sharjeelyunus/github-issues-dataset huggingface dataset:
Repository: next.js
Issue: the middleware breaks the locale of dynamic pages on the server side
Labels: bug,Middleware,Internationalization (i18n),linear: next

### Link to the code that reproduces this issue

https://github.com/dartess/nextjs-locale-bug

### To Reproduce

1. Start the application in development (next dev)
2. open `http://localhost:3000/`
3. click to `set de`. the locale will changed to `de`.
4. click to `go to /page/foo`. 

### Current vs. Expected behavior

I expect that the locale on the client and server is still `de`.
But I see that the locale on the client (useRouter) is `de`, and the locale on the server side (getStaticProps) is `en`.

### Provide environment information

```bash
Operating System:
  Platform: darwin
  Arch: arm64
  Version: Darwin Kernel Version 23.2.0: Wed Nov 15 21:53:18 PST 2023; root:xnu-10002.61.3~2/RELEASE_ARM64_T6000
  Available memory (MB): 32768
  Available CPU cores: 10
Binaries:
  Node: 18.18.0
  npm: 9.8.1
  Yarn: 1.22.18
  pnpm: 8.4.0
Relevant Packages:
  next: 14.1.1-canary.74 // Latest available version is detected (14.1.1-canary.74).
  eslint-config-next: N/A
  react: 18.2.0
  react-dom: 18.2.0
  typescript: 5.1.3
Next.js Config:
  output: N/A
```


### Which area(s) are affected? (Select all that apply)

Internationalization (i18n)

### Which stage(s) are affected? (Select all that apply)

next dev (local), next build (local), next start (local)

### Additional context

The problem appears only when there is a transition to a dynamic page and only when the project has a `middleware.ts` file (with any content; in the repl there is a file from the documentation).

<sub>[NEXT-2618](https://linear.app/vercel/issue/NEXT-2618/the-middleware-breaks-the-locale-of-dynamic-pages-on-the-server-side)</sub>
Repository: PowerToys
Issue: remapping key error
Labels: Issue-Bug,Product-Keyboard Shortcut Manager,Needs-Triage

### Microsoft PowerToys version

0.78.0

### Installation method

Microsoft Store

### Running as admin

No

### Area(s) with issue?

Keyboard Manager

### Steps to reproduce

Create a key remapping sequence to send text

### ✔️ Expected Behavior

Text should appear immediately when remapped key is selected 

### ❌ Actual Behavior

defined text appears very slowly - longer than the time needed to type out the text manually from the keyboard 

### Other Software

none
Repository: pytorch
Issue: Tracing UpSample get RuntimeError when use_determinitic_algorithms=True
Labels: oncall: jit,triaged,module: determinism

### 🐛 Describe the bug

when using deterministic algorithms, tracing Upsample layer will raise RuntimeError, saying ```RuntimeError: Expected all tensors to be on the same device, but found at least two devices, cuda:0 and cpu! (when checking argument for argument max in method wrapper_CUDA_clamp_Tensor)```. The example can reproduce this error.

```python

import torch
torch.use_deterministic_algorithms(True)

x = torch.zeros(
    size=(1, 3, 8, 8),
    device="cuda",
)
model = torch.nn.Upsample(scale_factor=2, mode="bilinear", align_corners=False)
model = model.cuda()
model.eval()

torch.jit.trace(model, x)
```

What I found is that in `torch._decomp.decompositions.py` at [line 3024@v2.1.1](https://github.com/pytorch/pytorch/blob/v2.1.1/torch/_decomp/decompositions.py#L3024), [line 3316@v2.2.1](https://github.com/pytorch/pytorch/blob/v2.2.1/torch/_decomp/decompositions.py#L3316) upsample_bilinear2d, it called `x_ceil = torch.ceil(x).clamp(max=in_h - 1).to(torch.int64)`, since `input.shape` return torch.Tensor in cpu, instead of a type int, it causes operating two tensor in different devices.


### Additional Context
* https://discuss.pytorch.org/t/x-shape-or-x-size-return-torch-size-with-elements-of-type-tensor/153136

### Versions

PyTorch version: 2.1.1+cu121
Is debug build: False
CUDA used to build PyTorch: 12.1
ROCM used to build PyTorch: N/A

OS: Microsoft Windows 11 Enterprise
GCC version: Could not collect
Clang version: Could not collect
CMake version: version 3.27.7
Libc version: N/A

Python version: 3.8.10 (tags/v3.8.10:3d8993a, May  3 2021, 11:48:03) [MSC v.1928 64 bit (AMD64)] (64-bit runtime)
Python platform: Windows-10-10.0.22631-SP0
Is CUDA available: True
CUDA runtime version: 11.3.109
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration: GPU 0: NVIDIA GeForce RTX 3070 Ti Laptop GPU
Nvidia driver version: 546.17
cuDNN version: C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.3\bin\cudnn_ops_train64_8.dll
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True

CPU:


Revision=17409

Versions of relevant libraries:
[pip3] mypy==1.4.1
[pip3] mypy-extensions==1.0.0
[pip3] numpy==1.22.3
[pip3] onnx==1.11.0
[pip3] onnxruntime-gpu==1.11.0
[pip3] pytorch-lightning==2.1.2
[pip3] torch==2.1.1+cu121
[pip3] torch-tb-profiler==0.4.3
[pip3] torchmetrics==1.3.1
[pip3] torchvision==0.16.1+cu121
[conda] Could not collect

cc @EikanWang @jgong5 @wenzhe-nrv @sanchitintel @mruberry @kurtamohler @jbschlosser @walterddr @mikaylagawarecki
Repository: pytorch
Issue: DISABLED test_is_isnot (__main__.TestScript)
Labels: oncall: jit,triaged,module: flaky-tests,skipped,oncall: pt2,module: dynamo

Platforms: dynamo

This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_is_isnot&suite=TestScript&limit=100) and the most recent trunk [workflow logs](https://github.com/pytorch/pytorch/runs/22012844685).

Over the past 3 hours, it has been determined flaky in 3 workflow(s) with 3 failures and 3 successes.

**Debugging instructions (after clicking on the recent samples link):**
DO NOT ASSUME THINGS ARE OKAY IF THE CI IS GREEN. We now shield flaky tests from developers so CI will thus be green but it will be harder to parse the logs.
To find relevant log snippets:
1. Click on the workflow logs linked above
2. Click on the Test step of the job so that it is expanded. Otherwise, the grepping will not work.
3. Grep for `test_is_isnot`
4. There should be several instances run (as flaky tests are rerun in CI) from which you can study the logs.


Test file path: `test_jit.py`

cc @EikanWang @jgong5 @wenzhe-nrv @sanchitintel @clee2000 @wdvr @chauhang @penguinwu @voznesenskym @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @jiayisunx @chenyang78 @kadeng @amjames @ezyang @msaroufim @bdhirsh @anijain2305 @zou3519
Repository: excalidraw
Issue: Fat Arrows out of the box
Labels: enhancement

There's just something about them...

![fat-arrow](https://github.com/excalidraw/excalidraw/assets/490201/10ee5b94-fec5-4c07-913a-a7d87bd3d1b7)

sure you can draw them by hand with the line tool, but they turn out a bit weird with odd proportions
also it's a very common shape so there should be an easier way to do it (is it really less common than diamond shape?)

Huge fan of Excalidraw, use it all the time with great success.
Repository: rust
Issue: Trait bounds on associated types are not commuted to the rigid types when projection predicates are in environment
Labels: A-trait-system,A-associated-items,C-bug,S-blocked,T-types

<!--
Thank you for filing a bug report! 🐛 Please provide a short summary of the bug,
along with any information you feel relevant to replicating the bug.
-->
cc @compiler-errors 
I tried this code:

```rust
trait Foo {
    type Bar: Qux;
}

trait Qux {
    fn hello();
}

fn doesnt_work<T: Foo<Bar = U>, U>() {
    T::Bar::hello(); // <~ `T::Bar` becomes `U`, for which we know nothing.
}

fn works<T: Foo>() {
    T::Bar::hello();
}
```

I expected to see this happen: this should pass type check.

Instead, this happened: since `T::Bar` is normalised to just `U`, but there is no facts about `U` except the projection predicate which is not used yet.

```
error[E0599]: no function or associated item named `hello` found for type parameter `U` in the current scope
  --> src/lib.rs:10:13
   |
9  | fn doesnt_work<U, T: Foo<Bar = U>>() {
   |                - function or associated item `hello` not found for this type parameter
10 |     T::Bar::hello();
   |             ^^^^^ function or associated item not found in `U`
   |
   = help: items from traits can only be used if the type parameter is bounded by the trait
help: the following trait defines an item `hello`, perhaps you need to restrict type parameter `U` with it:
   |
9  | fn doesnt_work<U: Qux, T: Foo<Bar = U>>() {
   |                 +++++

For more information about this error, try `rustc --explain E0599`.
```

### Meta
<!--
If you're using the stable version of the compiler, you should also check if the
bug also exists in the beta or nightly versions.
-->

It is known to be the case for a while including nightly and stable as of writing.

<!--
Include a backtrace in the code block by setting `RUST_BACKTRACE=1` in your
environment. E.g. `RUST_BACKTRACE=1 cargo build`.
-->
<details><summary>Backtrace</summary>
<p>

```
// Not an ICE
```

</p>
</details>
Repository: godot
Issue: Exporting with translations breaks the first time
Labels: bug,topic:export

### Tested versions

v4.2.1.stable.official [b09f793f5]

### System information

Windows 10, Godot 4.2.1

### Issue description

We recently added translation files to our project and this broke our CI/CD workflow. The generated pck or zip file would not include 90% of our non text assets. Upon further investigation it turns out that when adding (csv) translations it seems it is required to export the project **twice**. The first time will just create the packfile with only the .remap files and create the .godot folder. The second time it would work as expected. I also noticed that the first export takes considerable time for engine shutdown/cleanup and leaks a lot of resources. The console text is also broken with the cursor being a couple lines above the last output print (for both exports)

Also of note: before applying this fix here #88868, the second export would always segfault (for our full project not the attached MRP)

first export:
![grafik](https://github.com/godotengine/godot/assets/11277588/9fcb248f-a5af-451b-82f0-e9caa7a46418)
![grafik](https://github.com/godotengine/godot/assets/11277588/fe87b4b1-f409-40e2-99b5-b740d2d36024)

second export:
![grafik](https://github.com/godotengine/godot/assets/11277588/064e2d33-3fc1-4274-8aa9-63ff79b6835f)


### Steps to reproduce

1. download the attached project
2. export with `godot.exe -e --export-pack windows test.zip --headless`
3. resulting zip file will be missing all textures and meshes and be around 550kb
4. export again with `godot.exe -e --export-pack windows test.zip --headless`
5. resulting zip file will be around 22mb

### Minimal reproduction project (MRP)

[mrp.zip](https://github.com/godotengine/godot/files/14416107/mrp.zip)
Repository: storybook
Issue: [Bug]: Submit in Svelte project using sveltekit-superforms is not working
Labels: bug,help wanted,compatibility with other tools,svelte,sveltekit,sev:S3

### Describe the bug

When I click the submit button, nothing happens if my form is using `use:enhance` from `sveltekit-superforms`.

A form without `use:enhance` seems to work great.

https://github.com/storybookjs/storybook/assets/9967422/beda05ef-f2a3-402c-8cd0-c71b0e684ce6


**Button.svelte**
```svelte
<script lang="ts">
  import './button.css';
	import { defaults, superForm } from 'sveltekit-superforms';
	import { userSchema } from './schema';
	import { zod } from 'sveltekit-superforms/adapters';

  const formData = defaults({name: 'some name'}, zod(userSchema));

  const spForm = superForm(formData, {
    onSubmit: (data) => {
      console.log('Form submitted', data);
    }
  })
  const {enhance} = spForm;

  let formElement: HTMLFormElement;
</script>

<form id="form-1" use:enhance method="POST">
  <input type="text" name="name" value="Some text"/>
  <button>Submit form with use:enhance</button> <!-- Nothing seems to happen -->
</form>

<form id="form-2" method="POST" style="margin-top: 20px;" bind:this={formElement}>
  <input type="text" name="name" value="Some text"/>
  <button>Submit form, no enhance</button> <!-- can submit -->
</form>

<button type="button" on:click={() => formElement.requestSubmit()}>Submit form, no enhance also works</button>

```


### To Reproduce

Clone the [repo](https://github.com/21RISK/storybook-submit-not-working), `npm run storybook` and visit the `Button.svelte` story.

### System

```bash
System:
    OS: macOS 14.3.1
    CPU: (10) arm64 Apple M1 Max
    Shell: 5.9 - /bin/zsh
  Binaries:
    Node: 18.17.1 - ~/.nvm/versions/node/v18.17.1/bin/node
    npm: 10.2.5 - ~/.nvm/versions/node/v18.17.1/bin/npm <----- active
    pnpm: 8.12.0 - ~/.nvm/versions/node/v18.17.1/bin/pnpm
  Browsers:
    Chrome: 122.0.6261.69
    Safari: 17.3.1
  npmPackages:
    @storybook/addon-essentials: ^7.6.17 => 7.6.17 
    @storybook/addon-interactions: ^7.6.17 => 7.6.17 
    @storybook/addon-links: ^7.6.17 => 7.6.17 
    @storybook/blocks: ^7.6.17 => 7.6.17 
    @storybook/svelte: ^7.6.17 => 7.6.17 
    @storybook/sveltekit: ^7.6.17 => 7.6.17 
    @storybook/test: ^7.6.17 => 7.6.17 
    eslint-plugin-storybook: ^0.8.0 => 0.8.0 
    storybook: ^7.6.17 => 7.6.17 
```
```


### Additional context

My end-goal is to mock submit requests from sveltekit-superforms with the mock service worker plugin, and test my different states of form components.
Repository: kubernetes
Issue: Support endpoint authentication for K8s trace configuration
Labels: kind/feature,sig/instrumentation,triage/accepted

### What would you like to be added?

So far, grpc format endpoint is supported for K8s trace configuration.
If user wants to use an authentication for trace, it is not feasible.
I want to support grpc authentication for trace configuration.

### Why is this needed?

Only grpc without authentication for trace config is not enough, we need to support
grpc authentication for trace
Repository: pytorch
Issue: Invert the model architecture from the unknown neural network model (the python object of the model)
Labels: feature,module: nn,triaged,needs research

### 🚀 The feature, motivation and pitch

Invert the model architecture from the unknown neural network model (the python object of the model)
I am doing a research on NAS. This new function will make me easier to encode certain model.

### Alternatives

_No response_

### Additional context

_No response_

cc @albanD @mruberry @jbschlosser @walterddr @mikaylagawarecki
Repository: tensorflow
Issue: `tf.raw_ops.DecodeAndCropJpeg`: Assertion failure in shape inference step
Labels: awaiting review,type:bug,comp:ops,comp:core

### Issue type

Bug

### Have you reproduced the bug with TensorFlow Nightly?

Yes

### Source

source

### TensorFlow version

tf 2.17

### Custom code

Yes

### OS platform and distribution

Linux Ubuntu 22.04 LTS

### Mobile device

_No response_

### Python version

3.11.7

### Bazel version

6.5.0

### GCC/compiler version

clang 16

### CUDA/cuDNN version

_No response_

### GPU model and memory

_No response_

### Current behavior?

`tf.raw_ops.DecodeAndCropJpeg` can lead to assertion failure in shape inference step.
Error location is [here](https://github.com/tensorflow/tensorflow/blob/daea84aad67d1fcc8d58c648e1da58ee576445f9/tensorflow/core/ops/image_ops.cc#L523):
```C++
       w = c->MakeDim(crop_window_vec(3));
```
It makes a dim from an input argument without checking negativity.
In debug build, it ends up with assertion failure in [a constructor of`DimensionOrConstant`](https://github.com/tensorflow/tensorflow/blob/daea84aad67d1fcc8d58c648e1da58ee576445f9/tensorflow/core/framework/shape_inference.h#L891-L896).

### Standalone code to reproduce the issue

```Python
import tensorflow as tf

tf.compat.v1.disable_eager_execution()

tf.raw_ops.DecodeAndCropJpeg(
    contents="abc",
    crop_window=[0,0,0,-2],
    channels=0,
    ratio=1,
    fancy_upscaling=True,
    try_recover_truncated=False,
    acceptable_fraction=1,
    dct_method='',
    name=None
)
```


### Relevant log output

Release build: Outputs nothing

Debug build:
```shell
2024-02-27 18:41:59.133420: F ./tensorflow/core/framework/shape_inference.h:891] Check failed: val >= 0 || val == InferenceContext::kUnknownDim Dimension must be non-negative or equal to InferenceContext::kUnknownDim but got -2
Aborted (core dumped)
```
Repository: vscode
Issue: Warning tooltips hidden behind bottom panel
Labels: bug,settings-editor,confirmed

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> Last https://vscode.dev/ in chrome
Version: 1.86.2
Commit: 903b1e9d8990623e3d7da1df3d33db3e42d80eda
Date: 2024-02-13T19:42:42.858Z (1 wk ago)
Browser: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/121.0.0.0 Safari/537.36

Steps to Reproduce:
1. Any setting with warning that lays at the bottom of the scrolling region.
2. The warning is hidden behind bottom panels:

![image](https://github.com/microsoft/vscode/assets/26868611/f126916f-02ab-4218-825c-d684aac106af)

FIX:
- Seem like the simplest fix would be to just leave an empty space at the bottom of the scrolling region, at least the size of the max tooltip height.
- But then the user is required to scroll manually an extra amount to see it, therefore I guess the best solution is to make warnings overlay any other panel (potential side effects?)
Repository: puppeteer
Issue: [Bug]: Failed to open many pages with the '--incognito' property
Labels: bug,upstream,confirmed,P3

### Minimal, reproducible example

```TypeScript
const puppeteer = require('puppeteer');

(async () => {
  const browser = await puppeteer.launch({
    headless: false, // 是否为无头模式，这里设置为false便于观察
    args: ['--incognito'], // 启用无痕模式
  });

  const page = await browser.newPage();
  await page.goto('https://www.google.com/');

  // ... 其他操作

  // await browser.close(); // 最后记得关闭浏览器实例
})();
```


### Error string

Two browser Windows open

### Bug behavior

- [X] Flaky
- [ ] PDF

### Background

I am looking to open multiple pages in an incognito browser window. However, after using the `puppeteer.launch({args: ['--incognito']})` method to launch an incognito browser, when I create a new page with `browser.newPage()` and subsequently execute the `goto` method to navigate to the target URL, the outcome is that two separate browser windows are opened - one incognito and one non-incognito - with the target URL being loaded in the non-incognito browser. The actual effect and a screenshot of the code are presented below.
<img width="1194" alt="image" src="https://github.com/puppeteer/puppeteer/assets/144797635/7c92123b-7e94-4bf4-9d57-1f1011ced357">
<img width="557" alt="image" src="https://github.com/puppeteer/puppeteer/assets/144797635/5721d262-64aa-4efc-9aa9-68a290ae0f74">


### Expectation

Expect the target URL to open as a TAB in the incognito browser each time the goto method is executed, inheriting the browser's incognito mode.

### Reality

As mentioned above

### Puppeteer configuration file (if used)

_No response_

### Puppeteer version

v22.0.0

### Node version

v20.10.0

### Package manager

npm

### Package manager version

10.2.3

### Operating system

macOS
Repository: tensorflow
Issue: `tf.raw_ops.ExtractGlimpse`: Assertion failure in shape inference step
Labels: awaiting review,type:bug,comp:ops,comp:core

### Issue type

Bug

### Have you reproduced the bug with TensorFlow Nightly?

Yes

### Source

source

### TensorFlow version

tf 2.17

### Custom code

Yes

### OS platform and distribution

Linux Ubuntu 22.04 LTS

### Mobile device

_No response_

### Python version

3.11.7

### Bazel version

6.5.0

### GCC/compiler version

clang 16

### CUDA/cuDNN version

_No response_

### GPU model and memory

_No response_

### Current behavior?

`tf.raw_ops.ExtractGlimpse` can lead to assertion failure in shape inference step.
Error location is [here](https://github.com/tensorflow/tensorflow/blob/daea84aad67d1fcc8d58c648e1da58ee576445f9/tensorflow/core/ops/image_ops.cc#L57):
```C++
    height = c->MakeDim(vec(0));
```
It makes a dim from input argument without checking negativity.
In debug build, it ends up with assertion failure in [a constructor of `DimensionOrConstant`](https://github.com/tensorflow/tensorflow/blob/daea84aad67d1fcc8d58c648e1da58ee576445f9/tensorflow/core/framework/shape_inference.h#L891-L896).

### Standalone code to reproduce the issue

```Python
import tensorflow as tf

tf.compat.v1.disable_eager_execution()

tf.raw_ops.ExtractGlimpse(
    input=tf.random.normal([1,1,1,1]),
    size=[-2,-2],
    offsets=tf.random.normal([1,2]),
    centered=True,
    normalized=True,
    uniform_noise=True,
    noise='uniform',
    name=None
)
```


### Relevant log output

Release build: Outputs nothing

Debug build:
```shell
2024-02-27 19:02:16.866010: F ./tensorflow/core/framework/shape_inference.h:891] Check failed: val >= 0 || val == InferenceContext::kUnknownDim Dimension must be non-negative or equal to InferenceContext::kUnknownDim but got -2
Aborted (core dumped)
```
Repository: go
Issue: proposal: log/slog: add multiple handlers support for logger
Labels: Proposal

### Proposal Details

Currently slog package a logger only support one handler. 
For most language like python, A log module should be sent to multiple targets for output simultaneously for a logger. This feature is necessary， I propose adding multiple handlers support for logger.
cc @golang/proposal-review
Repository: material-ui
Issue: [material-ui][Rating] `arrowUp` and `arrowDown` are reversed
Labels: accessibility,package: material-ui,component: rating,status: expected behavior

### Steps to reproduce

Link to live example: [Basic Rating](https://mui.com/material-ui/react-rating/#basic-rating)

Steps:
1. tab into the rating
2. press arrow up/down
3. value setting is reversed



### Current behavior

`arrowUp` decreases value
`arrowDown` increases value


### Expected behavior

`arrowUp` increases value
`arrowDown` decreases value


### Context

_No response_

### Your environment

_No response_

**Search keywords**: rating arrow up down value
Repository: pytorch
Issue: FSDP First iteration takes very long
Labels: triaged,actionable,module: fsdp

### 🐛 Describe the bug

When running training with `fsdp` strategy in lightning on hundreds of GPUs, the first iteration takes extremely long (minutes...)

The culprit are these two N^2 checks
https://github.com/pytorch/pytorch/blob/a8e7c98cb95ff97bb30a728c6b2a1ce6bff946eb/torch/distributed/fsdp/_exec_order_utils.py#L221-L235
https://github.com/pytorch/pytorch/blob/a8e7c98cb95ff97bb30a728c6b2a1ce6bff946eb/torch/distributed/fsdp/_exec_order_utils.py#L246-L271

There does not seem to be an easy workaround (except going into the file and disabling the check for the first iteration)


### Versions

observed with 2.1.2 

cc @zhaojuanmao @mrshenli @rohan-varma @awgu @fegin @penguinwu @kwen2501