sharjeelyunus/github-issues-dataset huggingface dataset:
Repository: TypeScript
Issue: Type hierarchy api support 
Labels: Suggestion,Experience Enhancement

# Suggestion

## 🔍 Search Terms
- type hierarchy
- inheritance
- subclass
- superclass

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List of keywords you searched for before creating this issue. Write them down here so that others can find this suggestion more easily and help provide feedback.


## ⭐ Suggestion

VS Code recently introduced a new API for displaying type hierarchies:

- https://github.com/microsoft/vscode/issues/15533
- [api](https://github.com/microsoft/vscode/blob/cbf8b411b9ccce33926bfa2d20f86e0970a85235/src/vs/vscode.d.ts#L4773)

This api is very similar to the exiting call hierarchy api and displayed in a similar way in the editor

Although type hierarchies are most useful for languages like Java that use inheritance heavily, they would also be a nice feature to support for JavaScript and TypeScript
Repository: rust
Issue: mips64-unknown-linux-gnuabi64 rustc unable to produce mips4 binary
Labels: O-MIPS,A-target-specs,C-bug

I am trying to compile rustc, and some applications written in rust for my SGI R10000 workstation, with 64 bit Linux on it.
Found out, that even though I specify -Ctarget-cpu=mips4 for rustc, it always produces MIPS64r2 binaries.
R8000 and later mips CPUs implement MIPS4 architecture, which is a subset of MIPS64 ISA and subset of MIPS32 ISA.

I found, that the default settings in https://github.com/rust-lang/rust/blob/master/compiler/rustc_target/src/spec/mips64_unknown_linux_gnuabi64.rs is too restrictive, and it seems one can not downgrade by passing target-cpu parameter, what is defined in this file (even though, mips3 was the first ISA to support 64bit instructions), and by passing, it silently ignores, and generates executables:
```
ELF 64-bit MSB pie executable, MIPS, MIPS64 rel2 version 1 (SYSV), dynamically linked, interpreter /lib64/ld.so.1, for GNU/Linux 3.2.0, not stripped
```
By applying a simple patch like this:
```
--- compiler/rustc_target/src/spec/mips64_unknown_linux_gnuabi64.rs.old        2021-09-14 16:20:48.323014516 +0200
+++ compiler/rustc_target/src/spec/mips64_unknown_linux_gnuabi64.rs    2021-09-14 16:21:43.482314818 +0200
@@ -10,8 +10,8 @@
         options: TargetOptions {
             endian: Endian::Big,
             // NOTE(mips64r2) matches C toolchain
-            cpu: "mips64r2".to_string(),
-            features: "+mips64r2".to_string(),
+            cpu: "mips4".to_string(),
+            features: "+mips4".to_string(),
             max_atomic_width: Some(64),
             mcount: "_mcount".to_string(),
```
I was able to finally compile executables for R10000 CPU:
```
ELF 64-bit MSB pie executable, MIPS, MIPS-IV version 1 (SYSV), dynamically linked, interpreter /lib64/ld.so.1, for GNU/Linux 3.2.0, not stripped
```
And the -Ctarget-cpu=mips64r2 also worked, to generate what was before the default.

I propose to lower the default / minimum required CPU from mips64r2 to mips3, or mips4.
Repository: flutter
Issue: [localization][tests]: `use-deferred-loading: true` throws  `_WidgetTypeFinder:<zero widgets with type "Scaffold"` exception
Labels: a: tests,framework,a: internationalization,has reproducible steps,P2,found in release: 2.5,team-framework,triaged-framework

## Details

We have a simple unit test that's failing when it is copy pasted and tested twice. 

EG: 

```dart

    testWidgets('should be properly sorted without favorites', (tester) async {
      await tester.pumpWidget(builder());
      await tester.pumpAndSettle();
      final scaffold = find.byType(Scaffold);
      expect(scaffold, findsOneWidget);
    });

    // // // same test if added, fails
    // testWidgets('should be properly sorted without favorites', (tester) async {
    //   await tester.pumpWidget(builder());
    //   await tester.pumpAndSettle();
    //   final scaffold = find.byType(Scaffold);
    //   expect(scaffold, findsOneWidget);
    // });
```

We pinpointed the issue to the custom localization delegate used by the library.  More specifically the deferred loading

Both test pass when using arb files with flutter --gen-l10n, one of two test pass when using `use-deferred-loading: true`
One of the two test fail when loading a json for localization instead.  So maybe `rootBundle.loadString` is at cause here.


## reproduce 

We have two branch here that have been reduced to the minimum to reproduce the issue (at least in the test files);

This one fails when the second test is uncommented. The test is the only one remaining and is in test/_country_selector_test.dart
```
git clone https://github.com/cedvdb/phone_form_field/tree/localization_json && cd phone_form_field && flutter pub get && flutter test

```

This one works with `use-deferred-loading: false` (or not specified) and does not work with it set to true. This can be set in l10n.yaml
```
git checkout localization_arb && flutter pub get && flutter test
```


# Version:

flutter --version
Flutter 2.6.0-0.0.pre • channel dev • https://github.com/flutter/flutter.git
Framework • revision 83b9e99cfb (3 weeks ago) • 2021-08-23 19:03:21 +0200
Engine • revision d5adde01dd
Tools • Dart 2.15.0 (build 2.15.0-42.0.dev)

but I believe it happens on versions anterior to this one.
Repository: youtube-dl
Issue: Segmented VTTs and no Playlist !
Labels: question

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## Question

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Hi Guyz,
I've just downloaded one video file (from a VOD website, not Youtube) that comes with VTT subtitles.
The TS files were downloaded thanks to the M3U8 playlist.
But for some reason the VTT is not playlisted and appears as countless segments such as [this one](https://production.content.okast.tv/d07facb5-86b2-4821-bc29-34ef11dadf42/medias/3d6f0b33-7d07-4ec4-afd8-30ae2f59449f/subtitles_b53bce7c-7475-452a-b1de-b28872eeae81_11.vtt).
Does anyone have any ideas about how to deal with that (i.e. download + merge the VTT segments) ?
Thanks !
Repository: react
Issue: [DevTools Bug]: Hook names fail to parse if source file for Component is an html file
Labels: Type: Bug,Component: Developer Tools

When testing our fixture in Safari (`./fixtures/devtools/standalone/index.html`) with the standalone build if DevTools, I noticed that we were unable to parse hook names because the source file where the components are defined isn't a JavaScript file, and instead an HTML file (as in `index.html`), which contains HTML code, and some JS inside script tags, so the babel parser fails to parse the file.

Specifically:

```javascript
// parseSourceAndMetadata.js

const originalSourceAST = withSyncPerfMeasurements(
  '[@babel/parser] parse(originalSourceCode)',
  () =>
    parse(originalSourceCode, {
      sourceType: 'unambiguous',
      plugins: ['jsx', plugin],
    }),
);
```
In the above code, the call to `parse` fails because `originalSourceCode` is actually html (with JS inside) like:

```
<!DOCTYPE html>
<html>
  <head>
    <meta charset="UTF-8" />
    <title>TODO List</title>

    <!-- ... -->

  <body>
    <div id="root"></div>
    <script type="text/javascript">
      const { useState } = React;

      function App() {
        const [count, setCount] = useState(0);
        return null;
      }

      ReactDOM.render(React.createElement(App), document.getElementById("root"));
    </script>
  </body>
```

And `parse` expects actual JS code.

DevTools should handle the case when source files aren't JS files, and still be able to extract out the hook names, or fail more gracefully. As of #22320, we log to the console a slightly better error message when this happens, as opposed to an obscure parsing error.

### Repro steps

1. Run standalone app
2. Open fixtures file in safari: ./fixtures/devtools/standalone/index.html
3. Try getting hook names, observe that parsing source files fails
Repository: pytorch
Issue: [AWS EC2 P3DN, EFA is enabled] Torch RPC tensorpipe/common/ibv.h:172 "": Operation not supported
Labels: oncall: distributed,triaged,module: rpc,module: tensorpipe,pipeline parallelism

## 🐛 Bug

I got the following error when using sync.Pipe and initializing RPC.

## To Reproduce
I provide a small github repo and related script to reproduce this issue (https://github.com/chaoyanghe/pytorch_bug_reproduce).  A full error log is also maintained there.

## Expected behavior

Successfully run the Pipe demo.

## Environment
I run my source code on AWS EC2 P3DN GPU server. EFA is enabled.

Collecting environment information...
PyTorch version: N/A
Is debug build: N/A
CUDA used to build PyTorch: N/A
ROCM used to build PyTorch: N/A

OS: Amazon Linux 2 (x86_64)
GCC version: (GCC) 7.3.1 20180712 (Red Hat 7.3.1-9)
Clang version: 7.0.1 (Amazon Linux 2 7.0.1-1.amzn2.0.2)
CMake version: version 3.18.2
Libc version: glibc-2.2.5

Python version: 2.7.18 (default, Aug 27 2020, 21:22:52)  [GCC 7.3.1 20180712 (Red Hat 7.3.1-9)] (64-bit runtime)
Python platform: Linux-4.14.200-155.322.amzn2.x86_64-x86_64-with-glibc2.2.5
Is CUDA available: N/A
CUDA runtime version: 11.0.221
GPU models and configuration: 
GPU 0: Tesla V100-SXM2-32GB
GPU 1: Tesla V100-SXM2-32GB
GPU 2: Tesla V100-SXM2-32GB
GPU 3: Tesla V100-SXM2-32GB
GPU 4: Tesla V100-SXM2-32GB
GPU 5: Tesla V100-SXM2-32GB
GPU 6: Tesla V100-SXM2-32GB
GPU 7: Tesla V100-SXM2-32GB

Nvidia driver version: 450.80.02
cuDNN version: Probably one of the following:
/usr/local/cuda-10.1/targets/x86_64-linux/lib/libcudnn.so.7.6.5
/usr/local/cuda-10.2/targets/x86_64-linux/lib/libcudnn.so.7.6.5
/usr/local/cuda-11.0/targets/x86_64-linux/lib/libcudnn.so.8.0.4
/usr/local/cuda-11.0/targets/x86_64-linux/lib/libcudnn_adv_infer.so.8.0.4
/usr/local/cuda-11.0/targets/x86_64-linux/lib/libcudnn_adv_train.so.8.0.4
/usr/local/cuda-11.0/targets/x86_64-linux/lib/libcudnn_cnn_infer.so.8.0.4
/usr/local/cuda-11.0/targets/x86_64-linux/lib/libcudnn_cnn_train.so.8.0.4
/usr/local/cuda-11.0/targets/x86_64-linux/lib/libcudnn_ops_infer.so.8.0.4
/usr/local/cuda-11.0/targets/x86_64-linux/lib/libcudnn_ops_train.so.8.0.4
HIP runtime version: N/A
MIOpen runtime version: N/A

Versions of relevant libraries:
[pip] numpy==1.16.6
[conda] Could not collect



cc @pietern @mrshenli @pritamdamania87 @zhaojuanmao @satgera @rohan-varma @gqchen @aazzolini @osalpekar @jiayisuse @SciPioneer @H-Huang @cbalioglu @gcramer23 @jjlilley @mrzzd @lw @beauby
Repository: rust
Issue: CI: verify-backported-commits.sh is broken
Labels: A-testsuite,C-bug,T-release

In #88946, @Mark-Simulacrum suspected that I was going to fail CI for lack of `backport-of` in my new beta commit. But in the check runs, the test "passed" with this output:

```
Run src/ci/scripts/verify-backported-commits.sh
  src/ci/scripts/verify-backported-commits.sh
  shell: /bin/bash --noprofile --norc -e -o pipefail {0}
  env:
    CI_JOB_NAME: x86_64-gnu-tools
    SCCACHE_BUCKET: rust-lang-ci-sccache2
    TOOLSTATE_REPO: https://github.com/rust-lang-nursery/rust-toolstate
    CACHE_DOMAIN: ci-caches.rust-lang.org
    CI_ONLY_WHEN_SUBMODULES_CHANGED: 1
    IMAGE: x86_64-gnu-tools
fatal: unknown commit 53fd98ca776cb875bc9e5514f56b52eb74f9e7a9
All commits in `HEAD` are present in `master`
```

That unknown commit is the `BETA_LIMIT` at the top of the script, not mine.
Repository: pytorch
Issue: CUDA out of memory
Labels: needs reproduction,module: cuda,module: memory usage,triaged

When trying to run deep_gaze in windows cmd i got this error: RuntimeError: CUDA out of memory. Tried to allocate 128.00 MiB (GPU 0; 6.00 GiB total capacity; 4.22 GiB already allocated; 0 bytes free; 4.24 GiB reserved in total by PyTorch). What's wierd is that when i tried running deep-gaze before there was no issue, so i suspect this is because i downloaded a new version of pytorch (but i'm not sure). Can anyone help me resolve this issue.


cc @ngimel
Repository: flutter
Issue: _CastError: Null check operator used on a null value at MaterialFonts.updateInner(flutter_cache.dart:141)
Labels: c: crash,tool,P2,team-tool,triaged-tool

Number 6 crasher on Flutter 2.5
```
Thread 0 main thread_CastError: Null check operator used on a null value
at MaterialFonts.updateInner(flutter_cache.dart:141)
at CachedArtifact.update(cache.dart:688)
at Cache.updateAll(cache.dart:557)
at <asynchronous gap>(async)
at FlutterCommand.verifyThenRunCommand(flutter_command.dart:1228)
at <asynchronous gap>(async)
at FlutterCommand.run.<anonymous closure>(flutter_command.dart:1125)
at <asynchronous gap>(async)
at AppContext.run.<anonymous closure>(context.dart:150)
at <asynchronous gap>(async)
at CommandRunner.runCommand(command_runner.dart:209)
at <asynchronous gap>(async)
at FlutterCommandRunner.runCommand.<anonymous closure>(flutter_command_runner.dart:288)
at <asynchronous gap>(async)
at AppContext.run.<anonymous closure>(context.dart:150)
at <asynchronous gap>(async)
at FlutterCommandRunner.runCommand(flutter_command_runner.dart:236)
at <asynchronous gap>(async)
at run.<anonymous closure>.<anonymous closure>(runner.dart:62)
at <asynchronous gap>(async)
at AppContext.run.<anonymous closure>(context.dart:150)
at <asynchronous gap>(async)
at main(executable.dart:92)
at <asynchronous gap>(async)
```
https://github.com/flutter/flutter/blob/4cc385b4b84ac2f816d939a49ea1f328c4e0b48e/packages/flutter_tools/lib/src/flutter_cache.dart#L141

Caused by https://github.com/flutter/flutter/pull/85242#discussion_r658287550
> I think the right thing to do is `!` so if it does fail it shows up in crash logging
Repository: deno
Issue: Support configuring proxy via `ALL_PROXY` environment variable
Labels: feat,ext/http

Right now Deno [only looks for](https://deno.land/manual@v1.14.0/linking_to_external_code/proxies) `HTTP_PROXY`, `HTTPS_PROXY` and `NO_PROXY` for proxy configuration. It would be more convenient to support `ALL_PROXY` which controls all protocols.

Popular programs like [curl](https://everything.curl.dev/usingcurl/proxies/env) and [Homebrew](https://docs.brew.sh/Manpage#using-homebrew-behind-a-proxy) all respects `ALL_PROXY` and IMO Deno should follow suit, unless there is a reason not to.
Repository: pytorch
Issue: [pytorch v1.9.0] for torch sync.pipeline in a single GPU, passing tensor layer by layer is better or using the skip-connection API is better?
Labels: oncall: distributed,triaged,pipeline parallelism

## ❓ Questions and Help

For PyTorch pipeline, I think we have two ways to pass tensors to a skipped layer.  Which way has higher performance?

1. passing tensor layer by layer
```
    class Layer1(nn.Module):
        def __init__(self, hidden_size):
            super().__init__()
            self.fc1 = nn.Linear(hidden_size, hidden_size).cuda(local_rank)

        def forward(self, input):
            original_input = input
            return self.fc1(input), original_input

    class Layer2(nn.Module):
        def __init__(self, hidden_size):
            super().__init__()
            self.fc2 = nn.Linear(hidden_size, hidden_size).cuda(local_rank)

        def forward(self, input, original_input):
            return self.fc2(input), original_input

    class Layer3(nn.Module):
        def __init__(self, hidden_size):
            super().__init__()
            self.fc3 = nn.Linear(hidden_size, hidden_size).cuda(local_rank)

        def forward(self, input, original_input):
            return self.fc3(input) + original_input

layer1 = Layer1(hidden_size)
layer2 = Layer2(hidden_size)
layer3 = Layer3(hidden_size)
pipeline_model = nn.Sequential(layer1, layer2, layer3)

#  build Pipe (torch.distributed.pipeline.sync.Pipe)
self.pipeline_model = PipeModelWrapper(Pipe(pipeline_model, chunks=4, checkpoint="never"))
```

2. using skip-connection API
```
    @skippable(stash=['1to3'])
    class Layer1(nn.Module):
        def __init__(self, hidden_size):
            super().__init__()
            self.fc1 = nn.Linear(hidden_size, hidden_size).cuda(local_rank)

        def forward(self, input):
            yield stash('1to3', input)
            return self.fc1(input)

    class Layer2(nn.Module):
        def __init__(self, hidden_size):
            super().__init__()
            self.fc2 = nn.Linear(hidden_size, hidden_size).cuda(local_rank)

        def forward(self, input):
            return self.fc2(input)

    @skippable(pop=['1to3'])
    class Layer3(nn.Module):
        def __init__(self, hidden_size):
            super().__init__()
            self.fc3 = nn.Linear(hidden_size, hidden_size).cuda(local_rank)

        def forward(self, input):
            skip_1to3 = yield pop('1to3')
            return self.fc3(input) + skip_1to3

layer1 = Layer1(hidden_size)
layer2 = Layer2(hidden_size)
layer3 = Layer3(hidden_size)
pipeline_model = nn.Sequential(layer1, layer2, layer3)

#  build Pipe (torch.distributed.pipeline.sync.Pipe)
self.pipeline_model = PipeModelWrapper(Pipe(pipeline_model, chunks=4, checkpoint="never"))
```


cc @pietern @mrshenli @pritamdamania87 @zhaojuanmao @satgera @rohan-varma @gqchen @aazzolini @osalpekar @jiayisuse @SciPioneer @H-Huang @cbalioglu @gcramer23
Repository: go
Issue: x/playground: Faking the network example periodically deadlocks
Labels: NeedsInvestigation

### Problem

While reading about how "Faking the Network" works on the Go playground at https://go.dev/blog/playground, I'm running into the following error almost every time.  

```
fatal error: all goroutines are asleep - deadlock!

goroutine 1 [IO wait]:
internal/poll.runtime_pollWait(0x7f5332a0ee88, 0x72)
	/usr/local/go-faketime/src/runtime/netpoll.go:229 +0x89
internal/poll.(*pollDesc).wait(0xc0000c0000, 0x0, 0x0)
	/usr/local/go-faketime/src/internal/poll/fd_poll_runtime.go:84 +0x32
internal/poll.(*pollDesc).waitRead(...)
	/usr/local/go-faketime/src/internal/poll/fd_poll_runtime.go:89
internal/poll.(*FD).Accept(0xc0000c0000)
	/usr/local/go-faketime/src/internal/poll/fd_unix.go:402 +0x22c
net.(*netFD).accept(0xc0000c0000)
	/usr/local/go-faketime/src/net/fd_unix.go:173 +0x35
net.(*TCPListener).accept(0xc0000ac030)
	/usr/local/go-faketime/src/net/tcpsock_posix.go:140 +0x28
net.(*TCPListener).Accept(0xc0000ac030)
	/usr/local/go-faketime/src/net/tcpsock.go:262 +0x3d
main.main()
	/tmp/sandbox825819739/prog.go:24 +0x102
```

You can reproduce this by clicking on the **Run** button in the blog post a couple times. It does occasionally work and responds with with `Hello, network`. Maybe 1 in 5 times.

### Screenshot

![CleanShot 2021-09-14 at 22 40 49](https://user-images.githubusercontent.com/170299/133366905-64f164ff-458a-4416-9067-4025ff002c06.png)
Repository: ant-design
Issue: Can cascader of the multiple mode support select all function?
Labels: Inactive

- [ ] I have searched the [issues](https://github.com/ant-design/ant-design/issues) of this repository and believe that this is not a duplicate.

### What problem does this feature solve?
In multiple mode, I maybe want to select all options

### What does the proposed API look like?
Is it better to be a default support?


<!-- generated by ant-design-issue-helper. DO NOT REMOVE -->
Repository: terminal
Issue: Add a `minimizeToNotificationArea` action
Labels: Help Wanted,Product-Terminal,Issue-Task,Needs-Tag-Fix,Area-Windowing

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# Description of the new feature/enhancement

When the `minimizeToTray` property is set to true, the window gets minimized to the tray on clicking the minimize button on top right. I feel this is not always a desirable response - people might want to minimize to taskbar (the normal behavior) or minimize to tray, separately. An action called `minimizeToTray` (and a way to set a keybinding for this) would work best - allowing for both behaviors according to what the users want.
This will also allow WT to behave similar to tmux's `detach` - where detaching and minimizing (to taskbar) are distinct behaviors.

# Proposed technical implementation details (optional)

I was reading the discussion here at https://github.com/microsoft/terminal/pull/10368#issuecomment-884294259 - was this action not implemented?
Repository: neovim
Issue: Lua: vim.opt table syntax fails for "fillchars"
Labels: bug,complexity:low,lua

### Neovim version (nvim -v)

NVIM v0.6.0-dev+274-g6188926e0 (latest commit)

### Vim (not Nvim) behaves the same?

not applicable

### Operating system/version

Archlinux

### Terminal name/version

alacritty

### $TERM environment variable

alacritty

### Installation

Custom Build

### How to reproduce the issue

nvim -u NONE
:lua vim.opt.fillchars={'eob:a'}

### Expected behavior

For the vim.opt's table based syntax to work for the "fillchars" option.

### Actual behavior

The tables based syntax for vim.opt with comma separated options does not seem to work properly for the "fillchars" option. `:lua vim.opt.fillchars={'eob:a'}` does not work (invalid argument error) while `:lua vim.opt.fillchars='eob:a'` does and `:lua vim.opt.wildmode={'longest:full'}` does.