sharjeelyunus/github-issues-dataset huggingface dataset:
Repository: stable-diffusion-webui
Issue: [Feature Request]: Add/select generated images from a batch to a queue to be upscaled sequentially
Labels: enhancement

### Is there an existing issue for this?

- [X] I have searched the existing issues and checked the recent builds/commits

### What would your feature do ?

Currently you can only individually upscale an image 1 at a time. I generate say 4 images and go through them to see if any of them are worth upscaling. I want to be able either to click "upscale" and have that image added to the queue or select them and then upscale all the selected ones. I prefer the first method to save time.

### Proposed workflow

1. Generate a number of images
2. Click upscale on an image
3. While an image is being upscaled, click upscale on another image
4. Another image is added to a queue to upscale right after


### Additional information

_No response_
Repository: PowerToys
Issue: Swap selected text with clipboard
Labels: Idea-New PowerToy,Needs-Triage

### Description of the new feature / enhancement

When editing, having the ability to swap selected text with the content of the current clipboard. After the swap, the selected text now contains the clipboard, and the clipboard contains the previously selected text. 

### Scenario when this would be used?

When editing .xml files, swapping two specific values at different locations would be helpful. 
Key sequence before beforethis feature request;
place cursor at first location 
drag to select text
ctrl-c
place cursor at second location 
ctrl-v
at current location, drag to select text (to be moved to first location)
ctrl-c
place cursor back at first location 
ctrl-v

Key sequence after this feature request;
place cursor at first location 
drag to select text
ctrl-c
place cursor at second location, drag to select text
ctrl-s (the new feature swapping!)
place cursor at first location 
ctrl-v

### Supporting information

Two steps less and practical.
Repository: godot
Issue: [4.2] Headless import leads to invalid geometry in GDQuest TPS demo
Labels: bug,topic:rendering,topic:import

### Tested versions

- Reproducible in 4.2.2.stable, 4.2.1.stable, 4.2.stable
- Not reproducible in 4.3.dev (64520fe6741d8ec3c55e0c9618d3fadcda949f63), so it's 4.2 specific, but backporting the fix would be great

### System information

Fedora Linux 40 (KDE Plasma) - Wayland - Vulkan (Forward+) - dedicated AMD Radeon RX 7600M XT (RADV NAVI33) () - AMD Ryzen 7 7840HS w/ Radeon 780M Graphics (16 Threads)

### Issue description

When importing the GDQuest TPS demo (https://github.com/gdquest-demos/godot-4-3d-third-person-controller) with 4.2.2.stable in `--headless` mode (`godot --import --headless -v`), the tree meshes seem to be broken:

![image](https://github.com/godotengine/godot/assets/4701338/0caa0ef5-9e13-4a9c-931e-550077a48cee)
Import logs: [import-headless.log](https://github.com/godotengine/godot/files/15165451/import-headless.log)

When importing without `--headless`, the trees are correct (`godot --import -v`):

![Screenshot_20240430_155514](https://github.com/godotengine/godot/assets/4701338/9620816c-a87e-4f3a-8c93-f91b96f0e1ca)
Import logs: [import-vulkan.log](https://github.com/godotengine/godot/files/15165454/import-vulkan.log)

The main difference between the import logs is this error:
```
ERROR: Parameter "m" is null.
   at: mesh_get_surface_count (servers/rendering/dummy/storage/mesh_storage.h:114)
```

### Steps to reproduce

- Clone https://github.com/gdquest-demos/godot-4-3d-third-person-controller
- Import with `godot --headless --import` (or in earlier 4.2.x verisons, `godot --headless -e --quit-after 100`)
- Run the project

### Minimal reproduction project (MRP)

I'll see if I can extract a scene, but for now it's just:
https://github.com/gdquest-demos/godot-4-3d-third-person-controller
Repository: vscode
Issue: Keybindings service spends a long time in `updateKeybindingsJsonSchema`
Labels: perf-startup

![image](https://github.com/microsoft/vscode/assets/900690/99ee9236-db53-4d6d-8734-039da92ebfb9)

Is this needed and critical for startup or only later needed when using the keybindings editor? If so, could we take it out of the startup path?

[Trace-20240430T114019.json.zip](https://github.com/microsoft/vscode/files/15165566/Trace-20240430T114019.json.zip)
Repository: kubernetes
Issue: SVM RV Semantics: assert that k8s-dqlite RV semantics match etcd
Labels: sig/api-machinery,triage/accepted

[k8s-dqlite](https://github.com/canonical/k8s-dqlite) implements the etcd gRPC API.  We need to assert that its RV semantics match that of etcd, meaning that running SVM on either environment would work as expected.

/assign nilekhc
/triage accepted
/sig api-machinery

Links to code searches performed: [[1]](https://github.com/search?type=code&q=.RegisterWatchServer%28+.RegisterKVServer%28+language%3AGo+NOT+is%3Afork++NOT+is%3Aarchived&p=1) [[2]](https://grep.app/search?q=.RegisterWatchServer%28)
Repository: kubernetes
Issue: SVM RV Semantics: assert that kubebrain RV semantics match etcd
Labels: sig/api-machinery,triage/accepted

[kubebrain](https://github.com/kubewharf/kubebrain) implements the etcd gRPC API.  We need to assert that its RV semantics match that of etcd, meaning that running SVM on either environment would work as expected.

/assign nilekhc
/triage accepted
/sig api-machinery

Links to code searches performed: [[1]](https://github.com/search?type=code&q=.RegisterWatchServer%28+.RegisterKVServer%28+language%3AGo+NOT+is%3Afork++NOT+is%3Aarchived&p=1) [[2]](https://grep.app/search?q=.RegisterWatchServer%28)
Repository: pytorch
Issue: torch.no_grad() is not working for dynamo inductor backend 
Labels: triaged,oncall: pt2,module: inductor

### 🐛 Describe the bug

torch dynamo context manager is not seeing the `torch.no_grad()` setting from torchbench framework.

This is the reproducer
`python run_benchmark.py cpu --model hf_Bert --test eval --torchdynamo inductor`

Here is the code snippet from torchbench that sets the no_grad()
https://github.com/pytorch/benchmark/blob/main/torchbenchmark/util/framework/huggingface/model_factory.py#L120

```
with torch.no_grad():
            with self.amp_context():
                out = self.model(**self.example_inputs)
```
but the torch dynamo inductor backend isn't seeing the grad disabled, and hence is not triggering the graph level optimizations.
https://github.com/pytorch/pytorch/blob/v2.3.0/torch/_inductor/compile_fx.py#L1270

### Error logs

no error log, but the torch.compile didn't trigger the fx graph  optimizations

### Minified repro

_No response_

### Versions

torch mainline as well as torch 2.3
torchbench mainline
Ubuntu 22.04
aarch64 and x86_64

cc @ezyang @msaroufim @bdhirsh @anijain2305 @chauhang @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @peterbell10 @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 @ColinPeppler @amjames @desertfire
Repository: pytorch
Issue: Improved strategy for dealing with deterministically flaky tests which are order sensitive
Labels: module: ci,module: tests,triaged

### 🐛 Describe the bug

We have a pretty big flaky test problem in PyTorch CI (at time of writing, there are 389 open disables for flaky tests). Based on work done by @zou3519 et al, we have determined a big class of these flaky issues are due to ordering problems: that is to say, the test deterministically passes 100% when run by itself, but it's only failing when run with some other tests before it. We also suspect that test reordering (e.g., due to target determination) makes these tests flaky. Many flaky tests report 50% fail rate, but folks are consistently unable to reproduce.

If it is true that a test only fails when run with some other tests in a particular order, then it should be simple to reproduce problems locally. The bare minimum we need is:

1. CI must tell us exactly what order tests were run in on the run that failed
2. We need some way of running tests in exactly the same order locally

We technically have both of these pieces today. Specifically, the CI logs which tests it is executing from a shard, and using a pytest plugin bundled with https://github.com/asottile/detect-test-pollution you can force tests to execute in a particular error.  The rest of the problem is user education and UI.

To give an example, https://github.com/pytorch/pytorch/issues/119747 is a flaky test which folks have investigated, but which doesn't reproduce when you run it by yourself. It does reproduce when you run the same set of tests that ran exactly in CI.

Here is an idealized workflow I am imagining.

1. CI detects that a test is flaky, because it only fails sometimes or not other times.
2. Some offline infrastructure checks if the test is deterministically flaky based on test order. Specifically, it needs to rerun the entire test shard, exactly as run the first time, and check if the test fails again. (This is expensive).
3. Once it has been determined to be deterministically flaky, the offline infrastructure can use a tool like detect-test-pollution to attempt to bisect to a minimal set of tests that have to be run in order to repro the problem
4. We file a nice issue with clear instructions for how to reproduce the deterministic problem
5. Developers debug and fix issues
6. Profit!

We don't have to implement all of the ideal workflow, but in particular, making it easier for people to test (1) is it deterministically failing given a test order and (2) what exact order should I run things in, seems to be important. It also is relatively time consuming (on order of hours) to bisect minimum number of tests that need to be run, so an offline process that can backfill this would also be useful.

### Versions

main

cc @seemethere @malfet @pytorch/pytorch-dev-infra @mruberry @ZainRizvi
Repository: vscode
Issue: Use a non-webview component for text outputs and errors in notebooks
Labels: debt

Bringing these types of outputs out of the webview should make them easier to work with and provide access to the rest of the core code-base.

quicker - no passing messages between webview and renderer
better linking - similar to the terminal/chat view
access to core components

@Tyriar suggested we could try using xterm for this
Repository: material-ui
Issue: [material-ui][Modal] Enhanced Modals Manager with Multi-step Modal Support and Confirm Modal Component
Labels: new feature,waiting for 👍,component: modal,package: material-ui

### Summary

Introduce a feature to enhance the issue formatting for the modals manager. This feature aims to create a centralized modals manager with the ability to handle the state of multi-step modals efficiently.

### Examples

Refer to the Material Design specification or other implementations for inspiration on the expected behavior. Screenshots of the proposed implementation or links to similar implementations can also be provided for clarity.

Example Implementation: [Mantine Modals Manager](https://mantine.dev/x/modals/)

### Motivation

The objective of this feature is to streamline the management of modals within the application. By centralizing the modals manager, developers can efficiently handle the state of multi-step modals, enhancing the user experience and facilitating smoother interactions. Additionally, introducing a confirm modal component with built-in confirm and cancel buttons will improve the user flow for actions requiring confirmation. Furthermore, by clarifying that dynamic content is not supported when using the modals manager, users can make informed decisions about their implementation strategy, ensuring a seamless integration with the existing codebase.


**Search keywords**: modal

**Search keywords**:
Repository: pytorch
Issue: support methods for torch.compiler.allow_in_graph
Labels: triaged,oncall: pt2,module: dynamo

### 🚀 The feature, motivation and pitch

this is a bug/feature report.

When using `torch.dynamo.allow_in_graph` on a method, it's not respected during compile.


```python
import torch                                            
                                                                                          
def custom_backend(gm, _):
    gm.graph.print_tabular()                                                              
    return gm.forward


def test_allow_in_graph_fn():
    torch._dynamo.reset()

    @torch._dynamo.allow_in_graph
    def add_fn(a, b):
        return a + b

    class Model(torch.nn.Module):
        def forward(self, x):
            return add_fn(x, x)

    model = Model()
    model = torch.compile(model, backend=custom_backend)
    x = torch.rand(10)
    model(x)
```

This correctly creates a node for the `add_fn`

```
placeholder    l_x_    L_x_                                                                 ()            {}
call_function  add_fn  <function test_allow_in_graph_fn.<locals>.add_fn at 0x7f5c5646dea0>  (l_x_, l_x_)  {}
output         output  output                                                               ((add_fn,),)  {}
```

```python
def test_allow_in_graph_class_fn():
    torch._dynamo.reset()

    class Foo:
        @torch._dynamo.allow_in_graph
        def add_fn(self, a, b):
            return a + b

    class Model(torch.nn.Module):
        def forward(self, x):
            foo = Foo()
            print(id(foo.add_fn))
            return foo.add_fn(x, x)

    print(id(Foo.add_fn))
    model = Model()
    model = torch.compile(model, backend=custom_backend)
```
This instead shows a node, for the built in add `+`
```
placeholder    l_a_    L_a_                     ()            {}
call_function  add     <built-in function add>  (l_a_, l_a_)  {}
output         output  output                   ((add,),)     {}
```

This is most likely due to the `id` being used by `allow_in_graph`, however, this changes in python after the instance is created.


The ideal solution would be if this was actually supported, alternatively I think some warning/error when `allow_on_graph` is used on a method could make sense.

### Alternatives

`torch.compiler.disable` works is being respected, but it creates graph breaks which have been causing downstream issues for our custom backend so the `allow_in_graph` behaviour is preferred.



### 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: pytorch
Issue: [export] Add customization API for unflattener to control restored module types.
Labels: oncall: export

### 🚀 The feature, motivation and pitch

Today when we call unflattener, the restored module will look like the following:
```
(UnflattenedModule):
   (InterpreterModule)
      (InterpreterModule)
      (InterpreterModule)
      (InterpreterModule)
```
This prevents some eager transformations from functioning e.g. pipeline + tensor parallelism or quantization. Ideally it should be possible for users to restore the original submodule types like the following:
```
(UnflattenedModule):
   (ModuleList)
      (Linear)
      (Linear)
      (Linear)
```
We had an internal discussion recorded in this doc: https://docs.google.com/document/d/1CAKtSiPWMyjOwaEbTmoT1yM2vF2ZucxxbVeFYhhdy8A/edit 

This issue is filed for tracking purpose.

### Alternatives

_No response_

### Additional context

_No response_

cc @avikchaudhuri @gmagogsfm @tugsbayasgalan @angelayi @suo @ydwu4
Repository: stable-diffusion-webui
Issue: [Feature Request]:  Implement AYS Sampler proposed by Nvidia
Labels: enhancement

### Is there an existing issue for this?

- [X] I have searched the existing issues and checked the recent builds/commits

### What would your feature do ?

Align Your Steps (AYS), a novel general framework for optimizing sampling schedules in diffusion models that
significantly boosts the quality of outputs, especially when performing synthesis in few steps.
<img width="1020" alt="image" src="https://github.com/AUTOMATIC1111/stable-diffusion-webui/assets/20336084/f3ac395c-9aa1-4acf-a13a-cd95eab94b7c">


### Proposed workflow

The author has implemented AYS sampler in diffusers. It would be convenient to port it into webui. https://research.nvidia.com/labs/toronto-ai/AlignYourSteps/howto.html 

### Additional information

1. https://arxiv.org/abs/2404.14507 
2. https://research.nvidia.com/labs/toronto-ai/AlignYourSteps/
Repository: go
Issue: cmd/go/internal/modfetch: TestCodeRepo failures
Labels: NeedsInvestigation

```
#!watchflakes
default <- pkg == "cmd/go/internal/modfetch" && test == "TestCodeRepo"
```

Issue created automatically to collect these failures.

Example ([log](https://build.golang.org/log/fc71f7b8711523a83745e43fdd7423e1bd7689f1)):

    vcs-test.golang.org rerouted to http://127.0.0.1:46001
    https://vcs-test.golang.org rerouted to https://127.0.0.1:40743
    --- FAIL: TestCodeRepo (0.00s)
        --- FAIL: TestCodeRepo/github.com_rsc_vgotest1_v2/v2.0.1 (22.11s)
            coderepo_test.go:623: repo.Stat("v2.0.1"): github.com/rsc/vgotest1/v2@v2.0.1: invalid version: git fetch -f origin refs/heads/*:refs/heads/* refs/tags/*:refs/tags/* in /tmp/workdir/tmp/gitrepo-test-62827515/modcache/cache/vcs/4a5198d614ab1a6ef5a42101e7276bebd49f61fe11c77b35a3eeaaa999be6485: exit status 128:
                	error: RPC failed; HTTP 400 curl 22 The requested URL returned error: 400
                	fatal: expected flush after ref listing


— [watchflakes](https://go.dev/wiki/Watchflakes)
Repository: terminal
Issue: Terminal crashes when launched by `start /MAX`
Labels: Issue-Bug,Product-Terminal,Priority-2,Area-DefApp

### Windows Terminal version

1.19.10821.0

### Windows build number

10.0.22631.0

### Other Software

_No response_

### Steps to reproduce

Create the following batch file:
```batch
@echo off

REM restart maximized if not already
if not "%1" == "max" start /MAX cmd /c %0 max & exit /b

echo Beep boop
timeout /t 20

```

With all Terminal windows closed, double-click to execute the script.

### Expected Behavior

Terminal window should open maximized and display the 20 second countdown.

### Actual Behavior

You will see a terminal window pop up momentarily then exit, rather than waiting the 20 seconds.

Open a Terminal window in the background, then double-click to execute the script again. You will see a maximized terminal window pop up showing the countdown from 20 seconds (as expected).

Feedback Hub link: https://aka.ms/AAq7vl0
Repository: vscode
Issue: Saving notebook files should happen on extension host by default
Labels: bug,notebook-workflow

Right now, the setting `"notebook.experimental.remoteSave": true` can be used to save the file on the EH instead of needing a trip to the renderer. We should try to enable this behavior by default.

Need to handle this issue https://github.com/microsoft/vscode/issues/209291. It's hard to repro, but seems to come from this new code path.
Repository: flutter
Issue: [flutter_tools] Operation timed out while writing outputs.json from FlutterBuildSystem.build
Labels: P2,team-tool,triaged-tool

Version `beta/3.22.0-0.3.pre`

Only one affected client, although there is another similar one, but the OS error being `FileSystemException: Cannot open file, path = '/home/user/myapp/.dart_tool/flutter_build/ee75a1ac45aed72d173922f633b6dede/outputs.json' (OS Error: Read-only file system, errno = 30)`

```
FileSystemException: Cannot open file, path = '/Users/username/Desktop/SumMail/.dart_tool/flutter_build/6024ac9684952f34c214fdf161afab6d/outputs.json' (OS Error: Operation timed out, errno = 60)
at _File.throwIfError(file_impl.dart:675)
at _File.openSync(file_impl.dart:490)
at _File.writeAsBytesSync(file_impl.dart:644)
at _File.writeAsStringSync(file_impl.dart:668)
at ForwardingFile.writeAsStringSync(forwarding_file.dart:150)
at ErrorHandlingFile.writeAsStringSync.<anonymous closure>(error_handling_io.dart:266)
at _runSync(error_handling_io.dart:587)
at ErrorHandlingFile.writeAsStringSync(error_handling_io.dart:265)
at FlutterBuildSystem.build(build_system.dart:670)
at <asynchronous gap>(async)
at AssembleCommand.runCommand(assemble.dart:322)
at <asynchronous gap>(async)
at FlutterCommand.run.<anonymous closure>(flutter_command.dart:1394)
at <asynchronous gap>(async)
at AppContext.run.<anonymous closure>(context.dart:153)
at <asynchronous gap>(async)
at CommandRunner.runCommand(command_runner.dart:212)
at <asynchronous gap>(async)
at FlutterCommandRunner.runCommand.<anonymous closure>(flutter_command_runner.dart:372)
at <asynchronous gap>(async)
at AppContext.run.<anonymous closure>(context.dart:153)
at <asynchronous gap>(async)
at FlutterCommandRunner.runCommand(flutter_command_runner.dart:308)
at <asynchronous gap>(async)
at run.<anonymous closure>.<anonymous closure>(runner.dart:119)
at <asynchronous gap>(async)
at AppContext.run.<anonymous closure>(context.dart:153)
at <asynchronous gap>(async)
at main(executable.dart:93)
at <asynchronous gap>(async)
```
Repository: next.js
Issue: Dynamic metadata and RSC causing loader to be hidden without a page to render.
Labels: bug,Metadata

### Link to the code that reproduces this issue

https://github.com/felipedeboni/next-rendering-bug

### To Reproduce

1. Navigate to https://next-rendering-bug.vercel.app/
2. Click on "Works fine", the loading component shows up and later the page. No issues at all.
3. Click on "Has issues", the loading component shows up, then everything is gone and then the page is rendered.

### Current vs. Expected behavior

The expected behavior is the same as "Works fine".

### Provide environment information

```bash
Operating System:
  Platform: darwin
  Arch: arm64
  Version: Darwin Kernel Version 23.4.0: Fri Mar 15 00:12:49 PDT 2024; root:xnu-10063.101.17~1/RELEASE_ARM64_T6020
  Available memory (MB): 65536
  Available CPU cores: 12
Binaries:
  Node: 20.9.0
  npm: 10.1.0
  Yarn: 1.22.21
  pnpm: 8.15.4
Relevant Packages:
  next: 14.2.3 // Latest available version is detected (14.2.3).
  eslint-config-next: 14.2.3
  react: 18.3.1
  react-dom: 18.3.1
  typescript: 5.4.5
Next.js Config:
  output: N/A
```


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

Metadata, Partial Prerendering (PPR), Runtime

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

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

### Additional context

Looks like the bug was introduced in 14.2.1 - latest version it wasn't happening.

Additionally, it would be nice rendering loading.tsx  when the first request to get metadata is sent and hiding it only when the request for the RSC finish.