sharjeelyunus/github-issues-dataset huggingface dataset:
Repository: pytorch
Issue: [perf] 10x improvement when doing `x.sum(-1)` manually
Labels: module: performance,triaged,module: reductions

## 🐛 Bug

See repro code.

## To Reproduce

```python
import torch
import time

torch.set_num_threads(1)
REPEAT_COUNT = 100
n = 2
x = torch.rand(1024*1024, n)

print(f'ADD {n} with sum')
start = time.time()
for _ in range(REPEAT_COUNT):
  y = x.sum(-1)
print(time.time() - start) # 2s

print(f'ADD {n} with python')
start = time.time()
for _ in range(REPEAT_COUNT):
  y = x.select(-1, 0) + x.select(-1, 1)
print(time.time() - start) # 0.13s
```

## Expected behavior

I expect `x.sum(-1)` to be at least as fast as doing it manually

## Environment

Running on Google Colab
```
PyTorch version: 1.8.1+cu101
Is debug build: False
CUDA used to build PyTorch: 10.1
ROCM used to build PyTorch: N/A

OS: Ubuntu 18.04.5 LTS (x86_64)
GCC version: (Ubuntu 7.5.0-3ubuntu1~18.04) 7.5.0
Clang version: 6.0.0-1ubuntu2 (tags/RELEASE_600/final)
CMake version: version 3.12.0

Python version: 3.7 (64-bit runtime)
Is CUDA available: False
CUDA runtime version: 11.0.221
GPU models and configuration: Could not collect
Nvidia driver version: Could not collect
cuDNN version: Probably one of the following:
/usr/lib/x86_64-linux-gnu/libcudnn.so.7.6.5
/usr/lib/x86_64-linux-gnu/libcudnn.so.8.0.4
/usr/lib/x86_64-linux-gnu/libcudnn_adv_infer.so.8.0.4
/usr/lib/x86_64-linux-gnu/libcudnn_adv_train.so.8.0.4
/usr/lib/x86_64-linux-gnu/libcudnn_cnn_infer.so.8.0.4
/usr/lib/x86_64-linux-gnu/libcudnn_cnn_train.so.8.0.4
/usr/lib/x86_64-linux-gnu/libcudnn_ops_infer.so.8.0.4
/usr/lib/x86_64-linux-gnu/libcudnn_ops_train.so.8.0.4
HIP runtime version: N/A
MIOpen runtime version: N/A

Versions of relevant libraries:
[pip3] numpy==1.19.5
[pip3] torch==1.8.1+cu101
[pip3] torchsummary==1.5.1
[pip3] torchtext==0.9.1
[pip3] torchvision==0.9.1+cu101
[conda] Could not collect
```

## Additional context

This happens on server CPU, but also on arm64 CPU (int8).


cc @VitalyFedyunin @ngimel @heitorschueroff
Repository: pytorch
Issue: [perf] 10x improvement on element-wise operations with manual broadcast
Labels: module: performance,triaged,module: TensorIterator

## 🐛 Bug

I suspect this is due to how the tensor is iterated on, which doesn't allow to use vectorized instructions?
NOTE: The difference is the most extreme with `n=2`, but still exists for higher values of `n` (up to ~`n=128`)
## To Reproduce

```python
import torch
import time

torch.set_num_threads(1)
REPEAT_COUNT = 100
n = 2
x = torch.rand(1, 32, 32, n)
y = torch.rand(1024, 1, 1, n)

print('SUB with bcast from pytorch')
start = time.time()
for _ in range(REPEAT_COUNT):
  _ = x - y
print(time.time() - start) # 1.36s

print('SUB with manual (partial) broadcast')
start = time.time()
for _ in range(REPEAT_COUNT):
  _ = x - y.repeat(1, 1, 32, 1)
print(time.time() - start) # 0.15s
```

## Expected behavior

Broadcast done by pytorch should be at least as fast as broadcast done manually

## Environment

Running on Google Colab
```
PyTorch version: 1.8.1+cu101
Is debug build: False
CUDA used to build PyTorch: 10.1
ROCM used to build PyTorch: N/A

OS: Ubuntu 18.04.5 LTS (x86_64)
GCC version: (Ubuntu 7.5.0-3ubuntu1~18.04) 7.5.0
Clang version: 6.0.0-1ubuntu2 (tags/RELEASE_600/final)
CMake version: version 3.12.0

Python version: 3.7 (64-bit runtime)
Is CUDA available: False
CUDA runtime version: 11.0.221
GPU models and configuration: Could not collect
Nvidia driver version: Could not collect
cuDNN version: Probably one of the following:
/usr/lib/x86_64-linux-gnu/libcudnn.so.7.6.5
/usr/lib/x86_64-linux-gnu/libcudnn.so.8.0.4
/usr/lib/x86_64-linux-gnu/libcudnn_adv_infer.so.8.0.4
/usr/lib/x86_64-linux-gnu/libcudnn_adv_train.so.8.0.4
/usr/lib/x86_64-linux-gnu/libcudnn_cnn_infer.so.8.0.4
/usr/lib/x86_64-linux-gnu/libcudnn_cnn_train.so.8.0.4
/usr/lib/x86_64-linux-gnu/libcudnn_ops_infer.so.8.0.4
/usr/lib/x86_64-linux-gnu/libcudnn_ops_train.so.8.0.4
HIP runtime version: N/A
MIOpen runtime version: N/A

Versions of relevant libraries:
[pip3] numpy==1.19.5
[pip3] torch==1.8.1+cu101
[pip3] torchsummary==1.5.1
[pip3] torchtext==0.9.1
[pip3] torchvision==0.9.1+cu101
[conda] Could not collect
```

## Additional context

This happens on server CPU, but also on arm64 CPU (int8).


cc @VitalyFedyunin @ngimel
Repository: transformers
Issue: Distil BART for text simplification
Labels: New model

# 🌟 New model addition

## Model description
Not completed yet. I will notify very soon when it is done.
If anyone has any leads regarding the same issue, please share. It would be great help.
Repository: create-react-app
Issue: React Development Server takes a long time to startup
Labels: needs triage,issue: bug report

This is my package.json file:
{
  "name": "client",
  "version": "0.1.0",
  "private": true,
  "dependencies": {
    "@testing-library/jest-dom": "^5.12.0",
    "@testing-library/react": "^11.2.6",
    "@testing-library/user-event": "^12.8.3",
    "axios": "^0.21.1",
    "react": "^17.0.2",
    "react-dom": "^17.0.2",
    "react-router-dom": "^5.2.0",
    "react-scripts": "4.0.3",
    "uuid": "^8.3.2",
    "web-vitals": "^1.1.1"
  },
  "scripts": {
    "start": "react-scripts start",
    "build": "react-scripts build",
    "test": "react-scripts test",
    "eject": "react-scripts eject"
  },
  "eslintConfig": {
    "extends": [
      "react-app",
      "react-app/jest"
    ]
  },
  "browserslist": {
    "production": [
      ">0.2%",
      "not dead",
      "not op_mini all"
    ],
    "development": [
      "last 1 chrome version",
      "last 1 firefox version",
      "last 1 safari version"
    ]
  }
}
Repository: pytorch
Issue: Pruners' compute_mask returns tensors with dtypes that are not consistent with each other
Labels: module: nn,triaged,module: pruning

## 🐛 Bug

Pruners' `compute_mask` returns tensors with dtypes that are not consistent with each other.

## To Reproduce

```python
import torch
from torch.nn.utils.prune import L1Unstructured, LnStructured

weights = torch.tensor([[1, 2, 3, 4], [5, 6, 7, 8]], dtype=torch.float64)
default_mask = torch.tensor([[1, 1, 1, 0], [1, 1, 0, 1]])

# matches the dtype of `default_mask `
l1_pruner = L1Unstructured(amount=2)
print(l1_pruner.compute_mask(weights, default_mask).dtype)
# torch.int64

# matches the dtype of `weights`
ln_pruner = LnStructured(amount=1, n=2)
print(ln_pruner.compute_mask(t, default_mask).dtype)
# torch.float64
```
<!-- If you have a code sample, error messages, stack traces, please provide it here as well -->

## Expected behavior

I expect `compute_mask` to always match the dtype of `default_mask`.

## Environment

PyTorch version: 1.9.0a0+git42d073a
Is debug build: False
CUDA used to build PyTorch: 11.2
ROCM used to build PyTorch: N/A

OS: Ubuntu 20.04.2 LTS (x86_64)
GCC version: (Ubuntu 9.3.0-17ubuntu1~20.04) 9.3.0
Clang version: Could not collect
CMake version: version 3.20.1

Python version: 3.8 (64-bit runtime)
Is CUDA available: True
CUDA runtime version: 11.2.152
GPU models and configuration: GPU 0: NVIDIA GeForce GTX 1080 Ti
Nvidia driver version: 465.19.01
cuDNN version: Probably one of the following:
/usr/lib/x86_64-linux-gnu/libcudnn.so.8.2.0
/usr/lib/x86_64-linux-gnu/libcudnn_adv_infer.so.8.2.0
/usr/lib/x86_64-linux-gnu/libcudnn_adv_train.so.8.2.0
/usr/lib/x86_64-linux-gnu/libcudnn_cnn_infer.so.8.2.0
/usr/lib/x86_64-linux-gnu/libcudnn_cnn_train.so.8.2.0
/usr/lib/x86_64-linux-gnu/libcudnn_ops_infer.so.8.2.0
/usr/lib/x86_64-linux-gnu/libcudnn_ops_train.so.8.2.0
HIP runtime version: N/A
MIOpen runtime version: N/A

Versions of relevant libraries:
[pip3] numpy==1.20.2
[pip3] torch==1.9.0a0+git42d073a
[conda] magma-cuda112             2.5.2                         1    pytorch
[conda] mkl                       2021.2.0           h726a3e6_389    conda-forge
[conda] mkl-include               2021.2.0           h726a3e6_389    conda-forge
[conda] numpy                     1.20.2           py38h9894fe3_0    conda-forge
[conda] pytest-pytorch            0.2.0              pyh44b312d_0    conda-forge
[conda] torch                     1.9.0a0+git42d073a           dev_0    <develop>

cc @albanD @mruberry @jbschlosser
Repository: pytorch
Issue: After tracing, the device of the named buffer is still `cuda` although it was moved to `cpu `
Labels: oncall: jit

## 🐛 Bug

After tracing, the device of the named buffer is still `cuda` although it was moved to `cpu `

## To Reproduce

Steps to reproduce the behavior:
```
import torch
import torch.nn as nn

class MyModule(nn.Module):
    def __init__(self):
        super().__init__()
        self.register_buffer("aa", torch.tensor([1]))

    def forward(self, b):
        self.aa = self.aa.cpu()
        return self.aa + b

myModule = MyModule().cuda()

input = torch.tensor(2)

a = torch.jit.trace(myModule, (torch.tensor(1)))
print(a(input))
print(dict(a.named_buffers()))
```
Output:
========
print(a(input))
>> 
tensor([3])

print(dict(a.named_buffers()))
>>
{'aa': tensor([1], device='cuda:0')} # ----> This needs to be on CPU 

print(a.graph)
>>
graph(%self : __torch__.MyModule,
      %b : Long(requires_grad=0, device=cpu)):
  %15 : Tensor = prim::GetAttr[name="aa"](%self)
  %5 : int = prim::Constant[value=4]() # repro.py:10:0
  %6 : int = prim::Constant[value=0]() # repro.py:10:0
  %7 : Device = prim::Constant[value="cpu"]() # repro.py:10:0
  %8 : NoneType = prim::Constant()
  %9 : bool = prim::Constant[value=0]() # repro.py:10:0
  %10 : bool = prim::Constant[value=0]() # repro.py:10:0
  %11 : NoneType = prim::Constant()
  %12 : Long(1, strides=[1], requires_grad=0, device=cpu) = aten::to(%15, %5, %6, %7, %8, %9, %10, %11) # repro.py:10:0
  %13 : int = prim::Constant[value=1]() # repro.py:11:0
  %14 : Long(1, strides=[1], requires_grad=0, device=cpu) = aten::add(%12, %b, %13) # repro.py:11:0
  return (%14)

<!-- If you have a code sample, error messages, stack traces, please provide it here as well -->

## Expected behavior

The named buffer should be on CPU 
{'aa': tensor([1]}

cc @gmagogsfm
Repository: TypeScript
Issue: The ability to refactor implicit types to explicit types in typescript
Labels: Suggestion,Awaiting More Feedback

<!-- ⚠️⚠️ Do Not Delete This! feature_request_template ⚠️⚠️ -->
<!-- Please read our Rules of Conduct: https://opensource.microsoft.com/codeofconduct/ -->
<!-- Please search existing issues to avoid creating duplicates. -->

<!-- Describe the feature you'd like. -->

```ts
export type SomethingComplex = ReturnType<typeof GetSomethingComplex>
```

I like to rely on implicit return types, especially in the beginning when I'm exploring what I'm creating. But when you have implicit models and your idea has become more defined, it might be wise to have your logic follow explicit models rather than implicit models emerging from logic.

So I propose a refactoring tool that allows you to convert implicit types to explicit types.
Repository: pytorch
Issue: get_future() should be documented once it is enabled for gloo, mpi backends
Labels: oncall: distributed,triaged

## 📚 Documentation

We currently support `get_future` for NCCL backend only. @mrshenli in https://github.com/pytorch/pytorch/pull/56427 mentioned it would be good to document how `get_future()` behaves for various collectives, we should do this once support for all backends is added. Currently this is not documented and only mentioned as part of gradient comm. hooks. 


cc @pietern @mrshenli @pritamdamania87 @zhaojuanmao @satgera @rohan-varma @gqchen @aazzolini @osalpekar @jiayisuse @agolynski @SciPioneer @H-Huang @mrzzd @cbalioglu @gcramer23
Repository: godot
Issue: ` Incorrect C++ source stack trace file:line format` when trying to open C++ source on Github in debugger
Labels: bug,topic:editor

**Godot version:**
3.4.beta.custom_build. 6abf571d7
CC @Calinou 


**OS/device including version:**
Ubuntu 20.04


**Issue description:**
Running scene with code
```
var needed_hexes2: int = max(4, 3 * 4* (pow(5 / 100.0, 5) * 0.75))
```
cause showing warning 
```
Narrowing conversion(float is converted to int)
```
and after that, clicking with right mouse button and `open C++ source on Github`, shows this error
```
 Incorrect C++ source stack trace file:line format (please report).
```
so I report it.
Repository: godot
Issue: When creating multiple built-in scripts without saving the scene, only one can be opened
Labels: bug,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. -->
758bccf / 3.3

**Issue description:**
<!-- What happened, and what was expected. -->
![rm0sUQtkll](https://user-images.githubusercontent.com/2223172/117211565-779a6080-adf9-11eb-8a7b-d26f3f641802.gif)

**Steps to reproduce:**
1. Have a scene with at least 2 nodes
2. Add built-in script to both of them
3. Try opening both in the script editor
Repository: flutter
Issue: Reason about secondary vsync callback side effects on non-Fuchsia platforms.
Labels: engine,P2,team-engine,triaged-engine

The `VsyncWaiter::ScheduleSecondaryCallback` mechanism was added to service use-cases where non-rendering related workloads tied to vsync needed to be handled. The specific use case was the instrumentation of time taken from pointer event acquisition to the end of rendering of the next frame.

Since pointer event input and frame scheduling were orthogonal concerns (the scheduling of the frame would be decided by the gesture recognizer running in Dart code), it was initially decided that this mechanism would be backed out. Also, unintended consequence of this mechanism was the unnecessary arming of the vsync waiter on non-Fuchsia platforms.

After [further discussion](https://github.com/flutter/engine/pull/25787#issuecomment-829488663) (see additional reasoning in linked PRs and the Buganizer thread) with @farchond, satisfying the specific case of instrumentation was hard to do without the current mechanism.

Since this mechanism is still in place, it effect on existing embedders (iOS, Android and all other custom embedder) must be reasoned about and tested. Specifically, the following:

* Pointer events from the platform don't idly arm the vsync waiter.
* Rendering workloads from pointer events without the UI isolate explicitly requesting the said workloads must be impossible.

At least the first case is not true today on non-Fuchsia embedders.
Repository: TypeScript
Issue: Consider splitting `dom` lib events out into separate lib for nodejs use
Labels: Suggestion,In Discussion,Experimentation Needed,Rescheduled

# lib Update Request


## Configuration Check

Does not apply.

## Missing / Incorrect Definition

Does not apply.

## Sample Code

Does not apply.

## Documentation Link

NodeJS recently implementation most of the DOM event API https://nodejs.org/dist/latest-v16.x/docs/api/events.html#events_eventtarget_and_event_api I'm currently in the process of implementing these in the node typings but this is resulting in me practically copy/pasting type definitions, we should consider splitting them out so we can re-use them.
Repository: flutter
Issue: animator Render is called without BeginFrame in `flutter_tester` configuration
Labels: engine,P2,team-engine,triaged-engine

This wasn't noticed in real apps.
Repository: vscode
Issue: Fails To Copy Large Text
Labels: bug,editor-clipboard

- VS Code Version: 1.55.2
- OS Version: Kubuntu 20.04 (Linux)

Steps to Reproduce:

1. Open a very large css file (i.e. 100k lines, 2.15 million chars)
2. Select All
3. Copy
4. Switch to another text editor (i.e. KWrite)
5. Paste
6. See that nothing gets pasted

Does this issue occur when all extensions are disabled?: Yes

Notes:

* This is definitely not a limitation of the system clipboard; if I open the exact same CSS file in KWrite or another text editor, I can copy it in its entirety without issue.
* If I use a clipboard monitor (i.e. CopyQ), I observe that nothing is added to the clipboard when I try to "copy."
* This does not occur on VS Code for Windows (only on Linux).
* If I try to copy just a small subset of the file, it works just fine - i.e. the first 10k lines or so.  There seems to be some length over which it will not copy.
* No error message of any kind is shown; it simply fails to copy the text.  If there is some limitation to how much text it will let you copy, it should at least report an error if you attempt to copy more.
Repository: electron
Issue: [Feature Request]: Provide ability to hide taskbar preview of window
Labels: enhancement :sparkles:

### Preflight Checklist

- [X] I have read the [Contributing Guidelines](https://github.com/electron/electron/blob/master/CONTRIBUTING.md) for this project.
- [X] I agree to follow the [Code of Conduct](https://github.com/electron/electron/blob/master/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

I'd like to be able to hide the taskbar preview of a BrowserWindow when hovering over the taskbar icon.

### Proposed Solution

Add an API or configuration to `BrowserWindow` to allow turning off the taskbar preview in Windows.

### Alternatives Considered

Can be done in my .NET process that runs alongside the Electron app via [`DwmSetWindowAttribute`](https://docs.microsoft.com/en-us/windows/win32/api/dwmapi/nf-dwmapi-dwmsetwindowattribute) + the `DWMWA_FORCE_ICONIC_REPRESENTATION` flag



### Additional Information

n/a
Repository: storybook
Issue: Jest Addon Improvment on the panel component. 
Labels: feature request,addon: jest

Regarding ` @storybook/addon-jest`, I would like to suggest two improvements: 

1. The `Panel` component on `./addons/jest/src/components/Panel.tsx`, allowing for contraction when multiple Test Result Panels are in display, this would allow the user to visualize only the test results relevant for his task in hand, this would result in an _Accordion_-like feel when you have test results from multiple files.
 2. On the same file but in the `SuiteTotals` component (or probably make a separate component for it), allow to display the file name from which the tests result where gather.
 
**Are you able to assist to bring the feature to reality?**
Yes I can.

**Additional context**
Add any other context or screenshots about the feature request here.

This is a screenshot of what I did inject stuff in to the _developer tools DOM inspector_ with some corrections done on a bitmap editor.  But more or less I am proposing something like this. 

![image](https://user-images.githubusercontent.com/6476691/117227702-f944bb00-ae06-11eb-90e9-502b66f3db6c.png)
Repository: TypeScript
Issue: More correct translations for "Function Expression" in lib/ko/diagnosticMessages.generated.json 
Labels: Suggestion,Experience Enhancement

# lib Update Request

## Configuration Check

Does not apply.

## Missing / Incorrect Definition

Does not apply.

## Sample Code

Does not apply.

## Documentation Link

Hi 🙌 It's talking about Translation into Korean.

Regarding the notation for "Function Expression", I think "함수 표현식" is a better expression.
As you can see in [MDN](https://developer.mozilla.org/ko/docs/Web/JavaScript/Reference/Operators/function), "Function Expression" is specified as "함수 표현식" rather than "함수 식".

When checked with a translator, the two seem to have the same meaning.
However, strictly speaking, it can be taken in a different meaning.
Repository: youtube-dl
Issue: [Artstation Learning] Add support for Artstation Learning
Labels: site-support-request

## Checklist

<!--
Carefully read and work through this check list in order to prevent the most common mistakes and misuse of youtube-dl:
- First of, make sure you are using the latest version of youtube-dl. Run `youtube-dl --version` and ensure your version is 2021.04.26. If it's not, see https://yt-dl.org/update on how to update. Issues with outdated version will be REJECTED.
- Make sure that all provided video/audio/playlist URLs (if any) are alive and playable in a browser.
- Make sure that site you are requesting is not dedicated to copyright infringement, see https://yt-dl.org/copyright-infringement. youtube-dl does not support such sites. In order for site support request to be accepted all provided example URLs should not violate any copyrights.
- Search the bugtracker for similar site support requests: http://yt-dl.org/search-issues. DO NOT post duplicates.
- Finally, put x into all relevant boxes (like this [x])
-->

- 

- [x] I'm reporting a new site support request
- [x] I've verified that I'm running youtube-dl version **2021.04.26**
- [x] I've checked that all provided URLs are alive and playable in a browser
- [x] I've checked that none of provided URLs violate any copyrights
- [x] I've searched the bugtracker for similar site support requests including closed ones


## Example URLs

- https://www.artstation.com/learning/courses/dqQ/character-design-masterclass-with-serge-birault/chapters/Rxn3/introduction
- https://www.artstation.com/learning/courses/PJo/intro-to-substance-designer-for-vfx/chapters/Wnar/course-intro


## Description

Artstation Learning has alot of free tutorials for art, 3d modeling, art for game development and design in general
its Free, it requires an account but you can create an Artstation account and use everything for free till 2022
i think when 2021 is over you have to pay for subscription but dont quote me on this one, idk

but its free for the rest of the 2021
Repository: pytorch
Issue: [Docs] nn.init._calculate_fan_in_and_fan_out()
Labels: module: docs,triaged

## 📚 Documentation

<!-- A clear and concise description of what content in https://pytorch.org/docs is an issue. If this has to do with the general https://pytorch.org website, please file an issue at https://github.com/pytorch/pytorch.github.io/issues/new/choose instead. If this has to do with https://pytorch.org/tutorials, please file an issue at https://github.com/pytorch/tutorials/issues/new -->

```nn.init._calculate_fan_in_and_fan_out()``` is missing from the documentation in torch.nn.init

cc @brianjo @mruberry