669b
Repository: pytorch
Issue: [Torch TO ONNX BUG] The right shift operation in torch is mapped as a division operation when converted to ONNX.
Labels: module: onnx,triaged,onnx-needs-info

### 🐛 Describe the bug

The right shift operation in torch is mapped as a "DIV" operation instead of a "SHR" operation when converted to ONNX. This causes some problems when the negative number shifts to the right. For example, shifting -3527 right by 8 bits is not the same as dividing it by 256, especially if the result is truncated.

### Versions

python==3.10.13
torch==2.1.0
onnx==1.16.2
Repository: godot
Issue: Switching from the Default Keyboard to Num Keyboard Drops Keyboard altogether
Labels: bug,platform:android,needs testing,topic:input

### Tested versions

- Reproducible in Godot Stable v4.2.1

### System information

Windows 11 - Godot 4.2.1 (Developed an app for Android 14)

### Issue description

When switching focus from a textbox using the number keyboard to the default keyboard, the keyboard will drop entirely. The default keyboard should stay up when being switched to.

### Steps to reproduce

Create 2 textboxes
Give one a Number Keyboard (1)
Give two a Default Keyboard (2)
Use a signal like _on_text_changed, or _on_text_submitted
On Android make it so when you submit a value on a number keyboard (1), the default keyboard grabs focus (using grab_focus()) (2)
The keyboard will drop out on Android

### Minimal reproduction project (MRP)

N/A
Repository: vscode
Issue: Add title bar context menu entry in full screen to toggle menu bar on windows and linux
Labels: feature-request,linux,windows,titlebar,menus

<!-- ⚠️⚠️ Do Not Delete This! feature_request_template ⚠️⚠️ -->
<!-- Please read our Rules of Conduct: https://opensource.microsoft.com/codeofconduct/ -->
<!-- Please search existing issues to avoid creating duplicates. -->

<!-- Describe the feature you'd like. -->
Do not hide the Menu Bar (that includes File, Edit, etc.) when entering fullscreen on Windows. It makes the fullscreen mode quite less usable. I really do like using it through!
![Image](https://github.com/user-attachments/assets/29c4db7a-5c0d-428c-a800-affc0b341b81)
![Image](https://github.com/user-attachments/assets/22c911a2-9b6f-4429-b3ca-cd8a1a60394e)
Repository: transformers
Issue: Add more configurations to the class LlavaOnevisionConfig.
Labels: Feature request

### Feature request

I would like to add more flags to configuration class `LlavaOnevisionConfig`, including `spatial_pool_mode`, `newline_position `

### Motivation

 [LlavaOnevisionModel](https://huggingface.co/llava-hf/llava-onevision-qwen2-7b-ov-hf) uses the fixed value of `spatial_pool_mode="bilinear"` and `newline_position="one_token"`,  so the defined class [LlavaOnevisionConfig](https://github.com/huggingface/transformers/blob/main/src/transformers/models/llava_onevision/configuration_llava_onevision.py#L27C7-L27C27)  has omitted the corresponding configurations.

Many of models are trained with the LLaVA-Onevision model using the different flags mentioned above. Incorporating these flags into the configuration file would be highly helpful for developers.

### Your contribution

I can submit a PR with the modifications if you agree with the incorporation of this change.
Repository: rust
Issue: Array and Vec's Clone specialization is maybe unsound with conditionally Copy types.
Labels: P-medium,T-compiler,I-unsound,A-specialization,C-bug,T-libs,E-needs-investigation

Currently, [the `Clone` impl for `[T; N]`](https://github.com/rust-lang/rust/blob/24254efb432739965c50c43c86b2eabbb947a31c/library/core/src/array/mod.rs#L426-L455) uses specialization. If `T` implements `Copy`, then cloning a `[T; N]` will do a memcpy (ignoring `T`'s `Clone` impl). If `T` doesn't implement `Copy`, then it will iterate and call `T`'s `Clone` impl.

However, specialization doesn't look at lifetimes. Therefore, even if `T` implements `Copy` for only some lifetimes, cloning a `[T; N]` will do a memcopy. This is incorrect in the case where `T` actually doesn't implement `Copy`. For example:

```rust
struct Weird<'a>(&'a i32);

impl Clone for Weird<'_> {
    fn clone(&self) -> Self {
        println!("clone() called");
        Weird(self.0)
    }
}

impl Copy for Weird<'static> {}

fn main() {
    let local = 1;
    let _ = [Weird(&local)].clone();
}
```

In the above code, `Weird` only implements `Copy` when its lifetime is `'static`. Therefore, I think that cloning a `[Weird<'a>; 1]` should call the `clone()` method. However, running the above code in either stable (1.82.0) or nightly (`1.84.0-nightly (2024-10-30 759e07f063fb8e6306ff)`) rust doesn't print anything. I believe that this is incorrect.

I am unsure whether or not this can cause UB in purely safe code, (hence the "maybe" in the issue title). But maybe someone else could figure out how to do that?

However, I have written [this code](https://play.rust-lang.org/?version=stable&mode=debug&edition=2021&gist=dd3a22edf11e2d48fe48497ba2428eab), which uses unsafe code to implement a `WeirdCow` type whose public API I believe is sound on its own, but can be used in combination with array's Clone specialization to cause use-after-free. Either this `WeirdCow` type is unsound, or the array's Clone implementation is unsound, and I can't figure out which.

@rustbot label +I-unsound
Repository: rust
Issue: rustdoc: Consider adding CCI for the HIR expressions of public constants
Labels: T-rustdoc,C-enhancement

When a constant is inlined into another crate, we are forced to always show the evaluated/folded version of the constant. This is because we don't have access to the original HIR in the metadata.

This could be a situation where we can use (https://github.com/rust-lang/rfcs/pull/3662) to store the original expression for public constants (that could potentially be inlined by other crates) so that we don't have the cross-crate issue. Might be applicable to other cross-crate inconsistencies too (though hopefully the type alias one will be resolved by lazy_type_alias).

_Adapted from a post by @camelid in https://github.com/rust-lang/rust/issues/131975#issuecomment-2451225947_
Repository: PowerToys
Issue: [Advanced Paste] Remove clipboard history from main UI if feature turned off
Labels: Help Wanted,Cost-Small,Product-Advanced Paste

### Description of the new feature / enhancement

Remove the clipboard history function from Advanced Paste.

### Scenario when this would be used?

Windows has built in clipboard history (win + v) , it’s redundant to reimplement this feature and put it in the pop up.

### Supporting information

_No response_
Repository: flutter
Issue: [Web] Web app inside WebView is not responding after halfway swiping back gesture on iOS
Labels: c: crash,f: routes,a: platform-views,p: webview,platform-web,package,has reproducible steps,P2,team-web,triaged-web,found in release: 3.24,found in release: 3.27

### Steps to reproduce

1. Create a web application with three pages
2. Create a native application and use the web_view plug-in to open the web application
3. Enter the web page, slide sideways to return, and then cancel the return

### Expected results

The page is normal

### Actual results

ANR

### Code sample

<details open><summary>Code sample</summary>

```dart
final GoRouter _router = GoRouter(
  initialLocation: '/',
  routes: <RouteBase>[
    GoRoute(
      path: '/',
      builder: (BuildContext context, GoRouterState state) {
        return const MyHomePage();
      },
    ),
    GoRoute(
      path: 'list',
      builder: (BuildContext context, GoRouterState state) {
        return const ListPage();
      },
    ),

    GoRoute(
      path: 'detail',
      builder: (BuildContext context, GoRouterState state) {
        return const ListPage();
      },
    ),
  ],
);

void main() {
  runApp(const MyApp());
}

class MyApp extends StatelessWidget {
  const MyApp({super.key});
  @override
  Widget build(BuildContext context) {
    return MaterialApp.router(
      routerConfig: _router,
    );
  }
}

class MyHomePage extends StatefulWidget {
  const MyHomePage({super.key});
  @override
  State<MyHomePage> createState() => _MyHomePageState();
}

class _MyHomePageState extends State<MyHomePage> {

  @override
  Widget build(BuildContext context) {
    return Scaffold(
      appBar: AppBar(
        backgroundColor: Theme.of(context).colorScheme.inversePrimary,
        title: Text('Flutter Web Home Page'),
      ),
      body: Center(
        child: Column(
          mainAxisAlignment: MainAxisAlignment.center,
          children: <Widget>[
            TextButton(onPressed: (){
              Navigator.of(context).push(MaterialPageRoute(builder: (c)=> const ListPage()));
            }, child: Text('open web')),
          ],
        ),
      ),
    );
  }
}
```

</details>


### Screenshots or Video

<details open>
<summary>Screenshots / Video demonstration</summary>



https://github.com/user-attachments/assets/0da16172-0aeb-4cdc-8ae6-088190d99a56


</details>


### Logs

_No response_

### Flutter Doctor output

<details open><summary>Doctor output</summary>

```console
Doctor summary (to see all details, run flutter doctor -v):
[✓] Flutter (Channel stable, 3.24.3, on macOS 14.0 23A344 darwin-arm64 (Rosetta), locale zh-Hans-CN)
[✓] Android toolchain - develop for Android devices (Android SDK version 34.0.0)
[✓] Xcode - develop for iOS and macOS (Xcode 15.3)
[✓] Chrome - develop for the web
[✓] Android Studio (version 2023.2)
[✓] VS Code (version 1.94.2)
[✓] Connected device (5 available)
[✓] Network resources

• No issues found!
```

```console
webview_flutter: 4.1.0
```

</details>
Repository: svelte
Issue: Svelte 5: Unable to monitor state/derived without running the block
Labels: awaiting submitter

### Describe the bug

On page load, we pass the initial data into the component. Because of this, we don't need to fetch data again when the component is mounted, but if the query params change, we need to trigger a section of code to refetch results.

In Svelte 4, we had something like this (trimmed and simplified but it should be clear): (`$applicationContextStore.params` is just a store that initialized with params from the current URL)

```svelte
<script lang="ts">
  export let users: User[]

  let params = $applicationContextStore.params

  $: fetchData({
    url: '/users',
    params, // <- updates to this will trigger this call
    onSuccess: (newUsers: User[]) => {
      users = newUsers
    })
  })
</script>

<a href="#" on:click={() => {
  params = { ...params, sort: 'asc' }
}}>Sort Asc</a>

<a href="#" on:click={() => {
  params = { ...params, sort: 'desc' }
}}>Sort Desc</a>

<table>....</table>
```

This worked well. Users were passed in when the component was rendered for the first time. Then if the sorting links were clicked, the params were updated, triggering the fetchData block.

With Svelte 5, there does not appear to be any way to monitor a block of code for state changes without it also first running.

```svelte
<script lang="ts">
  interface Props {
    users: User[]
  }

  let { users }: Props = $props()

  let params = $state($applicationContextStore.params)

  $effect(() => {
    fetchData({
      url: '/users',
      params,
      onSuccess: (newUsers: User[]) => {
        users = newUsers
      })
    })
  })
</script>

<a href="#" onclick={() => {
  params = { ...params, sort: 'asc' }
}}>Sort Asc</a>

<a href="#" onclick={() => {
  params = { ...params, sort: 'desc' }
}}>Sort Desc</a>

<table>....</table>
```

The above doesn't work as intended. $derived, $derived.by, $effect, $effect.pre, and onMount all run the code when the component is mounted, which is not what we want, because we are already passing in the initial data. This ends up doubling requests which returns exactly the same data. 

What we need is a $track function or something, that doesn't run when component is mounted, but does run when any state vairables in it are run.

On a different note, the migrator is converting it to use legacy/run, which behind the scenes looks like $effect.pre, so the migrator is recommending a change that breaks functionality.

Any ideas/advice?

### Reproduction

See above

### Logs

_No response_

### System Info

```shell
System:
    OS: macOS 15.1
    CPU: (12) arm64 Apple M3 Pro
    Memory: 91.22 MB / 18.00 GB
    Shell: 5.9 - /bin/zsh
  Binaries:
    Node: 20.15.1 - ~/.asdf/installs/nodejs/20.15.1/bin/node
    Yarn: 4.3.1 - ~/.asdf/installs/nodejs/20.15.1/bin/yarn
    npm: 10.8.2 - ~/.asdf/plugins/nodejs/shims/npm
    bun: 1.1.0 - ~/.bun/bin/bun
  Browsers:
    Chrome: 130.0.6723.92
    Safari: 18.1
  npmPackages:
    svelte: ^5.1.9 => 5.1.9
```


### Severity

blocking an upgrade
Repository: kubernetes
Issue: SchedulingWhileGated test in scheduler-perf failed but was able to produce results
Labels: kind/bug,sig/scheduling,needs-triage

### What happened?

While trying to reproduce the Scheduler_perf results from #127180 , I encountered an issue where the SchedulingWhileGated test failed but still produced results.
I’m running the following code on an Ubuntu 22.04 Linux VM with 4 CPUs, 8GB memory, and a 100GB hard disk, under various configurations.

`make test-integration WHAT=./test/integration/scheduler_perf ETCD_LOGLEVEL=warn KUBE_TEST_VMODULE="''" KUBE_TEST_ARGS="-run=^$$ -benchtime=1ns -bench=BenchmarkPerfScheduling/SchedulingWhileGated/1Node_10000GatedPods"`

I obtained the following results, which show the same trend the PR mentioned, but my tests actually failed. Could you let me know if this outcome is normal at your convenience please?

> QHint enabled master branch vs. this branch : 117 pods/s→ 103pods/s performance decline
> QHint disabled master branch vs. this branch : 92 pods/s → 123 pods/s performance improve

message generated by executing the code above

```
make[1]: *** [Makefile:192: test] Error 1
make[1]: Leaving directory '/home/xie/go/src/k8s.io/kubernetes'
!!! [1018 05:41:12] Call tree:
!!! [1018 05:41:12] 1: hack/make-rules/test-integration.sh:108 runTests(...)
+++ [1018 05:41:12] Cleaning up etcd
+++ [1018 05:41:13] Integration test cleanup complete
make: *** [Makefile:215: test-integration] Error 1
```


### What did you expect to happen?

I’d like to know if this is normal behavior. If it’s not, it should be possible to obtain the correct results without the test failing.

### How can we reproduce it (as minimally and precisely as possible)?

Run the following code under the following four configurations.
`make test-integration WHAT=./test/integration/scheduler_perf ETCD_LOGLEVEL=warn KUBE_TEST_VMODULE="''" KUBE_TEST_ARGS="-run=^$$ -benchtime=1ns -bench=BenchmarkPerfScheduling/SchedulingWhileGated/1Node_10000GatedPods"` 

I conducted four test cases, and I think each test can generate similar results.
1. Master branch, SchedulerQueueingHints Disable
2. Master branch, SchedulerQueueingHints Enable
3. [#127180](https://github.com/kubernetes/kubernetes/pull/127180) PR branch, SchedulerQueueingHints Disable
4. [#127180](https://github.com/kubernetes/kubernetes/pull/127180) PR branch, SchedulerQueueingHints Enable

### Anything else we need to know?

/sig scheduling

### Kubernetes version

<details>

```console
$ kubectl version
# paste output here
```

</details>


### Cloud provider

<details>

</details>


### OS version

<details>

```console
# On Linux:
$ cat /etc/os-release
# paste output here
$ uname -a
# paste output here

# On Windows:
C:\> wmic os get Caption, Version, BuildNumber, OSArchitecture
# paste output here
```

</details>


### Install tools

<details>

</details>


### Container runtime (CRI) and version (if applicable)

<details>

</details>


### Related plugins (CNI, CSI, ...) and versions (if applicable)

<details>

</details>