sharjeelyunus/github-issues-dataset huggingface dataset:
Repository: flutter
Issue: [google_sign_in_web] googleSignIn.signIn() hangs forever if can't connect to apis.google.com
Labels: platform-web,p: google_sign_in,package,has reproducible steps,P2,found in release: 3.3,found in release: 3.7,team-web,triaged-web

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## Steps to Reproduce

1. In Chrome dev tools, add `apis.google.com` in "Network request blocking" tab
1. call: `var user = await googleSignIn.signIn()`

Nothing will happen and it will never return. 

**Expected results:** <!-- what did you want to see? -->

Expect an error. 

**Actual results:** <!-- what did you see? -->

Nothing, it never returns. eg:

```
print("before signIn");
user = await _googleSignIn.signIn();
print("after signIn");
```

"after signIn" never prints and no error is thrown.
Repository: node
Issue: Source Maps with Function.prototype.toString()
Labels: source maps

**Is your feature request related to a problem? Please describe.**

The output of `Function.prototype.toString()` can be useful for showing the source code for a function, such as in output for a test framework, to show the test code for a test.

If the original code was transformed/transpiled/etc, the output will be the post-processed source code, which is less useful.

**Describe the solution you'd like**

When using `--enable-source-maps`, show the original source code for the function, rather than the post-processed source code.

This is non-trivial from user-land since `Function.prototype.toString()` has no metadata about the source file or source lines. Maybe Node can get access to that information through V8? If source file and line numbers were available then it should be a fairly straight forward look up in the source map to get back to the original code.

**Describe alternatives you've considered**

None.
Repository: pytorch
Issue: Get forward output, grad, hessian all at once
Labels: module: autograd,triaged,enhancement

## 🚀 Feature

Currently the functional API `torch.autograd.functional.hessian` takes a function and input, and returns hessian. However, when hessian is required, the forward result and first-order derivative are often also required.

While it is possible that users can separately call other autograd APIs to obtain forward output and first-order derivative, this is not efficient because we are running the forward and backward multiple times. I wish there is a way to make `hessian` returns the forward, backward, and hessian all at once


cc @ezyang @albanD @zou3519 @gqchen @pearu @nikitaved
Repository: pytorch
Issue: Memory leak in nn.MaxPool2d layer when run on iOS
Labels: module: memory usage,triaged,module: ios

## 🐛 Bug
I create a simple network with two conv+relu layers followed by a max-pooling layer and test the model on the `HelloWorld` project from [official iOS demo of pytorch](https://github.com/pytorch/ios-demo-app). And found that `nn.MaxPool2d` layer will cause a memory leak.

## To Reproduce

Code for network structure
```python
class Network(torch.nn.Module):
    def __init__(self):
        super(Network, self).__init__()
        import torch.nn as nn
        self.relu = nn.ReLU(inplace=True)
        self.pool = nn.MaxPool2d(kernel_size=2, stride=2)
        self.conv1 = nn.Conv2d(3, 64, kernel_size=3, stride=1, padding=1)
        self.conv2 = nn.Conv2d(64, 64, kernel_size=3, stride=1, padding=1)

    def forward(self, input):
        x = self.relu(self.conv1(input))
        x = self.relu(self.conv2(x))
        x = self.pool(x)
        return x
```

Code for tracing the model
```python
    network = Network()
    network.eval()
    network_trace = torch.jit.script(network)
    network_trace.save("./model_test.pt")
```

Code for testing on iOS comes directly from the `HelloWorld` project from the official demo of pytorch + iOS: https://github.com/pytorch/ios-demo-app/tree/master/HelloWorld 

My modification on the code:
1. I modify the input image size to 480x640
2. I add an additional for loop before the exact [prediction](https://github.com/pytorch/ios-demo-app/blob/master/HelloWorld/HelloWorld/HelloWorld/ViewController.swift#L28) to make the memory leak more obvious
```swift
        for i in 0...19
        {
            autoreleasepool{
                print("running \(i)")
                guard let outputs = module.predict(image: UnsafeMutableRawPointer(&pixelBuffer)) else {
                    return
                }
            }
        }
```

I build the app, install it on iOS device (iPad mini 5th generation), run it, and observe the change of memory usage on XCode

## Expected behavior
1. When input image size is set to 640x480, there is a memory leak of about 2MB for each prediction, i.e. the memory usage is increased by 2MB after each execution.
2. When not using the max-pooling layer (by simply commenting on the line `x = self.pool(x)` in the `forward` of network code provided above), the memory leak does not happen, i.e. the memory does not change since the first time of running network prediction (which is as a result of `lazy` initialization of swift).

## Environment
 - PyTorch Version (e.g., 1.0): 1.5.1 for PC, 1.6 for iOS 
 - OS (e.g., Linux): Mac OS, iOS 13
 - How you installed PyTorch (`conda`, `pip`, source): conda on PC, Cocoapods for iOS
 - Build command you used (if compiling from source): already described in the project of official iOS demo
 - Python version: 3.6.12 
 - CUDA/cuDNN version: No
 - GPU models and configuration: No
 - Any other relevant information: No
Repository: pytorch
Issue: amp for custom op
Labels: triaged,module: custom-operators,module: amp (automated mixed precision)

I want use amp in `https://github.com/open-mmlab/mmcv/blob/master/mmcv/ops/roi_align.py`.

I refer to `https://pytorch.org/docs/stable/notes/amp_examples.html#functions-with-multiple-inputs-or-autocastable-ops`, and Apply custom_fwd and custom_bwd (with no arguments) to forward and backward respectively. I modify code :
```
class RoIAlignFunction(Function):
    ... ...
    @staticmethod
    @custom_fwd
    def forward(ctx,
                input,
                rois,
                output_size,
                spatial_scale=1.0,
                sampling_ratio=0,
                pool_mode='avg',
                aligned=True):
        ctx.output_size = _pair(output_size)
        ctx.spatial_scale = spatial_scale
        ... ...
 
    @staticmethod
    @once_differentiable
    @custom_bwd
    def backward(ctx, grad_output):
        rois, argmax_y, argmax_x = ctx.saved_tensors
        ... ...
```
The code still report error: 
```
  File "/usr/local/python16/lib/python3.7/site-packages/mmcv/ops/roi_align.py", line 71, in forward
    aligned=ctx.aligned)
RuntimeError: expected scalar type Half but found Float
```

what did `custom_fwd` and `custom_bwd ` do specifically? 


cc @mcarilli
Repository: opencv
Issue: findContours -The function cannot meet the performance requirements, it is too slow.Is there any plan to speed it up？
Labels: incomplete

findContours -The function cannot meet the performance requirements, it is too slow.Is there any plan to speed it up？
Repository: flutter
Issue: Flutter tool does not restore terminal single line mode when resumed with SIGCONT
Labels: tool,P2,team-tool,triaged-tool

let's say i ran flutter run, then I want to see `git status`
my usual workflow in this situation is to press C-z and then resume the job
when flutter resumes, it will log messages from the app, but if I press r R or whatever key, it won't reload/take effect
Repository: kubernetes
Issue: 🐘 Need a replacement for deprecated/unmaintained gogo-protobuf dependency
Labels: kind/cleanup,sig/api-machinery,priority/important-longterm,lifecycle/frozen,area/dependency,area/code-organization,triage/accepted

Is it officially marked as deprecated:

* https://twitter.com/awalterschulze/status/1584553056100057088
* https://github.com/gogo/protobuf
* https://github.com/gogo/protobuf/issues/691#issuecomment-1289137315
* discussion in sig-apimachinery : https://groups.google.com/g/kubernetes-sig-api-machinery/c/tcwFubV9Boo/m/MAdQfLY_AgAJ

There is a [document](https://docs.google.com/document/d/18YCIU8MSv2HzO9IEUiz1hgCtWCRzabUcpeKHOUiOlHs/edit?resourcekey=0-KhINfpm6jDUA7wAmzy1sYA#) gathering requirements/desirements for a replacement, possible solutions and considerations. Contributions welcome!

/area code-organization
/sig api-machinery
Repository: opencv
Issue: Simple opencv issue
Labels: question (invalid tracker),incomplete

System information (version)
->OpenCV => 4.3.0
->Operating System / Platform => Windows 10 18363.1139
->Compiler => vs 2017 professional
Detailed description
Building errors:
E:/Archive/Project/Kotlin/android-camera-master/camera-samples-master/Camera2Basic/app/src/main/jniLibs/include\opencv2/core/mat.inl.hpp:699
error: undefined reference to 'cv::Mat::copyTo(cv::_OutputArray const&) const'
Repository: pytorch
Issue: sparse filter layers (more specifically convolutions)
Labels: module: sparse,triaged,needs research,function request

## 🚀 Feature
The ability to force layer's weights to be sparse with some input mask so that for example a 1d convolution that has a weight matrix with mXn weights would have a sparse matrix of size mXn with some portion of that matrix being null.   
This should be accompanied by efficient implementations.  

## Motivation

there's a ton of works that promise reduced model weights and speed-ups without much sacrifice to model performance through pruning and sparsity. In practice, there is little benefit because there is no simple way in pytorch to implement this beyond zeroing out a non-sparse weight tensor. 

## Pitch

the future is sparse networks. In the community's effort to move research into production there is a mass of effort to create more efficient networks that rival performance. At the end of the day what people have come up with is a million ways to create effective sparse networks - whether it's depthwise separable convolutions or lottery ticket theory. Groups in pytorch are a reduced functionality whose more generalized form is fully controlled sparsity.  

## Alternatives
Numenta did something in this direction. I don't think it's efficiently implemented.
https://github.com/numenta/nupic.torch/



cc @aocsa @nikitaved @pearu @mruberry
Repository: vscode
Issue: [rename on type] stops when composing characters
Labels: bug,editor-synced-region

* start on-type rename
* compose a characters, e.g the mac type ¨ (<kbd>alt+u</kbd>) and then <kbd>u</kbd> for ü
* 🐛 on type rename stops

fyi - there is an event that the editor raises when composing starts/ends
Repository: pytorch
Issue: Hash mismatch for METADATA file
Labels: module: binaries,triaged

## 🐛 Bug

The METADATA file distributed in the wheel seems to not match the one listed in RECORD.

## To Reproduce

Steps to reproduce the behavior:

1. Download wheel (confirmed that hash matches the ones listed on pypi)
    ```
    $ wget https://files.pythonhosted.org/packages/05/2d/bb4611cf053eaa679f6086b78cff2776ff1d51a15fe5e063cdcbfc6b5577/torch-1.7.0-cp38-cp38-manylinux1_x86_64.whl
    ```
2. Confirm that sha256sum matches
    ```
    $ sha256sum torch-1.7.0-cp38-cp38-manylinux1_x86_64.whl
    11054f26eee5c3114d217201dba5b3a35f1745d11133c123c077c5981bc95997  torch-1.7.0-cp38-cp38-manylinux1_x86_64.whl
    ````
3. Try to unpack wheel
    ```
    $ wheel unpack torch-1.7.0-cp38-cp38-manylinux1_x86_64.whl
    Unpacking to: ./torch-1.7.0...Hash mismatch for file 'torch-1.7.0.dist-info/METADATA'
    ```

## Expected behavior

No error

## Environment

 - PyTorch Version: 1.7.0 (possibly previous versions too, but did not test)
 - OS: Linux
 - Python version: All? (confirmed for both 3.7 and 3.8)
 - Any other relevant information:
    ```
    $ wheel version
    wheel 0.35.1
    ```

cc @ezyang @seemethere @malfet @walterddr
Repository: pytorch
Issue: Function request: Sparse matrix inverse
Labels: module: sparse,triaged,module: linear algebra,function request

I want to calculate the inverse of a sparse matrix, how can I do this ?

for example
```py
vers_n=200000
ind_i = torch.Tensor(list(range(vers_n))).long().view(1,-1)
ind_j = torch.Tensor(list(range(vers_n))).long().view(1,-1)
indices = torch.cat((ind_i, ind_j), dim=0)
values = torch.ones(vers_n)
I = torch.sparse.FloatTensor(indices, values, (vers_n, vers_n))
print(I.inverse())
``` 

then will get the error:
```
RuntimeError: Could not run 'aten::_inverse_helper' with arguments from the 'SparseCPUTensorId' backend. 'aten::_inverse_helper' is only availabl
```
Maybe a possible solution is turn to dense and calculate the inverse, but if I turn to dense, it will be out of memory and exit 137.

cc @jianyuh @nikitaved @pearu @mruberry @heitorschueroff @walterddr @IvanYashchuk @xwang233 @Lezcano @cpuhrsch @aocsa
Repository: terminal
Issue: Doesn't detect pwsh installed in custom directory from Scoop
Labels: Help Wanted,Area-Settings,Product-Terminal,Issue-Task,good first issue

# Environment
Windows build number: 10.0.19042.0
Windows Terminal version (if applicable): 1.4.3141.0

PowerShell Core: 7.1.0
Scoop

# Steps to reproduce
1. [Installing Scoop to Custom Directory](https://github.com/lukesampson/scoop/wiki/Quick-Start#installing-scoop-to-custom-directory)
2. Install PowerShell Core via Scoop
3. Open Windows Terminal

# Expected behavior
When environment variable `SCOOP` or `SCOOP_GLOBAL` is defined, Terminal should search pwsh.exe in `%SCOOP%` and `%SCOOP_GLOBAL%` in addition to `%USERPROFILE%\scoop`.

# Actual behavior
Error dialog is opened.
The content of error message is "An error occurred while loading the settings."
(Sorry, I don't know the message of English version because I use Japanese version).

And, PowerShell is used instead, and PowerShell Core doesn't appear in the shell list.

Searching place is only `%USERPROFILE%scoop` for Scoop.
(ref: [PowershellCoreProfileGenerator.cpp](https://github.com/microsoft/terminal/blob/v1.4.3141.0/src/cascadia/TerminalApp/PowershellCoreProfileGenerator.cpp) Line 281, Tag 1.4.3141.0)

# Related issue
#1415
Repository: create-react-app
Issue: Should react-scripts be in dependencies or devDependencies?
Labels: needs triage

When bootstraping a new project, the `react-scripts` is listed in `dependencies`, but the docs suggests that should be in `devDependencies`. See [updating-to-new-releases.md](https://github.com/facebook/create-react-app/blob/ed5fb1066bd9d08b6aa0a74ccb2ab8304aec7490/docusaurus/docs/updating-to-new-releases.md#L9):

> react-scripts is a development dependency in the generated projects (including this one).

And [this image](https://github.com/facebook/create-react-app/blob/ed5fb1066bd9d08b6aa0a74ccb2ab8304aec7490/docusaurus/website/static/img/update.png) in the landing page:

![image](https://user-images.githubusercontent.com/6919329/99097044-cf2be200-25b5-11eb-898c-1a3df8a0088d.png)

I'm guessing that the previous versions worked fine in `devDependencies`, but something changed and the docs wasn't updated.
Repository: react
Issue: Bug: [eslint-plugin-react-hooks] Constructions should be caught in default props/args
Labels: Type: Enhancement,Component: ESLint Rules

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  Please provide a clear and concise description of what the bug is. Include
  screenshots if needed. Please test using the latest version of the relevant
  React packages to make sure your issue has not already been fixed.
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React version: 17.0.1

## Steps To Reproduce

1. ```js
   function useMyHook1(arr = []) {
     useEffect(() => {
       console.log(arr);
     }, [arr]);
   }

    function useMyHook2({ arr = [] }) {
     useEffect(() => {
       console.log(arr);
     }, [arr]);
   }

   function MyComponent({ arr = [] }) {
     useEffect(() => {
       console.log(arr);
     }, [arr]);

     return null;
   }
   ```

<!--
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  have dependencies other than React. Issues without reproduction steps or
  code examples may be immediately closed as not actionable.
-->

Link to code example: --

<!--
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  repository on GitHub, or provide a minimal code example that reproduces the
  problem. You may provide a screenshot of the application if you think it is
  relevant to your bug report. Here are some tips for providing a minimal
  example: https://stackoverflow.com/help/mcve.
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## The current behavior
No warning appears for `arr` being potentially constructed on every render.

## The expected behavior
Should warn that `arr` can be constructed on each render.
The lint rules already warn for the following, so this is just an extension of the existing behavior:
```js
const arr = props.arr ?? []; // The 'arr' logical expression could make the dependencies of useEffect Hook (at line 54) change on every render. Move it inside the useEffect callback. Alternatively, wrap the initialization of 'arr' in its own useMemo() Hook.
```
Reference: https://github.com/facebook/react/pull/19590
Repository: bitcoin
Issue: Avoid pruning blocks with transactions in wallets (even after wallets sync)
Labels: Feature

Good idea from @Bosch-0: https://github.com/bitcoin-core/gui/pull/125#issuecomment-723806881

By not pruning blocks that contain wallet transactions, old backups can be restored despite pruning.

Logical dependencies:
* My current prune-locks PR only works with heights, whereas this should probably be based on block hash.
* Some way to sort out if this was done, when restoring a backup, so we know it's safe to assume missing blocks are ignorable.
Repository: flutter
Issue: Provide interface for setting thread priorities in the embedder API
Labels: c: new feature,engine,e: embedder,P3,team-engine,triaged-engine

Today, it's possible to pass the `worker-thread-priority` to the Dart VM via the embedder. It's also possible to use FlutterEnginePostCallbackOnAllNativeThreads to set the priority for threads that have already been created.

It would be good if the embedder API just exposed an easier way to set thread priority for the various threads it will create, including passing that on through to the VM via the worker-thread-priority setting.
Repository: pytorch
Issue: Unknown DispatchKey when indexing tensor with named dimensions
Labels: triaged,module: dispatch,module: named tensor

## 🐛 Bug


## To Reproduce

Steps to reproduce the behavior:

1. Create a tensor and rename it's dimensions.

2. Use indexing like I have in the test code (forget what it's called).

```
import torch

test_tensor = torch.randn(3,4,4).refine_names("C", "H", "W")
test_tensor = test_tensor[[2, 1, 0], ...]
```

Results in this error message:

```
RuntimeError: false INTERNAL ASSERT FAILED at "/pytorch/c10/core/TensorOptions.h":679, please report a bug to PyTorch. Unknown DispatchKey: Named
```

## Expected behavior

There should be no error just like when using a tensor without named dimensions.

## Environment

```
Collecting environment information...
PyTorch version: 1.7.0+cu101
Is debug build: True
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: 3.6 (64-bit runtime)
Is CUDA available: False
CUDA runtime version: 10.1.243
GPU models and configuration: Could not collect
Nvidia driver version: Could not collect
cuDNN version: /usr/lib/x86_64-linux-gnu/libcudnn.so.7.6.5
HIP runtime version: N/A
MIOpen runtime version: N/A

Versions of relevant libraries:
[pip3] numpy==1.18.5
[pip3] torch==1.7.0+cu101
[pip3] torchsummary==1.5.1
[pip3] torchtext==0.3.1
[pip3] torchvision==0.8.1+cu101
[conda] Could not collect
```

cc @zou3519
Repository: vscode
Issue: Mouse positions influences initial selection on menus
Labels: bug,menus

Issue Type: <b>Bug</b>

VS Code version: Code 1.51.1 (e5a624b788d92b8d34d1392e4c4d9789406efe8f, 2020-11-10T23:34:32.027Z)
OS version: Windows_NT x64 10.0.19042

When bringing up a menu, the initial selected item is influenced by the current mouse position, including if the menu is brought up with a keyboard command.

Put another way, if I hit Shift-F10 to bring up the context menu, then press Down to select the first item, the first item will be selected, but if the mouse happens to be within the bounds of the menu, the same actions will select the item below the current mouse position.

As the user, if I'm interacting with the UI with the keyboard, I don't expect the mouse position to influence events.  This happens on Windows, on MacOS, the mouse position does not appear to influence the initial selection.

Here's what I'd expect, hitting Shift-F10 followed by the down arrow, the first item in the context menu is selected:

![expected](https://user-images.githubusercontent.com/14128876/99115890-00051a80-25a8-11eb-86d5-7af52ded5429.gif)

And here's what happens going through the same keyboard sequence if the mouse happens to be where the context menu will appear:

![mouse](https://user-images.githubusercontent.com/14128876/99115972-25922400-25a8-11eb-94dc-e0a0e1c3d244.gif)
Repository: three.js
Issue: Docs: Korean version
Labels: Documentation

Hello I am a college student in South Korea.
I want to translate the documentation into korean.
https://threejs.org/docs/index.html#manual/en/introduction/*

I want to know how to contribute to document translation.
Repository: godot
Issue: Editor shortcuts unable to use alt+shift+any_key combination
Labels: bug,topic:editor,topic:input

<!-- 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

**OS/device including version:**
<!-- Specify GPU model, drivers, and the backend (GLES2, GLES3, Vulkan) if graphics-related. -->
Win 10 

**Issue description:**
<!-- What happened, and what was expected. -->
When editing Editor shortcuts it's impossible to create a combination of keys that has alt+shift+any_key you can create ctrl+shift+any_key or ctrl+alt+any_key on the other hand.  Therefore I suspect this is a bug. Editor will only accept alt+shift and won't let you add 3rd key to the mix

**Steps to reproduce:**
Go to editor, shortcuts and try adding as described above

**Minimal reproduction project:**
<!-- A small Godot project which reproduces the issue. Drag and drop a zip archive to upload it. -->
Any project will work including empty one.