sharjeelyunus/github-issues-dataset huggingface dataset:
Repository: godot
Issue: Instancing new CanvasItem-derived nodes on a thread will hang
Labels: bug,topic:core,confirmed,topic:2d

**Godot version:**
3.2.1 (w/ Mono)

**OS/device including version:**
Win 10

**Issue description:**
Making new instances of `CanvasItem` types (such as `Control` or `Node2D`) on a thread other than the main thread will cause the game to hang. Other types do not cause a hang (I tested `Spatial`, `Node`, and `Object` - all fine).

It is not clear to me if this is expected. The threading docs seem to suggest that generating scene data outside the main thread and then adding the assembled scene via the main thread is a valid workflow.

Hang happens in both GDScript (using Godot threading) and Mono (using .Net threading).

GDScript test:
```
func _ready():
	var thread = Thread.new()
	thread.start(self, "_thread_entry")
	thread.wait_to_finish();

# This will hang
func _thread_entry(_data):
	var _moo = Node2D.new()
```

C# test

```
Parallel.For(0, 10, (i) => { new Node2D(); });
```

**Steps to reproduce:**
1. Start a new thread
2. Instance a type deriving from `CanvasItem` on the new thread, e.g. `var _moo = Node2D.new()`. **The app will now hang.**

**Minimal reproduction project:**
[Testing-ParallelInstancing.zip](https://github.com/godotengine/godot/files/4746448/Testing-ParallelInstancing.zip)
Repository: flutter
Issue: Support `--route` on flutter drive for Web
Labels: c: new feature,tool,t: flutter driver,f: routes,platform-web,c: proposal,P3,team-web,triaged-web

## Use case

I want to run an integration test for flutter web where it opens a unknown route and checks for the 404 page.

`flutter drive --target=test_driver/app.dart --no-headless --release --route '/password' lib/routes.dart`

## Proposal

On the web it seems to ignore the route parameter. On Android it works fine. I think this scenario makes way more sense on the web than on mobile since the user can type any URL in the search bar.
Repository: flutter
Issue: Support profile engine builds for simulators
Labels: a: tests,c: new feature,team,platform-ios,engine,P3,team-ios,triaged-ios

Today it is reported that `--ios --runtime-mode profile --simulator` can't be built, but an engine configured like this is needed for users who would like to run tests on AOT builds.

@mehmetf @chinmaygarde 

Separately, exposing this testing configuration to the Flutter tool would require building and packaging such an engine in the usual way on our infrastructure and removing certain gates from the Flutter tool. That work is not part of this issue, and should go in a separate issue if it's needed.

@jonahwilliams
Repository: PowerToys
Issue: Window Snapping/Start Menu problem with 3rd party software macros
Labels: FancyZones-Dragging&UI,Product-FancyZones,Area-App Compat

Hey there, 

I use a 60% keyboard, specifically the Anne Pro 2 for my machine. In the software included (obinskit) with the keyboard it allows you to make macros in order to compensate for the missing keys. I previously had made macros for window management, but after I installed powertools my macros for snapping windows to the left and right ( "Windows+left arrow " and "Windows+ right arrow") does still snap my windows to the desired direction, **BUT** it also triggers the start menu to pop up after the window has snapped. I have to then alt+tab or mouse click to get back to the window I was using in order to make it the currently focused window.

I've tried pulling up Carnac to see what was happening, but the shown keys pressed are as should be, nothing out of the ordinary and no extra key presses. But still the start menu keeps showing up. To be more clear this only happens with snapping windows to the left and right, not up or down.

I also checked my macros to see if the timing of the different key presses are registering at different times, but they are set to go off and stop and that same exact times. 

The thing is whenever I manually push all the buttons to snap the windows left and right without using macros, the commands work then works as it should and the start menu does not pop up

Kinda out of ideas, does anyone else who uses macros to snap windows have a similar problem.

Thanks for the input


# Environment

```
Windows build number: Microsoft Windows [Version 10.0.18363.836]
PowerToys version: 0.18.2
:
```

# Steps to reproduce

Press macro key for Window snapping left or right via Obinkit.


# Actual behavior

Window does snap left or right, **BUT** also opens up the start menu as if the only key pressed was the Windows Key

Problem does not happen when snapping up or down.
Repository: TypeScript
Issue: "Infer parameter type from usage" produces oddly formatted output
Labels: Bug

<!-- 🚨 STOP 🚨 𝗦𝗧𝗢𝗣 🚨 𝑺𝑻𝑶𝑷 🚨

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When using the "Infer parameter types from usage" quick fix in VS Code, TypeScript sometimes injects the JSDoc type annotation right in the middle of the code. The resulting code looks odd and broken.

<!--
Please try to reproduce the issue with the latest published version. It may have already been fixed.
For npm: `typescript@next`
This is also the 'Nightly' version in the playground: http://www.typescriptlang.org/play/?ts=Nightly
-->
**TypeScript Version:** 4.0.0-dev.20200607

<!-- Search terms you tried before logging this (so others can find this issue more easily) -->
**Search Terms:**
infer all from usage

**Code**
Using "Infer parameter type from usage" on this code:

```ts
function doSomething(things) {
  const states = things.filter(thing => true);
}
```

produces this output:

```ts
function doSomething(things) {
  const /**
     * @param {any} thing
     */
 states = things.filter(thing => true);
}
```

**Expected behavior:**

TypeScript produces annotated code that is not weirdly broken into different lines

**Actual behavior:**

TypeScript produces annotated code that looks odd and has the JSDoc comment injected in the middle of code

**Playground Link:** Not sure if this functionality is available in the Playground

**Related Issues:** N/A
Repository: youtube-dl
Issue: MotorTrend On Demand
Labels: site-support-request

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## Checklist

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- Finally, put x into all relevant boxes (like this [x])
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- [x] I'm reporting a new site support request
- [x] I've verified that I'm running youtube-dl version **2020.06.06**
- [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

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- Single video: https://www.motortrendondemand.com/detail/the-650hp-clevo-commando-returns/153906/
- Site: https://www.motortrendondemand.com/


## Description

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Used to be able to download just fine from https://www.motortrendondemand.com/ - looks like they changed something to break it, or changed their backend hosting.\
Tried with login and cookies, which used to work, but now it doesn't.
Found a closed request from last year (https://github.com/ytdl-org/youtube-dl/issues/23317) but the solution doesn't seem to work anymore, and the video IDs from the URL changed format.
In addition, it looks like they're now requiring logins. I can provide to someone working on the issue, if they don't want to sign up for a free trial that requires a CC.
Repository: pytorch
Issue: Better err msg for tensor ctor from sequence
Labels: triaged,enhancement,better-engineering

The `not a sequence` error message is very unhelpful.

```py
In [18]: torch.as_tensor([(72.4000015258789, 72.1199951171875), 73.36000061035156])
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-18-c8fc179c7fac> in <module>
----> 1 torch.as_tensor([(72.4000015258789, 72.1199951171875), 73.36000061035156])

TypeError: not a sequence

In [19]: torch.tensor([(72.4000015258789, 72.1199951171875), 73.36000061035156])
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-19-9e7f1b333fd9> in <module>
----> 1 torch.tensor([(72.4000015258789, 72.1199951171875), 73.36000061035156])

TypeError: not a sequence
```
Repository: flutter
Issue: InteractiveViewer `constrained: false` custom default scale
Labels: c: new feature,framework,a: quality,c: proposal,P3,team-framework,triaged-framework

## Use case

When I use the InteractiveViewer with `constrained: false`, my Image gets zoomed in a lot. So I have to zoom out to see the full image. 
I need contrained to be false, as my image is higher than the viewport and I don't want to combine the InteractiveViewer with a SingleChildScrollView, because this causes many other problems in panning around while zoomed in etc.

As a picture is worth a thousand words:

![interactive](https://user-images.githubusercontent.com/10547444/84067774-3c649700-a9c8-11ea-8965-452b5ef7a311.png)


## Proposal

It would be good, if there were a way to configure the default scale in this situation.
There could be a property called `defaultScale` which has properties like `Cover` which would make the image to be fully visible on the shortest axis. So if my image is very high, then I would see it with full with by default and would have to scroll down if I want to see the rest of the image, but I would not have to scroll left or right.
Repository: pytorch
Issue: Force JIT to do type inference even when mypy annotated
Labels: oncall: jit,module: typing,triaged

In #38211 I discovered a very interesting aspect of TorchScript's type system, which is that it is staged. Suppose you have a constructor like this:

```
        if self.affine:
            self.weight = Parameter(torch.Tensor(num_features))
            self.bias = Parameter(torch.Tensor(num_features))
        else:
            self.register_parameter('weight', None)
            self.register_parameter('bias', None)
```

In a normal type system, you would have to declare weight/bias as `Optional[Tensor]`, as it is not known at compile time what type they are (you must know the type of affine). However, in TorchScript, the type of the module is not ascribed until after the module has been constructed, at which point we **do** know what the type of `affine` is. So if you don't annotate weight/bias, TorchScript will properly infer `None` or `Tensor` as their types.

Here's the problem: if you annotate weight/bias for mypy, TorchScript will directly use this annotation, and no longer carry out its own type inference. And this in turn may cause code that previously typechecked in TorchScript to stop typechecking. This means that adding *most general* mypy signatures for modules can cause TorchScript to stop working.

There should be some way to force TorchScript to do type inference, even if there is an annotation. The relevant code is pretty easy to change, so the big question is what the syntax for triggering this type inference should be.

cc @gmagogsfm @ezyang @malfet @rgommers @xuzhao9 @gramster @suo
Repository: pytorch
Issue: TestTorchDeviceTypeCPU.test_float_to_int_conversion_finite_cpu_uint8 is broken on PowerPC
Labels: module: tests,triaged,module: POWER

From https://powerci.osuosl.org/job/pytorch-master-nightly-py3-linux-ppc64le/1099/console
```
======================================================================
FAIL: test_float_to_int_conversion_finite_cpu_uint8 (__main__.TestTorchDeviceTypeCPU)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/home/jenkins/miniconda/lib/python3.7/site-packages/torch/testing/_internal/common_device_type.py", line 241, in instantiated_test
    result = test(self, device_arg, dtype)
  File "/home/jenkins/miniconda/lib/python3.7/site-packages/torch/testing/_internal/common_device_type.py", line 542, in only_fn
    return fn(self, device, *args, **kwargs)
  File "test_torch.py", line 17152, in test_float_to_int_conversion_finite
    self._float_to_int_conversion_helper(vals, device, dtype)
  File "test_torch.py", line 17127, in _float_to_int_conversion_helper
    self.assertEqual(torch.from_numpy(a), t.cpu())
  File "/home/jenkins/miniconda/lib/python3.7/site-packages/torch/testing/_internal/common_utils.py", line 1085, in assertEqual
    self.assertTrue(result, msg=msg)
AssertionError: False is not true : Tensors failed to compare as equal! Found 2 different element(s) (out of 9), with the greatest difference of 255 (0 vs. 255) occuring at index 2.
```

cc @mruberry
Repository: flutter
Issue: Consider attempting to reconnect when the connection to a device is lost
Labels: tool,a: quality,P3,team-tool,triaged-tool

Currently when we lose a connection to a device -- whether it's because of a bad USB cable, a crashed or hung app, or a bug in our code somewhere -- we just disconnect with "Lost connection to device".

We should consider attempting to reconnect when this happens. Suggested UI:

First few times this happens in a session:
```
Lost connection to attached device. Attempting to reconnect. This will fail if the application has crashed or hung. /
```

If we notice that this has happened several times, and if we're somewhat confident that this is a connection over USB (as opposed to a simulator, same-host desktop or web app, adb-over-wifi, etc), we could replace the message with:
```
Lost connection to attached device again. Consider replacing your USB cable, it may be damaged. \
```
Repository: rust
Issue: Closure outlives error should mention the source of the requirement
Labels: C-enhancement,A-diagnostics,A-lifetimes,A-closures,T-compiler,D-confusing,D-newcomer-roadblock

The following code:

```rust
struct Inner;
struct Outer {
    field: Inner
}
fn use_it<R, F: FnOnce(&Outer) -> R>(_val: F) {}
fn main() {
    use_it(|outer| &outer.field)
}
```

produces the following error message as of `nightly-2020-06-07`

```
error: lifetime may not live long enough
 --> src/main.rs:7:20
  |
7 |     use_it(|outer| &outer.field)
  |             ------ ^^^^^^^^^^^^ returning this value requires that `'1` must outlive `'2`
  |             |    |
  |             |    return type of closure is &'2 Inner
  |             has type `&'1 Outer`
```

In general, returning a reference derived from an argument is perfectly fine. The issue is that `use_it` requires that the return type outlive the argument - however, this is not mentioned anywhere in the error message.

When we emit a lifetime error message for closures, we should try to find the reason for the requirement, and give a more detailed explanation to the user.
Repository: godot
Issue: C# Mono Build: Marking a asset to copy to output directory does not get copied to final export location
Labels: bug,topic:dotnet

**Godot version:** 
3.2.1

**OS/device including version:**
Win10(x64)

**Issue description:**
I marked a DLL in visual studio to copy to output location, but the DLL was not copied to the export location

**Steps to reproduce:**
Add some miscellaneous file to visual studio marked with a action of none, and always copy to output folder

_Bugsquad edit:_ reorganized for clarity
Repository: pytorch
Issue: [BatchNorm] Add boolean flags to choose the stats for normalization
Labels: module: nn,triaged,function request,module: norms and normalization

## 🚀 Flags for flexibility in BN
Hello there :wave: 

Following up on discussions with @SsnL in #37823 and #38084, I believe some clarifications are needed in the behaviour of the `forward` method of Batch normalization layers.

Concisely, the point of this issue would be to discuss the following points:
1. ability to dynamically tell the layer whether it should update its population stats' estimators (buffer) or not
2. ability to dynamically tell the layer whether the stats used for normalization should be the actual current mini-batch stats or the already seen population's estimators (buffer).
3. the train --> eval switch should use the computed population mean & variance for normalization if they are available, prevent population estimators from updating, and avoid updating the affine parameters.

## Motivation

Initially, I was only looking for the best way to use `BatchNorm2d` in frozen layers (in the case of transfer learning). Obviously, `FrozenBatchNorm2d` from torchvision was a good option but required replacing all BNs in a model (and there was no eps in frozenBN until very recently). I went looking for a simple flag that would work in vain (this needs to apply for both train and eval modes, otherwise the frequent switches that occur during a training procedure make it irrelevant)

## Pitch

First, `track_running_stats` should be converted into a constructor argument but not an attribute since it can be switched by the user later (meaning we cannot dynamically rely on this to assume whether the buffer is available and/or has been tracked)

Second, we could introduce two dynamic flags:
- `update_running_stats` (only renaming the original track_running_stats actually): controls whether the buffer should be updated on forward
- `minibatch_normalization`: controls whether the mini-batch stats should be used for data normalization instead of population estimators (buffer) during forward.

Since, in the current API, switching to train/eval mode does not change the parameters' requires_grad then:

- updating population stats (buffer) is only done if `self.update_running_stats and self.training`
- normalization is done with mini-batch stats rather than buffer's if `self.minibatch_normalization or self.training`


cc @albanD @mruberry
Repository: go
Issue: x/build/env/android-*-emu: adb does not propagate GO_BUILDER_NAME to tests
Labels: Builders,NeedsFix

The GO_BUILDER_NAME environment variable doesn't seem to be set on tests running on the android-amd64-emu builders.

How to reproduce:

I created CL [236960](https://go-review.googlesource.com/c/tools/+/236960) with the following test in it:

```
package a_test

import (
	"os"
	"testing"
)

func TestPlatform(t *testing.T) {
	t.Fatalf("GO_BUILDER_NAME = %q", os.Getenv("GO_BUILDER_NAME"))
}
```

on the android-amd64-emu builder, the test fails with the following error:

```
--- FAIL: TestPlatform (0.00s)
    platform_test.go:9: GO_BUILDER_NAME = ""
FAIL
exitcode=1FAIL	golang.org/x/tools/a	84.167s
```
Repository: go
Issue: cmd/vet: flag simple nil pointer dereferences for struct field usage and nil map assignments
Labels: NeedsInvestigation,Analysis

Coming here from an experience report narrated to me offline by @kastiglione and @indragiek.

The code below is biting yet can be trivially flagged by cmd/vet
### Usage of field in an obvious nil struct
https://play.golang.org/p/i_a3kGE61UZ
![724716BA-8467-4A68-8D9D-3F30840DC6FB](https://user-images.githubusercontent.com/4898263/84085411-6901ba00-a99a-11ea-8471-36f3e7afc534.png)

### Assignment to a nil map
https://play.golang.org/p/KlN7AY1U4lo
![5FA92B7F-78A6-4410-B9F1-8FDE1F551504](https://user-images.githubusercontent.com/4898263/84085543-a9f9ce80-a99a-11ea-86d1-f0a006576363.png)
Repository: angular
Issue: refactor(forms): unification of template-driven validator logic
Labels: refactoring,area: forms,forms: validators,P5

Currently the template-driven validators logic is a bit inconsistent where some validators use `@Input` getters/setters when in other cases we use `ngOnChanges` lifecycle hook to achieve the same behavior (see [packages/forms/src/directives/validators.ts](https://github.com/angular/angular/blob/030eff2b81fdf3750a6604415dbdffcb43f8d159/packages/forms/src/directives/validators.ts)). We should explore if we can unify this logic (most likely using `ngOnChanges` to always have a consistent behavior between Ivy/VE, based on https://github.com/angular/angular/issues/35330#issuecomment-638859443).

We should also check whether we can unify these conditions too (they seem very similar, but vary in minor details):
https://github.com/angular/angular/blob/030eff2b81fdf3750a6604415dbdffcb43f8d159/packages/forms/src/directives/validators.ts#L174
and 
https://github.com/angular/angular/blob/030eff2b81fdf3750a6604415dbdffcb43f8d159/packages/forms/src/directives/validators.ts#L284

[note: this is a low priority item atm and will probably be a breaking change]
Repository: pytorch
Issue: Run `clang-tidy` on the `aten` folder?
Labels: module: lint,triaged,module: build warnings,better-engineering

Seems that we only run `clang-tidy`on `torch/csrc/`. 



https://github.com/pytorch/pytorch/blob/0147216a46a67b110334ae246e1b032611099b19/.github/workflows/lint.yml#L152-L165


Should we run it on `aten` (or maybe just `aten/src/ATen`) as well?