sharjeelyunus/github-issues-dataset huggingface dataset:
Repository: go
Issue: x/pkgsite/internal/middleware: TestEnforceQuota failures
Labels: NeedsInvestigation

```
#!watchflakes
default <- pkg == "golang.org/x/pkgsite/internal/middleware" && test == "TestEnforceQuota"
```

Issue created automatically to collect these failures.

Example ([log](https://build.golang.org/log/b98f7a648398e09f25aa266272d37e0853717fb2)):

    2024/04/18 20:56:35 Info: caching response of length 25 for /A
    2024/04/18 20:56:35 Debug: serving "/A" from cache
    2024/04/18 20:56:35 Info: caching response of length 25 for /A
    2024/04/18 20:56:35 Debug: serving "/A" from cache
    2024/04/18 20:56:37 Error: middleware.Panic: panic!
    --- FAIL: TestEnforceQuota (20.90s)
        quota_test.go:84: 4: got false, want true (reason="blocked")


— [watchflakes](https://go.dev/wiki/Watchflakes)
Repository: go
Issue: internal/concurrent: unrecognized failures
Labels: NeedsInvestigation

```
#!watchflakes
default <- pkg == "internal/concurrent" && test == ""
```

Issue created automatically to collect these failures.

Example ([log](https://build.golang.org/log/de5da6e01cb49c36474668dbf271f8ca57a6cfa8)):

    panic: internal/concurrent.HashMapTrie: ran out of hash bits while iterating
    
    goroutine 39 gp=0xa483328 m=6 mp=0xa900008 [running]:
    panic({0x816e080, 0x81beff0})
    	/workdir/go/src/runtime/panic.go:778 +0x144 fp=0xa829aa8 sp=0xa829a54 pc=0x8083304
    internal/concurrent.(*HashTrieMap[...]).CompareAndDelete(0x81c00a0, {0xa74eb20, 0xa}, 0xd)
    	/workdir/go/src/internal/concurrent/hashtriemap.go:212 +0x374 fp=0xa829af8 sp=0xa829aa8 pc=0x815b9a4
    internal/concurrent.testHashTrieMap.func8.1(0xd)
    	/workdir/go/src/internal/concurrent/hashtriemap_test.go:163 +0x54e fp=0xa829fe8 sp=0xa829af8 pc=0x815610e
    internal/concurrent.testHashTrieMap.func8.gowrap1()
    ...
    runtime.gopark(0x81986a4, 0xaa2a168, 0x1a, 0xa, 0x0)
    	/workdir/go/src/runtime/proc.go:401 +0x10c fp=0xaa25f8c sp=0xaa25f78 pc=0x8086cdc
    runtime.gcBgMarkWorker(0xaa1e000)
    	/workdir/go/src/runtime/mgc.go:1352 +0xfd fp=0xaa25fe8 sp=0xaa25f8c pc=0x806362d
    runtime.gcBgMarkStartWorkers.gowrap1()
    	/workdir/go/src/runtime/mgc.go:1268 +0x27 fp=0xaa25ff0 sp=0xaa25fe8 pc=0x8063517
    runtime.goexit({})
    	/workdir/go/src/runtime/asm_386.s:1393 +0x1 fp=0xaa25ff4 sp=0xaa25ff0 pc=0x80bb701
    created by runtime.gcBgMarkStartWorkers in goroutine 34
    	/workdir/go/src/runtime/mgc.go:1268 +0x12c


— [watchflakes](https://go.dev/wiki/Watchflakes)
Repository: vscode
Issue: ChatResponseCommandButtonPart's should have a way to signal they've been 'used'
Labels: feature-request,api,chat

Because panel chat does not support diffs natively, I have a button to "Apply Changes" that applies the workspace edit when a model has changes to make.

However, after this is done, the button stays there and can be clicked again, which is likely to just lead to confusion since applying edits again will corrupt the file. It would be nice if there was a way in the API to make the button disabled and/or change text after the command it references has been executed.
Repository: rust
Issue: generic_const_exprs and inline_const interact poorly.
Labels: T-compiler,C-bug,F-inline_const,F-generic_const_exprs

On current nightly, this code works:

```rust
#![feature(inline_const)]

fn foo<const N: usize>() {
    const {
        assert!(N > 0);
    }
}

fn main() {
    foo::<4>();
}
```

However this code fails to compile if generic_const_exprs is enabled, by just adding `#![feature(generic_const_exprs)]` at the top of the file:

```
error: overly complex generic constant
 --> t.rs:5:11
  |
5 |       const {
  |  ___________^
6 | |         assert!(N > 0);
7 | |     }
  | |_____^ blocks are not supported in generic constants
  |
  = help: consider moving this anonymous constant into a `const` function
  = note: this operation may be supported in the future

error: aborting due to 1 previous error; 1 warning emitted
```

Which is clearly broken? generic_const_exprs should probably not try to dig into that expression to begin with.
Repository: pytorch
Issue: [feature request] allow torch.compile calls with compiler options, but without modifying global dynamo options
Labels: feature,triaged,oncall: pt2,module: dynamo

### 🚀 The feature, motivation and pitch

Originally discussed in: https://github.com/pytorch/pytorch/issues/106614

As I understood, any torch.compile call with passed options will modify global compiler options (and thus require `torch._dynamo.reset()` or sth like this). I suggest to introduce a "local mode" which applies passed options but only to a given function. Or maybe also introduce a "compile options context" - this would be a "semi-local" mode

### Alternatives

_No response_

### Additional context

_No response_

cc @ezyang @msaroufim @bdhirsh @anijain2305 @chauhang @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng
Repository: go
Issue: net: TestLookupContextCancel failures
Labels: NeedsInvestigation

```
#!watchflakes
default <- pkg == "net" && test == "TestLookupContextCancel"
```

Issue created automatically to collect these failures.

Example ([log](https://ci.chromium.org/b/8750210496859064209)):

    === RUN   TestLookupContextCancel
        lookup_test.go:917: starting concurrent LookupIPAddr
        lookup_test.go:940: testHookLookupIP performing lookup
        lookup_test.go:923: lookup google.com: no such host
    --- FAIL: TestLookupContextCancel (40.28s)


— [watchflakes](https://go.dev/wiki/Watchflakes)
Repository: flutter
Issue: Add gn rules to build iOS tests
Labels: platform-ios,engine,platform-mac,P2,team-engine,triaged-engine,e: engine-tool

Currently many iOS tests in the engine are run via Python scripts. We should support building these to targets to an output that is executable on the host machine and that does whatever test/simulator setup is required, then co-ordinates the running of the test, logging output, and reporting pass/fail status. Rule output could be as simple as a shell script.

Ideally these should resemble as much as possible, in terms of target attributes and configuration, the equivalent macOS and C++ rules.

Once supported, these rules can then be wired into `et` so that tests can be queried and launched from the tool.

See https://github.com/flutter/flutter/issues/147013 for an example of how this was done for Dart.
Repository: flutter
Issue: Support iOS tests in `et`
Labels: platform-ios,engine,platform-mac,P2,team-engine,triaged-engine,e: engine-tool

Once gn rules have been created to generate executable targets for iOS tests (https://github.com/flutter/flutter/issues/147071), add support to `et` to return these targets in queries and to be able to run them using `et test`.

See https://github.com/flutter/engine/pull/52250 for how this was done for Dart tests.
Repository: rust
Issue: testing `cg_gcc` is difficult
Labels: T-compiler,T-bootstrap,T-infra,C-bug,A-gcc

cc @GuillaumeGomez @antoyo

The backend currently only supports x86-64, but some contributors primarily use aarch64 machines, but have cause to work on the codegen backends. They instead have to force cg_gcc's code through emulators, which is often an inadequate solution. It would be better if it simply supported all of our **tier 1** architectures.

### Meta

`rustc --version --verbose`:
```
rustc 1.79.0-nightly (ccfcd950b 2024-04-15)
binary: rustc
commit-hash: ccfcd950b333fed046275dd8d54fe736ca498aa7
commit-date: 2024-04-15
host: x86_64-unknown-linux-gnu
release: 1.79.0-nightly
LLVM version: 18.1.3
```
Repository: pytorch
Issue: torch.export of ResNet with dynamic height fails due to constraint violation
Labels: oncall: export

### 🐛 Describe the bug

torch.export of ResNet with dynamic height fails due to constraint violation -- apparently it wants the height to be even.

Here is an example repro

```
import torch
from torchvision.models import resnet34

device = torch.device('cuda')
model = resnet34().to(device)
model.eval()

k = 1  # works with k = 2
height = torch.export.Dim('height', min=320 // k, max=7680 // k)
exported = torch.export.export(
    model,
    args=(
        torch.randn((1, 3, 640, 320)).to(device),
    ),
    dynamic_shapes=(
        {2: height * k},
    ),
)
example_input = torch.randn((1, 3, 1242, 320)).to(device)
print(exported.module()(example_input).shape)
```

This fails with
```
torch.fx.experimental.symbolic_shapes.ConstraintViolationError: Constraints violated (height)! For more information, run with TORCH_LOGS="+dynamic".
  - Not all values of height = L['x'].size()[2] in the specified range 320 <= height <= 7680 satisfy the generated guard Ne(Mod(((L['x'].size()[2] - 1)//2), 2), 0).

Suggested fixes:
  height = Dim('height', min=320, max=7680)
```

If we set k to 2 (so that height is always even), it works.

### Versions

This is using torch nightly.

```
Collecting environment information...                                                                                                  
PyTorch version: 2.4.0.dev20240419+cu121                                                                                               
Is debug build: False                                                                                                                  
CUDA used to build PyTorch: 12.1             
ROCM used to build PyTorch: N/A                          

OS: Ubuntu 22.04.1 LTS (x86_64)
GCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
Clang version: Could not collect
CMake version: Could not collect
Libc version: glibc-2.35
                                                                   
Python version: 3.10.6 (main, May 29 2023, 11:10:38) [GCC 11.3.0] (64-bit runtime)
Python platform: Linux-5.15.0-73-generic-x86_64-with-glibc2.35
Is CUDA available: True              
CUDA runtime version: Could not collect
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration:               
GPU 0: NVIDIA GeForce RTX 2080 Ti

Nvidia driver version: 550.67
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
...

Versions of relevant libraries:
[pip3] mypy==1.7.0
[pip3] mypy-extensions==1.0.0
[pip3] numpy==1.23.1
[pip3] onnx==1.15.0
[pip3] onnxruntime==1.17.1
[pip3] onnxruntime-gpu==1.17.1
[pip3] pytorch-triton==3.0.0+989adb9a29
[pip3] torch==2.4.0.dev20240419+cu121
[pip3] torch-model-archiver==0.5.3
[pip3] torchserve==0.7.1
[pip3] torchvision==0.19.0.dev20240419+cu121
[conda] Could not collect
```

cc @avikchaudhuri @gmagogsfm @zhxchen17 @tugsbayasgalan @angelayi @suo @ydwu4
Repository: next.js
Issue: Importing default from `next/document` in ESM inside a third-party package doesn't work
Labels: bug,Pages Router

### Link to the code that reproduces this issue

https://github.com/DiegoAndai/esm-test-8-next-document-monorepo?tab=readme-ov-file

### To Reproduce

Follow instructions in: https://github.com/DiegoAndai/esm-test-8-next-document-monorepo?tab=readme-ov-file#running-the-repro

### Current vs. Expected behavior

### Current

When importing next/document.js from an ESM module, the default value is not properly set:

```js
import Document from "next/document.js";

Document.getInitialProps; // unexpectedly undefined
Document.default.getInitialProps; // function
```

### Expected

In ESM, the default import should be set with using the syntax:

```js
import Document from "next/document.js";

Document.getInitialProps; // function
```

- NodeJS reference: https://nodejs.org/docs/latest/api/esm.html#esm_commonjs_namespaces:~:text=The%20preceding%20module%20supports%20named%20imports%20in%20ES%20modules%3A

### Provide environment information

```bash
Operating System:
  Platform: darwin
  Arch: x64
  Version: Darwin Kernel Version 22.5.0: Thu Jun  8 22:22:22 PDT 2023; root:xnu-8796.121.3~7/RELEASE_X86_64
  Available memory (MB): 16384
  Available CPU cores: 16
Binaries:
  Node: 18.19.0
  npm: 10.4.0
  Yarn: 1.22.21
  pnpm: 8.14.1
Relevant Packages:
  next: 14.2.2 // Latest available version is detected (14.2.2).
  eslint-config-next: N/A
  react: 18.2.0
  react-dom: 18.2.0
  typescript: N/A
Next.js Config:
  output: N/A
```


### Which area(s) are affected? (Select all that apply)

Pages Router

### Which stage(s) are affected? (Select all that apply)

next dev (local), next build (local)

### Additional context

Issue found when [trying to add `exports`](https://github.com/mui/material-ui/pull/41596) field to [the `material-nextjs` integration package](https://github.com/mui/material-ui/tree/next/packages/mui-material-nextjs).
Repository: bitcoin
Issue: Manually Banning Peers Results in Crash
Labels: GUI

### Is there an existing issue for this?

- [X] I have searched the existing issues

### Current behaviour

Both the pre-built binaries and manually compiling from source give the same issues with v27.

Very serious crashes that entirely lockup the client and require a force restart across both Windows 10 and Windows 11 across multiple machines. The issue does not happen on my Ubuntu machines and it seems to only be happening with my Windows based machines.

Have tried opening this ticket many times now but my logs never fit. Can provide them but they provide nothing of note anyways as the client crashes and Windows closes Core before it can write to the log the issue, but the issue seems QT driven so I'm not sure it would even show up in the log anyways.

Issue seems to happen the most when banning bad behaving peers manually.

### Expected behaviour

To be able to right click and ban known bad acting peers without a crash.

### Steps to reproduce

Right click on a bad actor peer and ban them, immediate lockup across MULTIPLE systems and both Windows 10 and Windows 11.

### Relevant log output

Can include in a comment as each time I have tried to make this issue (more than ten times now) I am unable to include the log because it exceeds the comment length.

### How did you obtain Bitcoin Core

Other

### What version of Bitcoin Core are you using?

v27 both pre-built and manually compiled, same issue.

### Operating system and version

Windows 10 and Windows 11

### Machine specifications

_No response_
Repository: pytorch
Issue: optim.apply_optimizer_in_backward does not account for gradient accumulation
Labels: oncall: distributed,module: optimizer,triaged

### 🐛 Describe the bug

https://github.com/pytorch/pytorch/blob/main/torch/distributed/optim/apply_optimizer_in_backward.py 

This fires the optimizer every time the gradient gets accumulated. However, in practice we might do gradient accumulation. So if we have a logical batch size of 64 and a physical batch size of 8, "apply_optimizer_in_backward" will not distinguish between the microbatches.

My suggested fix: just raise a warning for the user if we detect that gradient accumulation is being used with apply_optimizer_in_backward. I don't think it's possible to actually make this function work with gradient accumulation.

### Versions

Versions of relevant libraries:
[pip3] numpy==1.26.4
[pip3] torch==2.2.2
[pip3] triton==2.2.0
[conda] numpy                     1.26.4                   pypi_0    pypi
[conda] torch                     2.2.2                    pypi_0    pypi
[conda] triton                    2.2.0                    pypi_0    pypi

cc @mrshenli @pritamdamania87 @zhaojuanmao @satgera @rohan-varma @gqchen @aazzolini @osalpekar @jiayisuse @H-Huang @kwen2501 @awgu @penguinwu @fegin @XilunWu @wanchaol @fduwjj @wz337 @tianyu-l @wconstab @yf225 @chauhang @d4l3k @vincentqb @jbschlosser @albanD @janeyx99 @crcrpar
Repository: tauri
Issue: [bug] macOS audio bug with .webm
Labels: type: bug,status: upstream,platform: macOS,status: needs triage

### Describe the bug

Im working on a app with Tauri so far so good on windows everything works as expected but on macOS i can not play any files it alwasy gives me a error that the operation is not supported. I can confirm its only when using webm i tried it with mp3 too and that worked without any problems.

### Reproduction

- Clone Vleer on a macOS machine
- install all the dependencies
- run the app in dev mode
- download a song through the search page
- look into the browser console (right click inspect element)

### Expected behavior

It should play normally like on windows

### Full `tauri info` output

```text
[✔] Environment
    - OS: Mac OS 14.4.1 X64
    ✔ Xcode Command Line Tools: installed
    ✔ rustc: 1.76.0 (07dca489a 2024-02-04)
    ✔ cargo: 1.76.0 (c84b36747 2024-01-18)
    ✔ rustup: 1.26.0 (2023-04-05)
    ✔ Rust toolchain: stable-aarch64-apple-darwin (default)
    - node: 18.18.2
    - pnpm: 8.15.1
    - yarn: 1.22.19
    - npm: 10.4.0
    - bun: 1.1.3

[-] Packages
    - tauri [RUST]: 2.0.0-beta.15
    - tauri-build [RUST]: 2.0.0-beta.12
    - wry [RUST]: 0.39.1
    - tao [RUST]: 0.27.0
    - tauri-cli [RUST]: 1.5.11
    - @tauri-apps/api [NPM]: 2.0.0-beta.7
    - @tauri-apps/cli [NPM]: 2.0.0-beta.12

[-] App
    - build-type: bundle
    - CSP: unset
    - frontendDist: ../dist
    - devUrl: http://localhost:3000/
    - framework: Vue.js (Nuxt)
    - bundler: Webpack
```


### Stack trace

```text
$ tauri dev
    Running BeforeDevCommand (`pnpm nuxt dev`)
Nuxt 3.11.2 with Nitro 2.9.6                                                                                                           
                                                                                                                                                                                    
  ➜ Local:    http://localhost:3000/
  ➜ Network:  use --host to expose

    Info Watching /Users/pandadev/Developer/App/Vleer/src-tauri for changes...
   Compiling vleer v1.0.0 (/Users/pandadev/Developer/App/Vleer/src-tauri)
ℹ ✨ new dependencies optimized: axios, @tauri-apps/plugin-dialog                                                                                                                  
ℹ ✨ optimized dependencies changed. reloading                                                                                                                                     
ℹ Vite client warmed up in 1379ms                                                                                                                                                  
✔ Nuxt Nitro server built in 811 ms                                                                                                                                          
    Finished dev [unoptimized + debuginfo] target(s) in 4.24s
RemoteLayerTreeDrawingAreaProxyMac::scheduleDisplayLink(): page has no displayID
```


### Additional context

https://github.com/Vleerapp/Vleer
Repository: vscode
Issue: Duplicate untitled notebook is opened
Labels: bug,notebook

<!-- ⚠️⚠️ Do Not Delete This! bug_report_template ⚠️⚠️ -->
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<!-- 💡 Instead of creating your report here, use 'Report Issue' from the 'Help' menu in VS Code to pre-fill useful information. -->
<!-- 🔧 Launch with `code --disable-extensions` to check. -->
Does this issue occur when all extensions are disabled?: Yes

<!-- 🪓 If you answered No above, use 'Help: Start Extension Bisect' from Command Palette to try to identify the cause. -->
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- VS Code Version: 1.87.2
- OS Version: Linux

Steps to Reproduce:

1. Create a new untitled notebook with one cell in it
2. Open command palette (cmd + P) and run `Notebook: Delete Cell`
3. Two `Untitled-1` notebooks show up

<img width="833" alt="Screenshot 2024-04-19 at 2 40 15 PM" src="https://github.com/microsoft/vscode/assets/111001237/bcc7ea73-cc41-4b5a-b3db-94f83ef800f5">
Here is the screen recording:

https://github.com/microsoft/vscode/assets/111001237/be9c55a0-86e5-4526-bb38-08a7f4ec9b6f

Since that was really fast, here is a 0.25x speed screen recording:

https://github.com/microsoft/vscode/assets/111001237/729978c0-f98f-4c8e-965d-4b8c28ea4426

I've seen this a few times the past month. So far I am only able to reproduce this in my tests (which use https://github.com/redhat-developer/vscode-extension-tester) and the machine there is Linux. I'm contributing a custom notebook `.c3nb`, and here is the code for opening a notebook with a cell:

```js
const vscode = require('vscode');

async function createNotebook(appName) {
  const data = new vscode.NotebookData([
    new vscode.NotebookCellData(vscode.NotebookCellKind.Code, '// begin coding', 'javascript'),
  ]);
  const notebook = await vscode.workspace.openNotebookDocument('my-notebook-type', data);
  await vscode.window.showNotebookDocument(notebook);
}
```

Any help would be appreciated!
Repository: tensorflow
Issue: tf.function deadlock with multiple multiprocess/threading
Labels: stat:awaiting tensorflower,type:bug,comp:tf.function,TF 2.16

### Issue type

Bug

### Have you reproduced the bug with TensorFlow Nightly?

Yes

### Source

binary

### TensorFlow version

2.16

### Custom code

Yes


### Current behavior?

TensorFlow gets stuck when using multiprocessing/threading more than once.

I've observed it in more complicated situations with only once multithreading, but the following is a reproducible, standalone example that illustrates the point.

The code works correctly if either the `tf.function` decorator is removed _or_ if xla compilation `jit_compile` is enabled (!).

### Standalone code to reproduce the issue

```shell
import multiprocessing as mp  # can also be another module for multiprocess/threading
import random

import tensorflow as tf


# if we use jit_compile=True, it will work, magically
# it also works if there is no decorator at all, i.e. only eager mode
@tf.function(jit_compile=False)
def testjit(x):
    return tf.math.reduce_sum(x)


def make_zdata(_=None):
    print('Making data')
    # just to make sure that we recompile the function (different shapes)
    rnd = tf.random.uniform([random.randint(100, 10000)], -1, 1)
    zdata = testjit(rnd)
    print('Made data')
    return zdata

with mp.Pool(1) as executor:
    executor.map(make_zdata, [1])
executor.terminate()

# if we run this, it will fail (if jit_compile=False)
with mp.Pool(1) as executor:
    executor.map(make_zdata, [1])  # here, the code will be stuck
executor.terminate()
```


### Relevant log output

will be, approximately:
```
Making data
Made data
Making data
```
and then it's stuck. Otherwise, if using `jit_compile=True` or not using the tf.function decorator at all, another `Made data` will be printed