sharjeelyunus/github-issues-dataset huggingface dataset:
Repository: react
Issue: Bug:  Component with a Symbol as key, causes Crash
Labels: Type: Discussion

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  screenshots if needed. Please test using the latest version of the relevant
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React version:
16.13.1
# Steps To Reproduce

1. Go To the link https://codesandbox.io/s/happy-ramanujan-xlegp?file=/src/App.js
2. We can see errors caused by this part of code: https://github.com/facebook/react/blob/6fddca27e75950adda92ab4f4946442907dc3bb7/packages/react/src/ReactElement.js#L228

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Link to code example:
https://codesandbox.io/s/happy-ramanujan-xlegp?file=/src/App.js
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  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
Crash
## The expected behavior
No crash
Repository: ant-design
Issue: timepicker can't be selected on mobile
Labels: Inactive,📱Mobile Device

- [ ] I have searched the [issues](https://github.com/ant-design/ant-design/issues) of this repository and believe that this is not a duplicate.

### Reproduction link
[https://drive.google.com/file/d/1ud8pSWJklzCf4rhOAXp5P0aqdVuocR5i/view?usp=sharing ](https://drive.google.com/file/d/1ud8pSWJklzCf4rhOAXp5P0aqdVuocR5i/view?usp=sharing )

### Steps to reproduce
On mobile (iphone), a user can select a time with the controls or enter using the keyboard, however, you must select "done" on the keyboard to see the "ok button" When you click "done" it closes the whole picker and you are unable to click "ok" so the time you selected disappears. 

### What is expected?
able to select time 

### What is actually happening?
not able to use timepicker on mobile

| Environment | Info |
|---|---|
| antd | 4.6.4 |
| React | "react": "^16.13.1", |
| System | Apple iOS |
| Browser | Safari |


<!-- generated by ant-design-issue-helper. DO NOT REMOVE -->
Repository: flutter
Issue: [Proposal] : Color for unselected Button in ToggleButtons 
Labels: framework,f: material design,c: proposal,team-design,triaged-design

It is possible to define the selected color using ToggleButtons (fillColor) but it needs workarounds to define the color for unselected buttons which are transparent.

Workarounds see https://stackoverflow.com/questions/60434927/background-color-of-toggle-buttons/63943884#63943884

It would be great to have an option to just define a **"fillColor" for unselected ToggleButtons**.
Repository: flutter
Issue: Constrained TextFields compensate for prefix/suffix when none exist
Labels: a: text input,framework,f: material design,a: fidelity,a: quality,has reproducible steps,found in release: 3.3,found in release: 3.5,team-design,triaged-design

`fixBelowInput` is used in the layout of InputDecorator to compensate for a prefix/suffix that is so tall that it extends beyond the bottom of the input.  However, it is sometimes being applied even when there is no prefix/suffix at all.



## Steps to Reproduce

1. Run the app whose code is given below, or any TextField whose height is constrained smaller than it would otherwise be.
1. The TextField's baseline will be moved by `fixBelowInput`.

<details>

<summary>Code</summary>

```dart
import 'package:flutter/material.dart';

void main() => runApp(MyApp());

class MyApp extends StatelessWidget {
  @override
  Widget build(BuildContext context) {
    return MaterialApp(
      title: 'Material App',
      home: Home(),
    );
  }
}

class Home extends StatefulWidget {
  @override
  _HomeState createState() => _HomeState();
}

class _HomeState extends State<Home> {
  final TextEditingController controller = TextEditingController();

  @override
  Widget build(BuildContext context) {
    return Scaffold(
      appBar: AppBar(
        title: Text('Material'),
      ),
      body: Center(
        child: Container(
          width: 200,
          height: 28,
          color: Colors.cyanAccent.withOpacity(0.6),
          child: TextField(
            controller: TextEditingController(text: 'A'),
          ),
        ),
      ),
    );
  }
}
```

</details>

## Solution

The effect of fixBelowInput could be removed from cases where it is irrelevant with this change:

https://github.com/flutter/flutter/blob/48ba488d33a457a1faab84f7cef55d7fbecb8771/packages/flutter/lib/src/material/input_decorator.dart#L1068

```dart
final double fixBelowBaseline <= 0.0 ? 0.0 : math.max(
```

The problem is that this bug ends up making the baseline appear more correct than it would be without the bug!  At least one app has come to rely on the bug for that reason(see <PR> for more details).

So, in addition to the change given above, I think a full solution needs to properly place the baseline in cases like the app above.  Even when the field is being constrained too much, we probably want to attempt to place the baseline in the right place.
Repository: pytorch
Issue: for loop can't be symbolically traced
Labels: triaged,module: fx

```python
    def get_additional_output_info(
        self, encoded_feature: Dict[str, torch.Tensor]
    ) -> Dict[str, torch.Tensor]:
        additional_info: Dict[str, torch.Tensor] = {}
        for key in encoded_feature.keys():
            if key not in self.encoded_feature_key:
                additional_info[key] = encoded_feature[key]
        return additional_info
```

```
...
    for key in encoded_feature.keys():
    self._no_control_flow()
...
line 67, in _no_control_flow
    raise TraceError('symbolically traced variables cannot be used as inputs to control flow')
torch.fx.proxy.TraceError: symbolically traced variables cannot be used as inputs to control flow
```

what is the recommendation?

cc @ezyang @SherlockNoMad
Repository: flutter
Issue: All of ThemeData's factory constructor parameters should be required to be non-null
Labels: framework,f: material design,team-design,triaged-design

Because having a few needless exceptions is confusing and likely due to historical accident not design.

Of the 73 ThemeData.raw() parameters, buttonColor, applyElevationOverlayColor, and cupertinoOverrideTheme are _not_ required to be non-null.
Repository: node
Issue: Invalid ES module, internal SyntaxError, error text could use more context
Labels: esm

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* **Version**: v14.11.0
* **Platform**: Win10 64bit
* **Subsystem**: internal/modules/esm/translators.js:117:18

### What steps will reproduce the bug?

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run using `node` directly without installing third-party dependencies.
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While other async operations are happening, load a malformed ES module

### How often does it reproduce? Is there a required condition?

Consistently, in an ES module project, it seems to appear with lots of async operations including some that are using sockets.

### What is the expected behavior?

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`Error: unexpected character at ...` 

### What do you see instead?

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```txt
(node:26584) UnhandledPromiseRejectionWarning: SyntaxError: Missing initializer in destructuring declaration
    at Loader.moduleStrategy (internal/modules/esm/translators.js:117:18)
    at Loader.moduleStrategy (internal/modules/esm/translators.js:117:18)
    at emitUnhandledRejectionWarning (internal/process/promises.js:168:15)
    at processPromiseRejections (internal/process/promises.js:247:11)
    at processTicksAndRejections (internal/process/task_queues.js:94:32)
```

### Additional information

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Tell us anything else you think we should know.
-->
Easy recreation:
```js
// Malformed Module testImport.js
const {
	general: { getLocal },
} from '#utils');

// imported asynchronously
import('./testImport.js').catch(err => console.log(err))
```
Results in
```txt
SyntaxError: Missing initializer in destructuring declaration
    at Loader.moduleStrategy (internal/modules/esm/translators.js:117:18)
    at async link (internal/modules/esm/module_job.js:42:21)
```
In which there's no helpful information about the locations/modules involved
Repository: flutter
Issue: Update service worker to perform caching activities in install event
Labels: c: new feature,tool,platform-web,P3,team-web,triaged-web

The service worker event activate is not guaranteed to run to completion, for example if the browser closes. If it fails or ends early, then it will never be rerun.

The install event has stronger guarantees, and is a better solution for updating the caches.
Repository: flutter
Issue: Consider simplifying ChannelBuffers to only ever store one message per channel
Labels: c: new feature,team,engine,c: API break,c: performance,perf: speed,perf: app size,P3,a: plugins,team-engine,triaged-engine

There's a lot of complexity with having ring buffers and so forth, and they are a source of some confusion and bugs. We would benefit greatly from this being significantly simpler.

For use cases where a small ring buffer greater than 1 is appropriate, it seems like a sufficient solution is just to store all the relevant information in every message and send that.

For use cases where large amounts of information should be cached, it seems like a solution is to have the plugin do the caching and await a request.

We should see whether any plugins are making use of the ChannelBuffers control channel. If none are, that would be a good signal that we can just remove this. If some are, we should investigate what the use cases are.
Repository: pytorch
Issue: Incorrect documentation of SGD momentum
Labels: module: docs,module: optimizer,triaged

## 🐛 Bug

Pytorch documentation: https://pytorch.org/docs/stable/optim.html#torch.optim.SGD
"This is in contrast to Sutskever et. al. and other frameworks which employ an update of the form"
![image](https://user-images.githubusercontent.com/4337024/93537302-022c5f00-f900-11ea-9a98-fa83a7b90654.png)

SGD: http://proceedings.mlr.press/v28/sutskever13.pdf
![image](https://user-images.githubusercontent.com/4337024/93537287-f9d42400-f8ff-11ea-9535-42d1eafb92f1.png)

As an implication both the adapted and the interpreted version of SGD have negative momentum



cc @jlin27 @vincentqb
Repository: terminal
Issue: [Regressed in 19H1] When you copy text out of FAR manager, it gets line wrapped
Labels: Product-Conhost,Area-Output,Issue-Bug,Priority-3,Impact-Compatibility,Impact-Correctness

It appears that some time between RS5 and 19H1 we changed how line wrapping/unwrapping works and now FAR manager gets wrapped on copy.

_Notes from internal filer_

> I'm on 3.0.0.5656 x64. I had repro with some older version as well, I installed the latest to check if it was fixed. Copy like you do in any other cmd window. For example, select any text file and press F3 to open the text viewer, or press CTRL+O to hide panels and view console / Far version. Now click on icon in left top corner of the window, then in menu select Edit -> Mark and select any text. Then paste the text in any other application like Notepad.

MSFT:28821591
Repository: godot
Issue: Scripts loaded from outside of res are suggested to save in res instead of just saving
Labels: topic:editor

<!-- Please search existing issues for potential duplicates before filing yours:
https://github.com/godotengine/godot/issues?q=is%3Aissue
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**Godot version:**
<!-- Specify commit hash if using non-official build. -->
v3.2.3.stable

**OS/device including version:**
<!-- Specify GPU model, drivers, and the backend (GLES2, GLES3, Vulkan) if graphics-related. -->
Windows

**Issue description:**
<!-- What happened, and what was expected. -->
A script that is loaded from a folder other than `res://` is suggested to be saved in `res://` instead of just saving to loaded path

**Steps to reproduce:**
1) Open a new Godot project
2) Open Script Editor (F3)
3) Open a script that is not in `res://` (with File-Open)
4) Change the script code in the editor [not necessary] and try to close (ctrl+w) or save (ctrl+alt+s) the script
5) As you can see, `Save as` popup appears instead of just saving the script source to path where it is loaded from

The same is for loading a script using `load()` or `Gdscript.new()`.

**Minimal reproduction project:**
<!-- A small Godot project which reproduces the issue. Drag and drop a zip archive to upload it. -->
Repository: pytorch
Issue: Issue while writing scalars o tensorboard using writer.add_scalars(....)
Labels: triaged,module: tensorboard

## Problem using add_scalars in torch.utils.tensorboard
    line 387, in add_scalars
    scalar_value = workspace.FetchBlob(scalar_value)
    NameError: name 'workspace' is not defined
Repository: flutter
Issue: RenderFollowerLayer needs a proper showOnScreen implementation
Labels: framework,P2,team-framework,triaged-framework

Want to check if this is worth doing, before relanding https://github.com/flutter/flutter/pull/65884. `RenderFollowerLayer.showOnScreen` needs to call `RenderLeaderLayer.showOnScreen` when it's linked to the leader. But if a `RenderFollowerLayer` knows who its leader is then we won't need the `leaderSize` field. 

Currently the following test fails:

```dart
  testWidgets('Composited transforms - showOnScreen', (WidgetTester tester) async {
    final LayerLink link = LayerLink();
    final GlobalKey key = GlobalKey();
    final ScrollController controller = ScrollController(initialScrollOffset: 10);
    await tester.pumpWidget(
      Directionality(
        textDirection: TextDirection.ltr,
        child: ListView(
          controller: controller,
          children: <Widget>[
            SizedBox(
              height: 600,
              child: Stack(
                children: <Widget>[
                  Positioned(
                    left: 123.0,
                    top: 456.0,
                    child: CompositedTransformTarget(
                      link: link,
                      child: const SizedBox(width: 20.0, height: 20.0),
                    ),
                  ),
                  Positioned(
                    left: 787.0,
                    top: 343.0,
                    child: CompositedTransformFollower(
                      link: link,
                      child: Container(key: key, width: 30.0, height: 30.0),
                    ),
                  ),
                ],
              ),
            ),
            const SizedBox(height: 1000),
          ],
        ),
      ),
    );

    // With an initial offset of 10, both the CompositedTransformTarget and the
    // follower are partially visible.
    expect(controller.offset, 10);
    final RenderBox box = key.currentContext.findRenderObject() as RenderBox;
    expect(box.localToGlobal(Offset.zero), const Offset(123.0, 456.0 - 10.0));

    // Calling showOnScreen on the follower's child render object.
    box.showOnScreen();
    await tester.pumpAndSettle();
    expect(controller.offset, 0);
    expect(box.localToGlobal(Offset.zero), const Offset(123.0, 456.0));
  });
```
Repository: node
Issue: document cross compile arm on linux
Labels: doc,arm

I didn't find it in `BUILDING.md`, but it looks like this in our Jenkins CI.

cc @bnoordhuis @targos @nodejs/platform-arm
Repository: pytorch
Issue: DataParallel on CPU
Labels: triaged,enhancement,module: data parallel

## 🚀 Feature
<!-- A clear and concise description of the feature proposal -->
Adding DataParallel method for CPU

## Motivation

<!-- Please outline the motivation for the proposal. Is your feature request related to a problem? e.g., I'm always frustrated when [...]. If this is related to another GitHub issue, please link here too -->
Recently, I have been working on few-shot learning and meta-learning models which in particular need small datasets. Let's take MAML for example. We have scope for parallelizing the inner loop and data parallelism seemed to be the answer for that. While, using GPUs does the work, we can also make use of CPUs for the same, as the data is sufficiently small.

## Pitch

<!-- A clear and concise description of what you want to happen. -->
My question is, is it worth looking into adding an option for CPUs in DataParallel module along with GPUs?
Repository: animate.css
Issue: Add a troubleshoot/FAQ section in the docs
Labels: documentation,todo

It would make life easier if we had a docs section with some guidelines on common issues related to animate. On the top of my head, I can think of:
- CSS properties being overwritten #1117 
- Overflow "issues" #970 
- Performance problems (although we have a few words in the Best practices section)
Repository: pytorch
Issue: In pytorch 1.6。Run model with input no contiguous tensor will become very slow.
Labels: module: performance,module: cuda,triaged

## 🐛 Bug

In pytorch 1.6. Run model with no contiguous tensor will become very slow.
Pytorch 1.5.1 also has this problem, but the problem is not very obvious.

## To Reproduce

Steps to reproduce the behavior:

This is a simplified code, and the speed difference may not be obvious.  
In my training code and model, the speed difference between using contiguous and not using contiguous is very big (over 10x), I don't know why.

```
import torch
import torch.nn as nn
import torch.nn.functional as F
import numpy as np
import time

device = 'cuda:0'

torch.set_grad_enabled(False)

class Net2(nn.Module):
    def __init__(self, *args, **kwargs):
        super().__init__()
        self.layer1 = nn.Conv2d(3, 128, 3, 1, 1)
        self.layer2 = nn.Sequential(*([nn.Conv2d(128, 128, 3, 1, 1)]*20))

    def forward(self, x):
        x = self.layer1(x)
        x = self.layer2(x)
        return x

net = Net2().to(device)

def calc_time(use_contiguous=True, ep=10):
    t1 = time.time()

    batch_im = np.random.uniform(size=[10, 256, 256, 3]).astype(np.float32)

    for i in range(ep):
        batch_tensors = torch.tensor(batch_im, dtype=torch.float32, device=device).permute(0, 3, 1, 2)
        if use_contiguous:
            batch_tensors = batch_tensors.contiguous()
        out = net(batch_tensors)
        out = out.softmax(dim=1)
        out = F.interpolate(out, size=[512, 512], mode='area')
        out.cpu().numpy()

    t2 = time.time()
    print(t2-t1)

# warm start
calc_time(use_contiguous=False, ep=1)
# calc time
print('calc time')
calc_time(use_contiguous=True)
calc_time(use_contiguous=False)
calc_time(use_contiguous=True)
calc_time(use_contiguous=False)


```

<!-- If you have a code sample, error messages, stack traces, please provide it here as well -->

## Expected behavior

<!-- A clear and concise description of what you expected to happen. -->

## Environment

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): 1.6
 - OS (e.g., Linux): win10 and ubuntu18
 - How you installed PyTorch (`conda`, `pip`, source): pip
 - Build command you used (if compiling from source):
 - Python version: 3.8
 - CUDA/cuDNN version: 10.2 and 10.1
 - GPU models and configuration: gtx1070 and gtx 1080
 - Any other relevant information:

## Additional context

<!-- Add any other context about the problem here. -->


cc @ngimel @VitalyFedyunin
Repository: godot
Issue: "Signal already connected" error for inherited scenes Godot3.2 
Labels: bug,topic:editor,confirmed

___

***Note:** This issue has been confirmed several times already. No need to confirm it further.*

___

(Although there are some similarities with https://github.com/godotengine/godot/issues/6106 ; there are also differences, so Akien asked to make a new bug report; nevertheless, possible regression? in the other thread issues starting popping up again since May 2020)

Using Godot 3.2 stable (longer term project so haven't switched yet, was waiting for 3.2.3 stable to fix the polygon2D clipping problem); on Windows 10

I am getting a "Signal already connected" for each signal that I connect for a scene with inheritance.

The error pops up right after I change scenes, going from one level to the next via get_tree().change_scene(). These levels all extend my Level class, where I connect the signals. Maybe there's a desynch between disconnecting the signals of the old scene and connecting the new ones?

My scenes had editable children, but I made them uneditable again. The problem persists. (Here we seem to deviate from the earlier issue)

The error I get is:

```
E 0:01:08.592 connect: Signal 'freeze_player' is already connected to given method 'on_freeze_player' in that object.
<C++ Error> Method failed. Returning: ERR_INVALID_PARAMETER
<C++ Source> core/object.cpp:1464 @ connect()
LowerGuallidurth.gd:27 @ make_connections()
Level.gd:20 @ _ready()
LowerGuallidurth.gd:14 @ _ready()
```

Looking up that line in the source (not versed in C++) it looks to have something to do with it?

```cpp
void Object::_clear_internal_resource_paths(const Variant &p_var) {
switch (p_var.get_type()) {
```
Repository: pytorch
Issue: Fuse softmax and masking in MultiheadAttention
Labels: feature,module: nn,triaged,needs research

## 🚀 Feature
<!-- A clear and concise description of the feature proposal -->
Fuse `softmax` and mask calculation in `multi_head_attention_forward`.

## Motivation

<!-- Please outline the motivation for the proposal. Is your feature request related to a problem? e.g., I'm always frustrated when [...]. If this is related to another GitHub issue, please link here too -->
Currently `torch.nn.functional.multi_head_attention_forward` masks attention and then calls `softmax` as follows:

https://github.com/pytorch/pytorch/blob/caea1adc35404b39fe4f2e3fa75f9a0b9e554bbc/torch/nn/functional.py#L4265-L4281

(the code in C++ frontend is similar). In our own C++ implementation (not currently publicly available), we found that fusing these operations led to ~5% perfomance improvement in attention. Of course the number can't be expected to be the same in Pytorch, but it is probably a reasonable estimate.

## Pitch

<!-- A clear and concise description of what you want to happen. -->
Add a `masked_softmax` operation which effectively only calls `softmax` on un-masked values and fills the masked values with 0 without doing extra calculation. Include a fallback implementation for the cases we can't optimize (e.g. because an external library `softmax` is used, CUDA, etc.).

If accepted, we'll be happy to work on this.

The operation probably shouldn't be part of the public API, unless there are other significant uses for it.


cc @albanD @mruberry @jbschlosser @walterddr @mikaylagawarecki @zhangguanheng66