sharjeelyunus/github-issues-dataset huggingface dataset:
Repository: pytorch
Issue: Cannot compile torch 1.10 in CentOS 7.3
Labels: triaged

### 🐛 Describe the bug

I tried to compile PyTorch 1.10 on CentOS, but after configuring the system environment, I always got compilation errors as follows. I found that the gcc version was incorrect and could not be upgraded on CentOS. How can I solve this?

![image](https://user-images.githubusercontent.com/73052387/233765855-9ad9cb96-ee85-41a8-829e-2bd4aeec9d37.png)


### Versions

PyTorch version: 1.10.1
Is debug build: False
CUDA used to build PyTorch: 10.2
ROCM used to build PyTorch: N/A

OS: CentOS Linux 7 (Core) (x86_64)
GCC version: (conda-forge gcc 12.2.0-19) 12.2.0
Clang version: Could not collect
CMake version: version 3.22.1
Libc version: glibc-2.17

Python version: 3.9.16 (main, Mar  8 2023, 14:00:05)  [GCC 11.2.0] (64-bit runtime)
Python platform: Linux-3.10.0-514.el7.x86_64-x86_64-with-glibc2.17
Is CUDA available: True
CUDA runtime version: 10.2.89
CUDA_MODULE_LOADING set to: 
GPU models and configuration: GPU 0: Tesla T4
Nvidia driver version: 440.33.01
cuDNN version: Could not collect
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True

CPU:
Architecture:          x86_64
CPU op-mode(s):        32-bit, 64-bit
Byte Order:            Little Endian
CPU(s):                12
On-line CPU(s) list:   0-11
Thread(s) per core:    2
Core(s) per socket:    6
座：                 1
NUMA 节点：         1
厂商 ID：           GenuineIntel
CPU 系列：          6
型号：              158
型号名称：        Intel(R) Core(TM) i7-8700 CPU @ 3.20GHz
步进：              10
CPU MHz：             3155.250
BogoMIPS：            6400.00
虚拟化：           VT-x
L1d 缓存：          32K
L1i 缓存：          32K
L2 缓存：           256K
L3 缓存：           12288K
NUMA 节点0 CPU：    0-11

Versions of relevant libraries:
[pip3] numpy==1.23.5
[pip3] torch==1.10.1
[pip3] torchaudio==0.10.1
[pip3] torchvision==0.11.2
[conda] blas                      1.0                         mkl  
[conda] cudatoolkit               10.2.89              hfd86e86_1  
[conda] ffmpeg                    4.3                  hf484d3e_0    pytorch
[conda] mkl                       2021.4.0           h06a4308_640  
[conda] mkl-include               2023.1.0         h06a4308_46342  
[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                   1.10.1          py3.9_cuda10.2_cudnn7.6.5_0    pytorch
[conda] pytorch-mutex             1.0                        cuda    pytorch
[conda] torchaudio                0.10.1               py39_cu102    pytorch
[conda] torchvision               0.11.2               py39_cu102    pytorch
Repository: tauri
Issue: [bug] Cannot build app on Apple M1
Labels: type: bug,platform: macOS,status: needs triage

### Describe the bug

I simply ran `cargo tauri build`.

The build process itself succeeded, but the bundling of the binary failed. 

```
    Bundling splitfire.ai.app (/Users/myhome/splitfire-desktop/src-tauri/target/release/bundle/macos/splitfire.ai.app)
       Error failed to bundle project: Failed to copy binary from "/Users/myhome/splitfire-desktop/src-tauri/target/release/splitfire.ai": Failed to copy binary from "/Users/myhome/splitfire-desktop/src-tauri/target/release/splitfire.ai": `"/Users/myhome/splitfire-desktop/src-tauri/target/release/splitfire.ai" does not exist`
```

It seems like it wrongly refers the binary folder when trying to bundle the app.

I tried the` --target universal-apple-darwin`. The same error happened.

It's an existing React app that I integrated with Tauri with the official documentation tutorials. Any clue? 

### Reproduction

_No response_

### Expected behavior

Build and bundle the project successfully.

### Platform and versions

```text
MacBook Pro
MacOS Ventura 13.2.1 (22D68)
Apple M1 Pro
```


### Stack trace

_No response_

### Additional context

_No response_
Repository: rust
Issue: Tracking Issue for builtin # syntax
Labels: C-tracking-issue

This is a tracking issue for the MCP to add `builtin #` syntax, see https://github.com/rust-lang/compiler-team/issues/580 as well as the zulip [stream](https://rust-lang.zulipchat.com/#narrow/stream/233931-xxx/topic/Add.20builtin.23.20for.20compiler-intrinsic.20syntax.20compiler-team.23580).
The feature gate for the issue is `#![feature(builtin_syntax)]`.

### About tracking issues

Tracking issues are used to record the overall progress of implementation.
They are also used as hubs connecting to other relevant issues, e.g., bugs or open design questions.
A tracking issue is however *not* meant for large scale discussion, questions, or bug reports about a feature.
Instead, open a dedicated issue for the specific matter and add the relevant feature gate label.

### Steps

- [x] Implement a scaffolding for the `builtin #` syntax: #110694
- [ ] Adopt `builtin #` syntax in the qualifying places:
  - [x] `offset_of!`: #110694
  - [x] `type_ascribe!`: #122806
  - [x] `deref!(PAT)` #122793
  - [ ] `asm!`/`global_asm!`
  - [ ] `format_args!`
  - [ ] (the list is incomplete)
- There will never be a general stabilization. The sub-syntaxes should be exposed stably in other ways to end users, for example through macros. Alternatively, the syntax should be changed before stabilization to something that doesn't use `builtin #`. In any way, stabilization is specific to each feature that uses `builtin #`.
  
### Unresolved Questions

The MCP lists a few potential use cases for `builtin #`, but the list is not final (and probably will keep changing).

### Implementation history

* #110694
Repository: godot
Issue: Noise in shaders does not work correctly on new NVIDIA graphics cards.
Labels: bug,topic:rendering,confirmed,documentation,topic:thirdparty,topic:shaders

### Godot version

4,02 stable

### System information

Windows 10, GTX 1050, forward+

### Issue description

I am working on a sky shader and everything works correctly on my computer with an old video card. However, users of the new series of video cards (4070 like) complain that the shader does not work. It was found out that it is the noise function that does not work correctly. Moreover, I used fundamentally different noise functions, but all of them not work.

I get this correct result from the noise.
![image](https://user-images.githubusercontent.com/48552343/233779515-224b7305-7eaa-4706-9e09-20e7172aa380.png)
But users of new video cards get this.
![image](https://user-images.githubusercontent.com/48552343/233779626-d172e506-dc67-4283-9eda-9b977ba6cc85.png)

Everything is complicated by the fact that I do not have a modern video card for tests. And since everything works for me, I can't figure out the reason.

It's very similar to this error https://github.com/godotengine/godot/issues/67150,
BUT **I don't use the sin function in noise**.

### Steps to reproduce

There are two types of noise - texture-based and procedural. Both work correctly on older video cards. And both don't work on the new ones. For procedural noise, just uncomment the last line in the shader.

### Minimal reproduction project

[noise glitch.zip](https://github.com/godotengine/godot/files/11301144/noise.glitch.zip)
Repository: next.js
Issue: [NEXT-1183] compress: false and middleware causes blank page in development
Labels: bug,Runtime,linear: next

### Verify canary release

- [X] I verified that the issue exists in the latest Next.js canary release

### Provide environment information

```bash
Operating System:
      Platform: darwin
      Arch: x64
      Version: Darwin Kernel Version 21.6.0: Mon Dec 19 20:44:01 PST 2022; root:xnu-8020.240.18~2/RELEASE_X86_64
    Binaries:
      Node: 16.19.0
      npm: 8.19.3
      Yarn: 1.22.19
      pnpm: N/A
    Relevant packages:
      next: 13.3.1-canary.19
      eslint-config-next: 13.3.0
      react: 18.2.0
      react-dom: 18.2.0
```


### Which area(s) of Next.js are affected? (leave empty if unsure)

Middleware / Edge (API routes, runtime)

### Link to the code that reproduces this issue

https://github.com/dottodot/next-compress-middleware

### To Reproduce

run yarn dev and you'll see you get a blank page
remove compress: false and the app loads correctly

### Describe the Bug

When compress: false is set in next.config and middleware.ts is added in the route the app will load blank, however it's fine after running build

### Expected Behavior

compress should not have an impact on middleware.

### Which browser are you using? (if relevant)

_No response_

### How are you deploying your application? (if relevant)

_No response_

<sub>[NEXT-1183](https://linear.app/vercel/issue/NEXT-1183/compress-false-and-middleware-causes-blank-page-in-development)</sub>
Repository: storybook
Issue: [Bug]: Addon being forced to use React v16.14.0 in storybook 7 (v18 worked in 6)
Labels: bug,has workaround,builder-manager

### Describe the bug

In previous versions of storybook the `import React from "react"` in my register.tsx would find version 18 as expected, but now it seems to be given `v16.14.0`.

https://github.com/neil-morrison44/storybook-addon-recoil-flow/blob/073490700fdca76c24593d6e4009238426b53777/src/register.tsx#L6

v16 doesn't appear at all when doing `npm list react` (all `react@18.2.0`) so I'm really not sure where it's coming from (I know storybook pre-bundles itself now so I'm guessing it could be that?)

I've tried using esbuild to pre-bundle my addon but I get `Rule of Hooks` warnings about different versions of React (which makes sense, I guess)

I'm using `react-three-fiber` which needs to use React 18 features (`useId` is the first one it'll error on)

Thanks

### To Reproduce

The storybook can be found in my draft PR for updating to storybook 7: https://github.com/neil-morrison44/storybook-addon-recoil-flow/pull/4 (it's pretty much a new storybook + the addon)

Though, if I do manage to find a workaround in the interim you'll want the one from this commit: https://github.com/neil-morrison44/storybook-addon-recoil-flow/tree/073490700fdca76c24593d6e4009238426b53777

### System

```shell
Environment Info:

  System:
    OS: macOS 13.3.1
    CPU: (10) arm64 Apple M1 Pro
  Binaries:
    Node: 16.13.0 - /usr/local/bin/node
    Yarn: 1.22.17 - /usr/local/bin/yarn
    npm: 8.1.0 - /usr/local/bin/npm
  Browsers:
    Chrome: 112.0.5615.137
    Firefox: 109.0.1
    Safari: 16.4
  npmPackages:
    @storybook/addon-actions: ^7.0.6 => 7.0.6 
    @storybook/addon-essentials: ^7.0.6 => 7.0.6 
    @storybook/addon-interactions: ^7.0.6 => 7.0.6 
    @storybook/addon-links: ^7.0.6 => 7.0.6 
    @storybook/cli: ^7.0.6 => 7.0.6 
    @storybook/react: ^7.0.6 => 7.0.6 
    @storybook/react-webpack5: ^7.0.6 => 7.0.6 
    @storybook/testing-library: ^0.1.0 => 0.1.0 
```


### Additional context

https://github.com/neil-morrison44/storybook-addon-recoil-flow/pull/4 (PR link again, if I happen upon a workaround it'll be there)
Repository: PowerToys
Issue: Enhancement Request: Find Mouse only using one monitor when multiple monitors are connected but not all of them are in user view
Labels: Needs-Triage

### Description of the new feature / enhancement

Mouse jump dialog doesn't appear on all monitors, so if you lost your mouse and are looking a monitor A (and it is not on monitor A) you still can't find your mouse!  I think it would be better if mousejump appeared on all montiors the the same time and/or/both Mouse Pointer Crosshairs could be enhanced to also show on all monitor with arrows across monitors that show where the mouse is compared if on another monitor.

I ask because I use my TV and can't see other monitors while I am using that and I lose my mouse frequency and I have to wildly shake my air mouse until it randomly appears on my TV to find it.  None of the power tools mouse apps help with that right now when I have to find my mouse and am only looking at one monitor to find it.

### Scenario when this would be used?

I ask because I use my TV and can't see other monitors while I am using that and I lose my mouse frequency and I have to wildly shake my air mouse until it randomly appears on my TV to find it.  None of the power tools mouse apps help with that right now when I have to find my mouse and am only looking at one monitor to find it.

### Supporting information

n/a
Repository: next.js
Issue: [AppDir] generateStaticParams triggers server components twice
Labels: bug

### Verify canary release

- [X] I verified that the issue exists in the latest Next.js canary release

### Provide environment information

```bash
Operating System:
      Platform: win32
      Arch: x64
      Version: Windows 10 Home
    Binaries:
      Node: 18.13.0
      npm: N/A
      Yarn: N/A
      pnpm: N/A
    Relevant packages:
      next: 13.3.1-canary.5
      eslint-config-next: 13.1.0
      react: 18.2.0
      react-dom: 18.2.0
```


### Which area(s) of Next.js are affected? (leave empty if unsure)

AppDir

### Link to the code that reproduces this issue

https://github.com/knenkne/next-generate-static-params-bug-example

### To Reproduce

1. Run `npm run build`
2. Check out console logs (each `id` is called twice)
![image](https://user-images.githubusercontent.com/35743791/233793334-be590cea-5187-4f89-8b93-de2d7ca728f1.png)


### Describe the Bug

Pages with `isr` or `ssg` are rendering twice, lead to poor performance and side effects.

### Expected Behavior

Pages are rendering once.

### Which browser are you using? (if relevant)

_No response_

### How are you deploying your application? (if relevant)

_No response_
Repository: TypeScript
Issue: Create subtype reduction rules for assertion functions
Labels: Suggestion,Experimentation Needed

# Bug Report

<!--
  Please fill in each section completely. Thank you!
-->

### 🔎 Search Terms

inference assert

### 🕗 Version & Regression Information

- This is the behavior in every version I tried, and I reviewed the FAQ for entries about [Common "Bugs" That Aren't Bugs](https://github.com/Microsoft/TypeScript/wiki/FAQ#common-bugs-that-arent-bugs)

### ⏯ Playground Link

[Playground link with relevant code](https://www.typescriptlang.org/play?ts=5.1.0-dev.20230422#code/GYVwdgxgLglg9mABAFQKYGcoB4AajUAeUqYAJuogIZgCeAfABQAOlATpQLboBciOA2gF0AlIgDeAXwCwAKFCRYCFBigAmLAEkwABTacKhYmQqtUlUggA2NKrSGMW7Lry26n6UZNmz50eEmAARgZKXmoaYV4wEA4AI1RWcVMoEFYkQOk5cD8lYFUQsNpIxExWGDAAcyTUFLTEACJS8or6zN9FAIBmAtsI6tqkMQBrXgzMn2yOqmDQ3uLKdHQEqApKRBgKaLiE8TbJ-yp82fD5xeXV9Yomyt2JhQPKbuOisLPWFapL8RHELfjWCS3GSyCAITBUGDAADuqEQAF5EPwggAaRB5VHATqCWRoTAMJGBDGqDFY4Q4lT4yiEw6ox4icmYfIEokk+kyXFqSnUyjEqikoA)

### 💻 Code

<!-- Please post the relevant code sample here as well-->
```ts
function Test<X extends any>(params: X[]) {}
function Test2<InParams extends readonly any[]>(params: InParams) {}

function f1(a: any): number {return 1}
function f2(a: any): string {return "string"}
function f3(a: any) {return {k: 1}}

function a1(a: any): asserts a is number {}
function a2(a: any): asserts a is string {}
function a3(a: any): asserts a is {k: number} {}

const aifwe = [f1, f2, f3]
Test([f1, f2, f3])
Test([a1, a2, a3])
Test2([f1, f2, f3])
Test2([a1, a2, a3])
```

### 🙁 Actual behavior

The Test and Test2 calls are inferred as (in order):

* `function Test<((a: any) => number) | ((a: any) => string) | ((a: any) => {
    k: number;
})>(params: (((a: any) => number) | ((a: any) => string) | ((a: any) => {
    k: number;
}))[]): void`
* `function Test<(a: any) => asserts a is number>(params: ((a: any) => asserts a is number)[]): void`
* `function Test2<(((a: any) => number) | ((a: any) => string) | ((a: any) => {
    k: number;
}))[]>(params: (((a: any) => number) | ((a: any) => string) | ((a: any) => {
    k: number;
}))[]): void`
* `function Test2<((a: any) => asserts a is number)[]>(params: ((a: any) => asserts a is number)[]): void`

### 🙂 Expected behavior

For the assert calls to also be inferred as unions.

This is also irregular since with the wrong inference, I would expect the other functions to be marked as errors, since they have different type signatures.
Repository: rust
Issue: `x build` lives blissfully assuming llvm does not exist
Labels: T-bootstrap,C-bug

When running `x b` I get the following output:
`Warning: no codegen-backends config matched the requested path to build a codegen backend. Help: add backend to codegen-backends in config.toml.`
after building stage1 library artifacts.
for reference here is my `config.toml`:
```
# Includes one of the default files in src/bootstrap/defaults
profile = "compiler"
changelog-seen = 2

[rust]
debug = true
deny-warnings = false
incremental = false
```
cc @jyn514
Repository: electron
Issue: [Feature Request]: Support lock-screen event on Linux
Labels: enhancement :sparkles:,platform/linux,component/powerMonitor

### Preflight Checklist

- [X] I have read the [Contributing Guidelines](https://github.com/electron/electron/blob/main/CONTRIBUTING.md) for this project.
- [X] I agree to follow the [Code of Conduct](https://github.com/electron/electron/blob/main/CODE_OF_CONDUCT.md) that this project adheres to.
- [X] I have searched the [issue tracker](https://www.github.com/electron/electron/issues) for a feature request that matches the one I want to file, without success.

### Problem Description

Currently, the `lock-screen` and `unlock-screen` are not implemented on Linux. The `lock-screen` event in particular would be very benefitial for applications like Bitwarden.

### Proposed Solution

Implement the event(s). For reference, KeepassXC does it like [this](https://github.com/keepassxreboot/keepassxc/blob/develop/src/gui/osutils/nixutils/ScreenLockListenerDBus.cpp)

### Alternatives Considered

There are no alternatives.

### Additional Information

_No response_
Repository: pytorch
Issue: Automatic broadcasting for sparse csr tensors
Labels: module: sparse,triaged

### 🚀 The feature, motivation and pitch

Hey, would it be possible to add broadcasting to sparse csr tensors.


```python
import torch
input = torch.randn(6,6).to_sparse_csr()
bias = torch.tensor([[1,2,0,0,3,2]]).t().to_sparse_csr()
input.to_dense() + bias.to_dense() # working
input + bias.to_dense() # not working
input.to_dense() + bias # not working
input + bias # not working
```



### Alternatives

While elementwise dense matrix multplication/addition broadcasting is supported, it is not supported for sparse (csr) tensors.
Could that be added?

### Additional context

_No response_

cc @alexsamardzic @nikitaved @pearu @cpuhrsch @amjames @bhosmer
Repository: rust
Issue: Missing opt: inlining condition into Option optimizes better, than not inlining
Labels: I-slow,T-compiler,C-bug

Consider two functions, one with if...else out of Option, other one with if...else inlined.
```rust
pub fn foo(x: u8) -> Option<u8> {
    if x < 146 {
        if x > 42 {
            Some(x - 10)
        } else {
            Some(x + 5)
        }
    } else {
        None
    }
}
```

```rust
pub fn foo(x: u8) -> Option<u8> {
    if x < 146 {
        Some(if x > 42 { x - 10 } else { x + 5 })
    } else {
        None
    }
}
```
Expecting that both variants will produce similar asm, but second one actually shorter (and branchless).
Not true for any inlined conditions, some additional calculation on value required to see trigger the difference.
https://rust.godbolt.org/z/3fcnz7coj checked on rustc 1.71.0-nightly (39c6804b9 2023-04-19)

(Probably already existing somewhere, close it that case)

@rustbot label: +I-Slow
Repository: godot
Issue: The fact that `GridMap`s do not have collision until the frame after entering the tree is not documented
Labels: documentation,topic:physics

### Godot version

v4.0.2.stable.official [7a0977ce2]

### System information

Fedora 37

### Issue description

The methods `intersect_ray`, `intersect_point`, and `intersect_shape` from `PhysicsDirectSpaceState3D` do not take `GridMap`s from the scene into consideration, and will not collide.

### Steps to reproduce

1. Try to check for a collision with a GridMap using one of the aforementioned methods.
2. No collision is ever reported.

### Minimal reproduction project

~~[GridmapQueries.zip](https://github.com/godotengine/godot/files/11301948/GridmapQueries.zip)~~

[GridmapQueries.zip](https://github.com/godotengine/godot/files/11301972/GridmapQueries.zip)

**Edit for easier searching:** RayCast, IntersectPoint, IntersectShape, IntersectRay
Repository: tensorflow
Issue: The inferred shape of `tf.RaggedTensor.row_lengths(axis=2)` in Keras graph is incorrect for ragged tensor with uniform row lengths
Labels: stat:awaiting tensorflower,type:bug,comp:keras,comp:ops,TF 2.12

<details><summary>Click to expand!</summary> 
 
 ### Issue Type

Bug

### Have you reproduced the bug with TF nightly?

Yes

### Source

binary

### Tensorflow Version

TF 2.12, TF nightly 2.13.0-dev20230420

### Custom Code

No

### OS Platform and Distribution

_No response_

### Mobile device

_No response_

### Python version

_No response_

### Bazel version

_No response_

### GCC/Compiler version

_No response_

### CUDA/cuDNN version

_No response_

### GPU model and memory

_No response_

### Current Behaviour?

Assume a Keras graph gets a ragged tensor with uniform row lengths in the axis 1, so for example
```python
inputs = tf.keras.layers.Input([64, None], ragged=True)
```

Then `inputs.row_lengths(axis=2)` is a `KerasTensor` with a correct spec `RaggedTensorSpec(TensorShape([None, 64]), ...)`.

However, when you index the first axis using a "full" slice, i.e.
```python
inputs.row_lengths(axis=2)[:]
```
you should get the same tensor -- but you get a `KerasTensor` with an incorrect spec `RaggedTensorSpec(TensorShape([1, 64]), ...)`.

### Standalone code to reproduce the issue

A Colab notebook reproducing the issue both in TF 2.12.0 and in TF nightly 2.13.0-dev20230420 can be found at https://colab.research.google.com/drive/1RKvNdB_81yKZkfzDpefIPJU2pgqZuYUY?usp=sharing

The full source also follows:

```python
inputs = tf.keras.layers.Input([64, None], ragged=True)
print(inputs)

print(inputs.row_lengths(axis=1))
print(inputs.row_lengths(axis=1)[:]) # OK, is the same as above

print(inputs.row_lengths(axis=2))
print(inputs.row_lengths(axis=2)[:]) # Problem, should be the same as above
```


### Relevant log output

```python
KerasTensor(type_spec=RaggedTensorSpec(TensorShape([None, 64, None]), tf.float32, 2, tf.int64), name='input_1', description="created by layer 'input_1'")
KerasTensor(type_spec=TensorSpec(shape=(None,), dtype=tf.int64, name=None), name='input.row_lengths/sub:0', description="created by layer 'input.row_lengths'")
KerasTensor(type_spec=TensorSpec(shape=(None,), dtype=tf.int64, name=None), name='tf.__operators__.getitem/strided_slice:0', description="created by layer 'tf.__operators__.getitem'")
KerasTensor(type_spec=RaggedTensorSpec(TensorShape([None, 64]), tf.int64, 1, tf.int64), description="created by layer 'input.row_lengths_2'")
KerasTensor(type_spec=RaggedTensorSpec(TensorShape([1, 64]), tf.int64, 1, tf.int64), description="created by layer 'tf.__operators__.ragged_getitem'")
```
</details>