sharjeelyunus/github-issues-dataset huggingface dataset:
Repository: pytorch
Issue: shared torch.tensor with multiprocesses using python Queue cause coredump 
Labels: module: multiprocessing,triaged,shadow review

## 🐛 Bug

Our process crashed when send torch.tensor with Queue, but when the torch.tensor is converted  to numpy, the process works good.

When we send small torch.tensor, after couple of times of success, the process crash again! 

## To Reproduce

Steps to reproduce the behavior:

1 .run the following code on linux with kernel 3.10.0-693.el7.x86_64

<!-- If you have a code sample, error messages, stack traces, please provide it here as well -->

```
import time
from multiprocessing import Process
from multiprocessing.managers import SyncManager
from queue import PriorityQueue
import torch

class MyManager(SyncManager):
    pass
MyManager.register("PriorityQueue", PriorityQueue)  # Register a shared PriorityQueue


def Manager():
    class PipelineManager(SyncManager):
        pass

    PipelineManager.register("PriorityQueue", PriorityQueue)
    m = PipelineManager()
    m.start()
    return m

m = Manager()
pr_queue = m.PriorityQueue()

mytensor = torch.ones((153, 3, 224, 224), dtype=torch.float32)*3.141592

print(mytensor.shape)

pr_queue.put({"data": mytensor})

print("put data done")

time.sleep(600)
```

## Expected behavior

<!-- A clear and concise description of what you expected to happen. -->
the process with queue.put will crashed.
## Environment
python 3.6 
linux kernel 3.10.0-693.el7.x86_64
torch 1.2.0

Please copy and paste the output from our
[environment collection script](https://raw.githubusercontent.com/pytorch/pytorch/master/torch/utils/collect_env.py)
(or fill out the checklist below manually).

You can get the script and run it with:
```
wget https://raw.githubusercontent.com/pytorch/pytorch/master/torch/utils/collect_env.py
# For security purposes, please check the contents of collect_env.py before running it.
python collect_env.py
```

 - PyTorch Version (e.g., 1.0):
 - OS (e.g., Linux):
 - How you installed PyTorch (`conda`, `pip`, source):
 - Build command you used (if compiling from source):
 - Python version:
 - CUDA/cuDNN version:
 - GPU models and configuration:
 - Any other relevant information:

## Additional context

<!-- Add any other context about the problem here. -->


cc @ezyang
Repository: PowerToys
Issue: Color Picker not working correctly with Touch / Stylus
Labels: Idea-Enhancement,Product-Color Picker,Planning-Consideration

### Microsoft PowerToys version

0.35.0

### Running as admin

- [x] Yes

### Area(s) with issue?

ColorPicker

### Steps to reproduce

1. Launch color picker
2. Use stylus of Tablet PC to move cursor

### ✔️ Expected Behavior

The overlay should move the same way as if using a mouse

### ❌ Actual Behavior

The overlay stays at the position it was launched at.
Video: https://streamable.com/9hllki

### Other Software

_No response_
Repository: pytorch
Issue: unsafe_reclaim_from_nonowning is not that unsafe
Labels: module: internals,module: bootcamp,triaged

@dzhulgakov added this intrusive ptr method in #17190 and named it unsafe, but I don't think it's actually unsafe.  Assuming that the nonowning reference is live (which one generally assumes in these cases), it's not possible to mess up the refcount because the returned intrusive ptr will account for handling the decrement. It's basically `enable_shared_from_this`. If people agree then we should rename this.

cc @ezyang @bhosmer @smessmer @ljk53 @bdhirsh @ailzhang
Repository: pytorch
Issue: Add compute_residuals flag for torch.linalg.lstsq
Labels: triaged,enhancement,module: numpy,module: linear algebra

## 🐛 Bug

<!-- A clear and concise description of what the bug is. -->

I think we should add to `torch.linalg.lstsq` support for a "compute_residuals={True, False}" keyword argument and, if False, return an empty "residuals" tensor but, if True, compute it.

SciPy and NumPy both have `linalg.lstsq` that returns a tuple (solution, residuals, rank, singular_values). In PyTorch we have [`torch.linalg.lstsq`](https://pytorch.org/docs/master/generated/torch.linalg.lstsq.html#torch.linalg.lstsq) aiming at NumPy compatibility.
SciPy and NumPy operate only on non-batched input and return `residuals` as an empty array with shape (0,) if `rank(A) != n` for the input matrix A.
In PyTorch, the batched input is also supported and some matrices in the batch can have `rank(A_i) == n` while others could have a different rank.
In https://github.com/pytorch/pytorch/pull/54722 it was initially proposed to fill the residuals with `inf` for corresponding matrices with `rank != n`. Currently that PR computes the residuals only if all matrices in the batch have `rank==n`.

Residual is available as a byproduct of the LAPACK calls after some post-processing (abs and pow are fast element-wise operations). Raw residual is available if `"gels"` driver is used for any input and only for `rank==n` inputs if `"gelss"`, `"gelsd"` drivers are used. So for other cases calculating the residual would require matrix-matrix multiplication and then calculating the norm, I think it's an unnecessarily expensive procedure, and it's not immediately clear we should do that.

## Additional context

<!-- Add any other context about the problem here. -->
The discussion about the "residuals" tensor content started in the original `torch.linalg.lstsq` PR. See https://github.com/pytorch/pytorch/pull/49093#issuecomment-762771848.


cc @jianyuh @nikitaved @pearu @mruberry @heitorschueroff @walterddr @IvanYashchuk @xwang233 @rgommers @Lezcano
Repository: neovim
Issue: Concealed text causes line to wrap before window width
Labels: enhancement,bug-vim,complexity:high,display

<!-- Before reporting: search existing issues and check the FAQ. -->

- nvim --version
```
NVIM v0.4.4
Build type: Release
LuaJIT 2.1.0-beta3
Compilation:
Compiled by _nixbld2

Features: +acl +iconv +tui
```

- OS: Macos X Catalina v10.15.7
- Terminal emulator: iterm2
- $TERM: xterm-256color

Actually this issue is already marked wontfix in vim (https://github.com/vim/vim/issues/260), but I was wondering if it was possible to fix it in nvim…


### Steps to reproduce using `nvim -u NORC`

```
nvim -u NORC
reduce the window to a small width (like 80)
write "The quick fox jumps over the lazy dog." 2 or 3 times
:setlocal conceallevel=3
:syn match Foo /brown/ conceal
```

### Actual behaviour
The line is cut before the end of the window, as shown in picture
<img width="892" alt="Screen Shot 2021-04-20 at 5 09 38 PM" src="https://user-images.githubusercontent.com/67050900/115421307-1faa0a00-a1fc-11eb-8ffc-31dbd11f0def.png">

### Expected behaviour
I would expect line wrapping to be aware of conceal and wrap at the end of the window
Repository: pytorch
Issue:  Sparse tensor CSR layout for CUDA
Labels: module: sparse,module: cuda,triaged

## 🚀 Feature

Sparse tensor CSR layout for CUDA

## Motivation

Recently Implementation of compressed sparse row (CSR)  #50937 layout  was landed, however it still misses CUDA support.

## Status 
- [x] [#59012](https://github.com/pytorch/pytorch/pull/59012) CUDA support in the CSR layout: matvec
   Related issues
   - [ ] Issue: support auto generation of device check for sparse tensors #59058
   - [ ] Issue: Add 64-bit indices support to csrmm2 #58899
   - [ ] Issue: Relaxing constraints to s_addmm_out_sparse_dense_cuda_worker #59099
   - [ ] Issue: Use of storage_offset is not needed in add_out_dense_sparse_csr_cuda #59101
   - [ ] Issue: Data access pattern in the loop in add_out_dense_sparse_csr_cuda could be pretty bad #59104
   - [ ] Issue: MKL csr matmul issue #58770
- [x] [#59011](https://github.com/pytorch/pytorch/pull/59011) CSR layout: CPU addmm Fix
- [x] [#59010](https://github.com/pytorch/pytorch/pull/59010) CUDA support in the CSR layout: sparse_to_dense/add_sparse_csr

### Other CSR issues

 CSR sparse tensor: ops not implemented yet
- [x] Addition of sparse CSR tensors is not yet implemented https://github.com/pytorch/pytorch/issues/59060
- [ ] addmm_
- [ ] bmm
- [x] [torch.sparse.mm]: sparse@sparse

Other issues reported before:
- [ ] COO to CSR conversion https://github.com/pytorch/pytorch/issues/57381
- [ ] Inefficient conversion between COO and CSR formats https://github.com/pytorch/pytorch/issues/56959
- [ ] Avoid no-op suggest_memory_format call in SparseCsrTensorImpl https://github.com/pytorch/pytorch/issues/56697  

## Additional context
CSR tensor support in PyTorch
https://pearu.github.io/csr_tensor_support.html



cc @ngimel @aocsa @nikitaved @pearu @mruberry
Repository: storybook
Issue: Angular with inline stories interferes with `keypress` binding
Labels: bug,angular

**Describe the bug**
I have components that call a method when an element receives a `keypress`. For instance, `<button (keypress)='foo($event)'>`. When enabling inline stories, the keypress event doesn't trigger for certain keys. Spacebar works, but Enter/Return doesn't. If I disable inline stories and go back to iframes, everything works as expected.

Note: I am still pinned to 6.2.0-rc.7 due to #14193

**System**
System:
    OS: macOS 10.15.7
    CPU: (12) x64 Intel(R) Core(TM) i7-8850H CPU @ 2.60GHz
  Binaries:
    Node: 14.16.0 - ~/.nvm/versions/node/v14.16.0/bin/node
    npm: 7.7.6 - ~/.../node_modules/.bin/npm
  Browsers:
    Chrome: 89.0.4389.128
    Edge: 90.0.818.42
    Firefox: 87.0
    Safari: 14.0.3
  npmPackages:
    @storybook/addon-a11y: 6.2.0-rc.7 => 6.2.0-rc.7
    @storybook/addon-backgrounds: 6.2.0-rc.7 => 6.2.0-rc.7
    @storybook/addon-docs: 6.2.0-rc.7 => 6.2.0-rc.7
    @storybook/addon-postcss: ^2.0.0 => 2.0.0
    @storybook/addon-viewport: 6.2.0-rc.7 => 6.2.0-rc.7
    @storybook/addons: 6.2.0-rc.7 => 6.2.0-rc.7
    @storybook/angular: 6.2.0-rc.7 => 6.2.0-rc.7
    @storybook/theming: 6.2.0-rc.7 => 6.2.0-rc.7
Repository: pytorch
Issue: [torchdeploy] ar: _bz2module.o: No such file or directory 
Labels: triaged,module: deploy

If you build PyTorch with `USE_DEPLOY=ON` on a system that doesn't have bzip2/lzma devel headers available, the  cpython implementation will not be built with _bz2module.o. However, torchdeploy's cmake unconditionally assumes this (and other conditionally built object files) are available, and you'll fail ar with an obscure error.

cc @wconstab
Repository: godot
Issue: VisualScriptNode's do not completely initiate 
Labels: bug,topic:editor,topic:visualscript

<!-- Please search existing issues for potential duplicates before filing yours:
https://github.com/godotengine/godot/issues?q=is%3Aissue
-->

**Godot version:**
3.3 rc9


**OS/device including version:**
win 10 gles3


**Issue description:**
When creating new VisualScript nodes they do not completely instantiate


**Steps to reproduce:**
Create new project.
Create new Visual Script
RMB click, select call or call_defered
reboot project
https://user-images.githubusercontent.com/20573784/115431964-2d648d00-a206-11eb-8b93-6af721214c1a.mov



**Minimal reproduction project:**
[error VS call.zip](https://github.com/godotengine/godot/files/6345155/error.VS.call.zip)

![image](https://user-images.githubusercontent.com/20573784/115866179-9c75f780-a439-11eb-8d70-09e01feabe61.png)

Possible related
#38435
Repository: flutter
Issue: Makes a convenient page class for PageRouteBuilder
Labels: c: new feature,framework,f: routes,P2,team-framework,triaged-framework

We had MaterialPage class for MaterialPageRoute, and CupertinoPage class for CupertinoPageRoute, we should come up with a convenient page class for PageRouteBuilder. We don't have this before because we can't figure out how to handle the scope issue when using page class. The page class can't take in widget builder, otherwise it is very easy to break the widget tree during the page transition.
Repository: flutter
Issue: ios_add2app_life_cycle isn't running anywhere
Labels: a: tests,team,a: existing-apps,P2,team-ios,triaged-ios

This test relanded with #49368 but it doesn't seem to be running anywhere.
Repository: youtube-dl
Issue: request: allow lowest bitrate specification
Labels: request

## Checklist

- [x] I'm reporting a feature request
- [x] I've verified that I'm running youtube-dl version **2021.04.17**
- [x] I've searched the bugtracker for similar feature requests including closed ones (referenced below)

Currently it's not possible to specify saving format (without manual step with reading `-F` output) to get smallest file size with specific resolution.
Using just `worst` is not enough for that, as far as I see from #28307 
I do it manually for now, so presence of something like `worstabr` / `worstvbr` / `worsttbr` (meaning just lowest available values) would be very helpful.

Similar: #24246, #20606, #12188

`best` bitrate specifiers might be also reasonable: related #17259, #26633
Repository: godot
Issue: Code completion does not suggest owner properties, methods etc defined in the script
Labels: bug,topic:gdscript,topic:editor

<!-- Please search existing issues for potential duplicates before filing yours:
https://github.com/godotengine/godot/issues?q=is%3Aissue
-->

**Godot version:**
<!-- Specify commit hash if using non-official build. -->
`3.2.3 stable`, `3.3rc`

**OS/device including version:**
<!-- Specify GPU model, drivers, and the backend (GLES2, GLES3, Vulkan) if graphics-related. -->
Linux

**Issue description:**
<!-- What happened, and what was expected. -->

https://user-images.githubusercontent.com/16458555/115446981-649c6380-a231-11eb-8e5d-fb186db464c9.mp4

Here you can see that code completion works for `get_owner()` but not for `owner`.

**Steps to reproduce:**
create a scene with 2 nodes and attach scripts to them
- for "root" node:
```gdscript
extends Node #or any other, doesn't matter
var a = 1
```

- for child node:
```gdscript
extends Node

func _ready():
	owner.a
```
As you can see, when typing `owner` the code completion doesn't suggest `a`, and for `get_owner()` it works

**Minimal reproduction project:**
<!-- A small Godot project which reproduces the issue. Drag and drop a zip archive to upload it. -->
Repository: flutter
Issue: [video_player] Scrubbing video that has ended
Labels: p: video_player,package,team-ecosystem,has reproducible steps,P2,found in release: 2.5,found in release: 2.6,triaged-ecosystem

<h1>Issue</h1>
I have encountered bug while scrubbing video that has ended, if you try to scrub, it won't change isPlaying variable. That means it will stay false until user press play button in the middle of the screen. As you can see on the video, bug will appear only when looping is disabled also video and audio will play in the background also VideoProgressIndicator won't move from the place it was scrubbed until video finishes. 
<h2>Steps to reproduce</h2>

1.  Clone and open video_player Example 
2. Comment line "_controller.setLooping(true)" inside of init_state _BumbleBeeRemoteVideoState Widget
3. Let video end and then try scrubbing

<h2>Video</h2>

https://user-images.githubusercontent.com/70284063/115444768-4cb6e680-a215-11eb-97a7-bfa1dc13f05a.mov



<h2>Logs</h2>

```
Doctor summary (to see all details, run flutter doctor -v):
[✓] Flutter (Channel stable, 2.0.5, on macOS 11.2.3 20D91 darwin-x64, locale
    en-GB)
[✓] Android toolchain - develop for Android devices (Android SDK version 30.0.3)
[✓] Xcode - develop for iOS and macOS
[✓] Chrome - develop for the web
[✓] Android Studio (version 4.1)
[✓] VS Code (version 1.55.2)
[✓] Connected device (2 available)

• No issues found!
```
Repository: pytorch
Issue: [cpp op] TORCH_LIBRARY schema doesn't respect keyword only
Labels: module: cpp-extensions,module: cpp,triaged

## 🐛 Bug

Say you have a cpp extension defining ops like below
```cpp
TORCH_LIBRARY(cdf_ops, m) {
    m.def("f(Tensor x, *, bool ha=True) -> Tensor", &f);
}
```

After compiling you will find that you can still call `XXX.f(x, False)`.

This is at least true on `'1.9.0.dev20210315'`.

cc @yf225 @glaringlee
Repository: pytorch
Issue: Can't deepcopy memory format objects
Labels: triaged,module: memory format

```
import torch

class Foo(torch.nn.Module):
  def __init__(self):
    super().__init__()
    self.mem_format = torch.channels_last

  def forward(self, x):
    return x.contiguous(memory_format=self.mem_format)


f = Foo()
x = torch.randn(5, 3, 224, 224)
print(f(x).is_contiguous(memory_format=torch.channels_last))
"""
True
"""

import copy
copied = copy.deepcopy(f)
"""
TypeError                                 Traceback (most recent call last)
<ipython-input-3-8bb621468625> in <module>()
      1 import copy
----> 2 copied = copy.deepcopy(f)

4 frames
/usr/lib/python3.7/copy.py in deepcopy(x, memo, _nil)
    178                     y = x
    179                 else:
--> 180                     y = _reconstruct(x, memo, *rv)
    181 
    182     # If is its own copy, don't memoize.

/usr/lib/python3.7/copy.py in _reconstruct(x, memo, func, args, state, listiter, dictiter, deepcopy)
    279     if state is not None:
    280         if deep:
--> 281             state = deepcopy(state, memo)
    282         if hasattr(y, '__setstate__'):
    283             y.__setstate__(state)

/usr/lib/python3.7/copy.py in deepcopy(x, memo, _nil)
    148     copier = _deepcopy_dispatch.get(cls)
    149     if copier:
--> 150         y = copier(x, memo)
    151     else:
    152         try:

/usr/lib/python3.7/copy.py in _deepcopy_dict(x, memo, deepcopy)
    239     memo[id(x)] = y
    240     for key, value in x.items():
--> 241         y[deepcopy(key, memo)] = deepcopy(value, memo)
    242     return y
    243 d[dict] = _deepcopy_dict

/usr/lib/python3.7/copy.py in deepcopy(x, memo, _nil)
    167                     reductor = getattr(x, "__reduce_ex__", None)
    168                     if reductor:
--> 169                         rv = reductor(4)
    170                     else:
    171                         reductor = getattr(x, "__reduce__", None)

TypeError: can't pickle torch.memory_format objects
"""

cc @VitalyFedyunin @jamesr66a @ppwwyyxx
Repository: create-react-app
Issue: Proxy not working after deployed in IIS
Labels: stale,needs triage

Hi,

I have used create react app to deploy app, where I'm using the proxy to call API, it works in local mode whereas after deployed to IIS it's not working, it results in generic HTML not json response

Not sure what is the issue.
Repository: flutter
Issue: Hsl adjustment specifically for 6 different colors
Labels: c: new feature,framework,would be a good package,a: images,c: proposal,P3,team-framework,triaged-framework

I want to provide specific hue, saturation, lightness adjustment for 6 different color tones in a photo. I couldn't do this in flutter. For one color, it is partially done with the ColorFiltered matrix method, but I could not do it for 6 different shades at the same time.
If I could not explain, I want to give an example:
Let's say red, orange, yellow colors on a photo.
I just want to adjust the saturation value of the area with red tint, I want to be able to adjust the orange and yellow separately.

This hsl feature works very well in applications such as lightroom, vsco. I could not do it in Flutter, I looked at the examples and libraries and saw that it was insufficient. I asked the Flutter developers for support and they couldn't figure it out, so I wanted to post here. I want help how can I solve this issue.
Repository: flutter
Issue: Ensure resident_runner cleanup prevents any new device commands (restart) or is delayed/cancels any pending requests
Labels: c: crash,tool,P2,team-tool,triaged-tool

There are a few crash reports that appear to be bad states in the resident runner: Either a hot reload/restart command was triggered after the device shutdown started, or a pending restart command was interrupted by a shutdown command.

We should ensure that the tool prevents any new commands from being issued to a device while a shutdown is in progress.

This manifests as an NPE on the devFS, which is nulled out after shutting down.
Repository: deno
Issue: Native HTTP detect protocol (HTTP/2 vs. HTTP/1.1)
Labels: feat,public API

There should be some mechanism in the Native HTTP server to detect if a served HTTP connection/request is HTTP/1.1 or HTTP/2.  Specifically when formulating a response, it is important for a server code to understand if it is HTTP/1.1 or HTTP/2 to determine how to send back large files.  In HTTP/1.1 the server may want to send back the data as "chunked" which HTTP/2 does not support, but without that information available, the server cannot determine what is appropriate.
Repository: TypeScript
Issue: JSDoc @type does not attach to for loop variable declarations
Labels: Suggestion,Awaiting More Feedback,Needs Investigation,Rescheduled

# Bug Report

From what I could tell, this is a common pattern with JSDoc used to properly document the type of a loop variable. It does not seem to work in VSCode.

### 🔎 Search Terms

jsdoc for loop type

### 🕗 Version & Regression Information

- This is the behavior in every version I tried, and I reviewed the FAQ for entries about JSDoc.

### ⏯ Playground Link

https://www.typescriptlang.org/play?#code/GYewTgBAFA9AVHCABALgTwA4FMIG8ASAKgLIAyAogDZYC2WAdigL4RwwQDGI9AzihDhDAIAExAcArnUYA6AEYgRaGQEcJWMGgDKWahxTgAgpUpQA5DJRY+ZgJS28AKAguBMvmmoyRASx4ZKAEM0CABeCDN6biwzAG5HJiA

### 💻 Code

```js
for (/** @type {HTMLElement} */ const e of document.body.querySelectorAll('.test')) {
    e.style.display = 'none';
}
```

### 🙁 Actual behavior

`e` is typed as Element

### 🙂 Expected behavior

`e` should be typed as HTMLElement, as I have overridden it via @type.

As an example, if I were to change the code to this:

```js
/** @type {HTMLElement} */ const e = document.body.querySelectorAll('.test');
```

VSCode correctly picks up that I'm wishing to override `e` as an HTMLElement (and complains about missing interface implementations, but, that's not the issue here - in fact that's expected!)