sharjeelyunus/github-issues-dataset huggingface dataset:
Repository: pytorch
Issue: ☂️  Issues that trigger crashes due to corner-case API usages
Labels: triaged,module: edge cases

### 🐛 Describe the bug

Does not seem like a real user issues, but detected using some sort of API fuzzing:
- https://github.com/pytorch/pytorch/issues/87960
- https://github.com/pytorch/pytorch/issues/87961
- https://github.com/pytorch/pytorch/issues/87963
- https://github.com/pytorch/pytorch/issues/87964
- https://github.com/pytorch/pytorch/issues/94594


Sanitizer detected issues:
- https://github.com/pytorch/pytorch/issues/88724
- https://github.com/pytorch/pytorch/issues/88940
- https://github.com/pytorch/pytorch/issues/88939

### Versions

None
Repository: rust
Issue: It should be possible to get a mutable reference to a ZST literal
Labels: A-zst,T-types

The following code is legal:

```rust
fn get_mut_ref<'a>() -> &'a mut [u8] {
    &mut []
}
```

However, if we instead use `()`, it's no longer legal:

```rust
fn get_mut_ref<'a>() -> &'a mut () {
    &mut ()
}
```

We get this error:

```text
error[E0515]: cannot return reference to temporary value
 --> src/lib.rs:2:5
  |
2 |     &mut ()
  |     ^^^^^--
  |     |    |
  |     |    temporary value created here
  |     returns a reference to data owned by the current function
```

Is there a reason that the former is legal while the latter is not? I would expect the latter to be legal - in the general case, it'd be great if it were legal for _any_ ZST, although I'm sure that's more complicated (especially in a generic context).

On Fuchsia, we're currently using [this hack](https://fuchsia-review.googlesource.com/c/fuchsia/+/741462/8/src/connectivity/lib/packet-formats/src/ipv6/ext_hdrs.rs#1154) to work around this limitation.
Repository: stable-diffusion-webui
Issue: [Feature Request]: Few Shot Patch Based Training
Labels: enhancement,extension-request

### Is there an existing issue for this?

- [X] I have searched the existing issues and checked the recent builds/commits

### What would your feature do ?

This: 
https://github.com/nicolai256/Few-Shot-Patch-Based-Training

Looks really good at creating temporally stable videos from keyframes. Seems much better than Deforum in that regard. Would be great to see this implemented. 

### Proposed workflow

A new Tab in the UI with this method

### Additional information

_No response_
Repository: flutter
Issue: [Windows] Improve Switch widget accessibility
Labels: a: accessibility,platform-windows,a: desktop,P2,team-windows,triaged-windows

## Problem 
Windows uses MSAA checkbox for the `Switch` widget accessibility. See: https://github.com/flutter/engine/pull/36177

This announces the switch's state as `Checked` and `Not checked`.

## Solution

When we switch to UI Automation, we should implement the [Toggle Control Pattern](https://learn.microsoft.com/en-us/windows/win32/winauto/uiauto-implementingtoggle) to properly announce switches.

## Repro

```dart
Scaffold(
  appBar: AppBar(
    // Here we take the value from the MyHomePage object that was created by
    // the App.build method, and use it to set our appbar title.
    // We also apply a custom font, ProductSans.
    title: Text(widget.title, style: TextStyle(fontFamily: 'ProductSans')),
  ),
  body: Column(
    children: [
      Switch(
        value: value,
        onChanged: onChanged,
      ),
    ],
  ),
);
```

Use a screen reader and interact with the `Switch`.
Repository: material-ui
Issue: [Tooltip] Cannot access links within Tooltips by tabbing if there is another Tooltip on page
Labels: bug 🐛,component: tooltip

### Duplicates

- [X] I have searched the existing issues

### Latest version

- [X] I have tested the latest version

### Steps to reproduce 🕹

Link to live example: https://codesandbox.io/s/tooltip-accessibility-bug-vhh4hm?file=/index.js

Steps:

1. Have more than one tooltip on a page, each containing a link
2. To test accessibility, tab through the page to open each tooltip and try to open each link


### Current behavior 😯

Cannot access the link within the first tooltip by tabbing. Only the link in the last tooltip is accessible.

### Expected behavior 🤔

Links within a tooltip should be accessible via the tab button, and I should be able to press enter or space to open the link.

### Context 🔦

We use tooltips to explain things further to users. There is a case where we provide a link within a tooltip to one of our other pages if users need to get in touch with us. However, it's not accessible because the link gets skipped and immediately focuses on the next tooltip. We require accessibility to support a large part of our userbase.

### Your environment 🌎

In production, we use still use version 4 of MUI: `"@material-ui/core": "^4.11.3"`.

Browser tested in Chrome: `107.0.5304.87`

<details>
  <summary><code>npx @mui/envinfo</code></summary>

```
    System:
    OS: macOS 11.6
  Binaries:
    Node: 15.2.1 - ~/.nvm/versions/node/v15.2.1/bin/node
    Yarn: Not Found
    npm: 6.14.9 - ~/.nvm/versions/node/v15.2.1/bin/npm
  Browsers:
    Chrome: 107.0.5304.87
    Edge: Not Found
    Firefox: Not Found
    Safari: 14.1.2

```
</details>
Repository: tauri
Issue: [bug] app crash when called window.close() in tauri::command on macos
Labels: type: bug,platform: macOS,status: needs triage

### Describe the bug

**tauricomand:**
```rs
#[tauri::command[async]]
fn close_window(window: tauri::Window) {
     if window.close().is_err() {
         error!("failed to close window");
     }
}
```

and i also added api prevent_exit()
```rs
app.run(move |_app_handle, e| {
        if let RunEvent::ExitRequested { api, .. } = &e {
            api.prevent_exit();
        }
})
```

call this command on React ,app will stop and show nothing on macos
but it works good on windows

### Reproduction

_No response_

### Expected behavior

_No response_

### Platform and versions

Environment
  › OS: Mac OS 13.0.0 X64
  › Node.js: 18.3.0
  › npm: 8.11.0
  › pnpm: Not installed!
  › yarn: 1.22.18
  › rustup: 1.24.3
  › rustc: 1.61.0
  › cargo: 1.61.0
  › Rust toolchain: stable-aarch64-apple-darwin 

Packages
  › @tauri-apps/cli [NPM]: 1.0.0
  › @tauri-apps/api [NPM]: 1.1.0
  › tauri [RUST]: 1.1.1,
  › tauri-build [RUST]: 1.1.1,
  › tao [RUST]: 0.14.0,
  › wry [RUST]: 0.21.1,

App
  › build-type: bundle
  › CSP: unset
  › distDir: ../build
  › devPath: http://localhost:3000/
  › framework: React

App directory structure
  ├─ node_modules
  ├─ public
  ├─ src-tauri
  ├─ build
  ├─ .git
  ├─ installer
  └─ src

### Stack trace

```shell
DOESN'T EXIST
```


### Additional context

_No response_
Repository: opencv
Issue: The current Mat::at has no constraints for the data type of different channels as the source.
Labels: feature

### Descripe the feature and motivation

The current Mat::at has no constraints for the data type of different channels as the source. And, it will cause a little confusion in some code practices.

For example:
``` c++
cv::Mat img(rows, cols, CV_64F);
```
The number of channels of `img` is 1, however, the following operations are still correct since the number of channels of `cv::Vec3d` is 3.

``` c++
img.at<cv::Vec3d>(0, 0)[0] = 255.0;
img.at<cv::Vec3d>(0, 0)[1] = 255.0;
img.at<cv::Vec3d>(0, 0)[2] = 255.0;
```

The [] operation in cv::Vec limits the number of channels, but it cannot limit the converted ones in this case.

**I personally feel that the better way is to add some assertions or warnings that appear during compile time.**

### Additional context
Related PR: https://github.com/opencv/opencv/pull/22733

_No response_
Repository: material-ui
Issue: [joy-ui][Tabs] Scrollable variant
Labels: new feature,component: tabs,package: base-ui,package: joy-ui

### Duplicates

- [X] I have searched the existing issues

### Latest version

- [X] I have tested the latest version

### Summary 💡

Tabs should feature a scrollable variant for smaller screen sizes.

### Examples 🌈

MUI Material: https://mui.com/material-ui/react-tabs/#scrollable-tabs

### Motivation 🔦

Scrollable tabs.
Repository: stable-diffusion-webui
Issue: [Feature Request]: Explore potential StableDiffusion speed benefits from implementing kernl (Up to 12X faster GPU inference)
Labels: enhancement

### Is there an existing issue for this?

- [X] I have searched the existing issues and checked the recent builds/commits

### What would your feature do ?

Explore whether implementing kernl would provide speedups for Stable Diffusion.

- https://github.com/ELS-RD/kernl
  - > Kernl lets you run PyTorch transformer models several times faster on GPU with a single line of code, and is designed to be easily hackable.
- https://www.reddit.com/r/MachineLearning/comments/ydqmjp/p_up_to_12x_faster_gpu_inference_on_bert_t5_and/
  - > Up to 12X faster GPU inference on Bert, T5 and other transformers with OpenAI Triton kernels

### Proposed workflow

N/A

### Additional information

- Crossposted on:
  - https://github.com/huggingface/diffusers/issues/1094
  - https://github.com/ELS-RD/kernl/issues/141
- A few other potential speedup/efficiency gain issues:
  - https://github.com/AUTOMATIC1111/stable-diffusion-webui/issues/1625
  - https://github.com/AUTOMATIC1111/stable-diffusion-webui/issues/4606
  - https://github.com/AUTOMATIC1111/stable-diffusion-webui/issues/4721
Repository: storybook
Issue: [Bug]: non-story content not working with angular components
Labels: bug,needs triage

### Describe the bug

Canvas without Story but using angular components inside, is not working. I followed the docs: https://storybook.js.org/docs/angular/writing-docs/doc-block-canvas#non-story-content.

There seems to be a problem with instantiation:
![image](https://user-images.githubusercontent.com/36576424/199184444-4dea1402-089b-4889-85ae-80f7f7f0d4ef.png)

My Component
```ts
import { CommonModule } from '@angular/common';
import { Component } from '@angular/core';

@Component({
  selector: 'inova-figma-frame',
  standalone: true,
  imports: [CommonModule],
  template: ` <p>figma-frame works!</p> `,
  styleUrls: ['./figma-frame.component.scss'],
})
export class FigmaFrameComponent {}
```

My mdx story:
```mdx
import { Meta, Story, Canvas } from '@storybook/addon-docs';
import { FigmaFrameComponent } from '../../demo';

<Meta title="Design Tokens / Elevations" component={FigmaFrameComponent} />

<Canvas>
  <FigmaFrameComponent />
</Canvas>
```


### To Reproduce

```shell
npx sb@next repro didn't work:

An error occurred while executing: `yarn set version berry && yarn config set enableGlobalCache true && yarn config set nodeLinker node-modules`
🚨 Installing Yarn 2 failed
🚨 Failed to create repro

But to reproduce it, is simple, as described above.
```


### System

```shell
System:
    OS: Windows 10 10.0.19044
    CPU: (16) x64 11th Gen Intel(R) Core(TM) i7-11700K @ 3.60GHz
  Binaries:
    Node: 16.10.0 - C:\Program Files\nodejs\node.EXE
    npm: 7.24.2 - C:\Program Files\nodejs\npm.CMD
  Browsers:
    Edge: Spartan (44.19041.1266.0), Chromium (106.0.1370.52)   
  npmPackages:
    @storybook/addon-essentials: ~6.5.9 => 6.5.12 
    @storybook/addons: ^6.5.12 => 6.5.12 
    @storybook/angular: ~6.5.9 => 6.5.12 
    @storybook/builder-webpack5: ~6.5.9 => 6.5.12
    @storybook/core-server: ~6.5.9 => 6.5.12
    @storybook/manager-webpack5: ~6.5.9 => 6.5.12
    @storybook/theming: ^6.5.12 => 6.5.12
```


### Additional context

_No response_
Repository: opencv
Issue: Expose missing imgproc operations to G-API python
Labels: feature,category: python bindings,category: g-api / gapi

### Descripe the feature and motivation

All `imgproc` G-API operations can be found there: https://github.com/opencv/opencv/blob/4.x/modules/gapi/include/opencv2/gapi/imgproc.hpp

Most of them already have prefix `GAPI_EXPORTS_W` that means they're exposed to python, but a few of them still not.
The main obstacle is signature of that functions is complex from python parser/generator perspective.
Need to invent how composite types such as `GArray<GArray<Point>>` can be handled by parser/gen automatically without hand-written implementation

Missing operations:
* `GArray<GArray<Point>> findContours(...)` - 2 overloads
* `std::tuple<GArray<GArray<Point>>,GArray<Vec4i>> findContoursH(...)` - 2 overloads
* `GOpaque<Vec4f> fitLine2D(...)` - 4 overloads 
* `GOpaque<Vec6f> fitLine3D(...)` - 4 overloads
* `GMatP NV12toRGBp(...)`
* `GMatP NV12toBGRp(...)`
* ` GMatP resizeP(...)`

### Additional context

_No response_
Repository: pytorch
Issue: `torch.mm` Trigger RuntimeError with UndefinedBehaviorSanitizer
Labels: triaged,module: sanitizers

### 🐛 Describe the bug

A test case for `torch.mm` aborted because of runtime error when it's run with the undefined behavior sanitizer. Without sanitizers, the program terminated normally.
Reproduction:
```python
import torch

def test():
    arg_1_tensor = torch.rand([0, 64], dtype=torch.float32)
    arg_1 = arg_1_tensor.to_sparse()
    arg_2_tensor = torch.rand([64, 1], dtype=torch.float32)
    arg_2 = arg_2_tensor.to_sparse()
    res = torch.mm(arg_1,arg_2,)

test()
```
Error log:
```bash
/home/yuyao/dev/pytorch/c10/core/TensorImpl.h:1495:38: runtime error: applying non-zero offset 8 to null pointer
```
It seems that the error can be triggered only if we use sparse tensors.

### Versions

```
PyTorch version: 1.14.0a0+gita86278b
Is debug build: False
CUDA used to build PyTorch: Could not collect
ROCM used to build PyTorch: N/A

OS: Ubuntu 22.04.1 LTS (x86_64)
GCC version: (Ubuntu 11.3.0-1ubuntu1~22.04) 11.3.0
Clang version: 11.1.0-6
CMake version: version 3.24.1
Libc version: glibc-2.35

Python version: 3.10.6 (main, Aug 10 2022, 11:40:04) [GCC 11.3.0] (64-bit runtime)
Python platform: Linux-5.15.0-50-generic-x86_64-with-glibc2.35
Is CUDA available: False
CUDA runtime version: 11.6.124
CUDA_MODULE_LOADING set to: N/A
GPU models and configuration: 
GPU 0: NVIDIA GeForce RTX 3090
GPU 1: NVIDIA GeForce RTX 3090
GPU 2: NVIDIA GeForce RTX 3090

Nvidia driver version: 515.65.01
cuDNN version: Probably one of the following:
/usr/lib/x86_64-linux-gnu/libcudnn.so.8.4.1
/usr/lib/x86_64-linux-gnu/libcudnn_adv_infer.so.8.4.1
/usr/lib/x86_64-linux-gnu/libcudnn_adv_train.so.8.4.1
/usr/lib/x86_64-linux-gnu/libcudnn_cnn_infer.so.8.4.1
/usr/lib/x86_64-linux-gnu/libcudnn_cnn_train.so.8.4.1
/usr/lib/x86_64-linux-gnu/libcudnn_ops_infer.so.8.4.1
/usr/lib/x86_64-linux-gnu/libcudnn_ops_train.so.8.4.1
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True

Versions of relevant libraries:
[pip3] numpy==1.21.5
[pip3] torch==1.14.0a0+gita86278b
[pip3] torchvision==0.13.1
[conda] blas                      1.0                         mkl  
[conda] cudatoolkit               11.3.1               h2bc3f7f_2  
[conda] mkl                       2021.4.0           h06a4308_640  
[conda] mkl-service               2.4.0            py39h7f8727e_0  
[conda] mkl_fft                   1.3.1            py39hd3c417c_0  
[conda] mkl_random                1.2.2            py39h51133e4_0  
[conda] numpy                     1.21.5           py39he7a7128_1  
[conda] numpy-base                1.21.5           py39hf524024_1  
[conda] numpydoc                  1.2                pyhd3eb1b0_0
```
Repository: go
Issue: crypto: add ContextSigner and use in crypto/tls
Labels: Proposal,Proposal-Accepted,Proposal-Crypto

This was previously proposed in #28427 but rejected. However, I don't think it was given proper consideration.

As mentioned in #28427, it is possible for a crypto.Signer to require remote calls to some external service such as AWS KMS. Currently the `Sign` method does not take a `context.Context`, meaning that the timeout/cancellation and any logging/monitoring metadata cannot make it across the method call. @bcmills mentioned using currying to simulate this but that does not work well with the crypto/tls API (and possibly others). Instead the desire there would be to forward the context from `HandshakeContext` across.

I propose the following changes. First add a new interface to crypto.
```go
type ContextSigner interface {
	Signer
	SignContext(ctx context.Context, rand io.Reader, digest []byte, opts SignerOpts) (signature []byte, err error)
}
```

Then add a helper function to crypto. (Not strictly required but will make people's lives easier.)
```go
func SignContext(ctx context.Context, s Signer, rand io.Reader, digest []byte, opts SignerOpts) (signature []byte, err error) {
    cs, ok := s.(ContextSigner)
    if !ok {
        return s.Sign(rand, digest, opts)
    }
    return cs.SignContext(ctx, rand, digest, opts)
}
```

Then the internals of net/tls can be amended to call the new `crypto.SignContext` function from `HandshakeContext`.
Repository: pytorch
Issue: Moving tensor to GPU by .cuda() gets stucked when AMD Secure Encripted Virtualization (SEV) is activated
Labels: module: cuda,module: rocm,triaged

### 🐛 Describe the bug

My workstation is equipped with an AMD Threadripper 3960x and GPUs of 30 series, with Ubuntu 22.04.1 installed. 

Before I activated the AMD SEV, everything is normal. After I activated the AMD SEV by:
1. change the line <GRUB_CMDLINE_LINUX_DEFAULT="quite splash"> to <GRUB_CMDLINE_LINUX_DEFAULT="quite splash mem_encrypt=on kvm_amd.sev=1"> in /etc/default/grub to enable AMD SEV.
2. run 'sudo update-grub'.
3. reboot.

The ".to('cuda')" or ".cuda()" operations get stucked for Pytorch tensor: I tested in the terminal
```
import torch
a = torch.rand(5).cuda()
```
and got stucked (no response for a long time). Meanwhile, I founded that the GPU memory does not change and there was only one CPU core busy.

After I disabled the AMD SEV by restoring <GRUB_CMDLINE_LINUX_DEFAULT="quite splash">  in  /etc/default/grub, the bug disappeared.



### Versions

CPU: AMD Threadripper 3960x
OS: Ubuntu 22.04.01
Linux kernel:  5.15.0-52-generic
GCC version: gcc (Ubuntu 11.3.0-1ubuntu1~22.04) 11.3.0

Tested driver: nvidia-driver-510, nvidia-driver-520
Tested pytorch version: 1.12, 1.3 (latest)
Tested python version: 3.10.4, 3.10.6.


cc @ngimel @jeffdaily @sunway513 @jithunnair-amd @ROCmSupport
Repository: vscode
Issue: enter and automatic indentataion
Labels: info-needed

Type: <b>Bug</b>

when i press the enter key after a tag or a function it doesn`t make the automatic indentation i used to

VS Code version: Code 1.72.2 (d045a5eda657f4d7b676dedbfa7aab8207f8a075, 2022-10-12T22:15:18.074Z)
OS version: Windows_NT x64 10.0.19044
Modes:
Sandboxed: No

<details>
<summary>System Info</summary>

|Item|Value|
|---|---|
|CPUs|Intel(R) Core(TM) i5-10210U CPU @ 1.60GHz (8 x 2112)|
|GPU Status|2d_canvas: enabled<br>canvas_oop_rasterization: disabled_off<br>direct_rendering_display_compositor: disabled_off_ok<br>gpu_compositing: enabled<br>multiple_raster_threads: enabled_on<br>opengl: enabled_on<br>rasterization: enabled<br>raw_draw: disabled_off_ok<br>skia_renderer: enabled_on<br>video_decode: enabled<br>video_encode: enabled<br>vulkan: disabled_off<br>webgl: enabled<br>webgl2: enabled<br>webgpu: disabled_off|
|Load (avg)|undefined|
|Memory (System)|7.84GB (3.80GB free)|
|Process Argv|--crash-reporter-id 0cbe3a7a-c7eb-40fc-b739-9a7ee6d52cad|
|Screen Reader|no|
|VM|0%|
</details><details><summary>Extensions (32)</summary>

Extension|Author (truncated)|Version
---|---|---
rainbow-brackets|2gu|0.0.6
vscode-django|bat|1.10.0
blackbox|Bla|0.3.5
vscode-html-css|ecm|1.13.1
vsc-material-theme|Equ|33.5.0
vsc-material-theme-icons|equ|2.4.0
prettier-vscode|esb|9.9.0
vscode-firefox-debug|fir|2.9.8
auto-rename-tag|for|0.1.10
code-runner|for|0.11.8
live-sass|gle|5.5.1
rest-client|hum|0.25.1
tab-indent-space-align|j-z|0.0.3
fluent-icons|mig|0.0.18
python|ms-|2022.16.1
vscode-pylance|ms-|2022.10.40
jupyter|ms-|2022.9.1202862440
jupyter-keymap|ms-|1.0.0
jupyter-renderers|ms-|1.0.10
vscode-jupyter-cell-tags|ms-|0.1.6
vscode-jupyter-slideshow|ms-|0.1.5
indent-rainbow|ode|8.3.1
material-icon-theme|PKi|4.21.0
material-product-icons|PKi|1.4.1
vscode-css-peek|pra|4.2.0
LiveServer|rit|5.7.9
vscode-field-lights|sve|0.0.11
sass-indented|syl|1.8.22
ayu|tea|1.0.5
bootstrap4-vscode|the|6.1.0
vscode-icons|vsc|12.0.1
JavaScriptSnippets|xab|1.8.0

(6 theme extensions excluded)

</details><details>
<summary>A/B Experiments</summary>

```
vsliv368:30146709
vsreu685:30147344
python383cf:30185419
vspor879:30202332
vspor708:30202333
vspor363:30204092
vslsvsres303:30308271
pythonvspyl392:30443607
vserr242:30382549
pythontb:30283811
vsjup518:30340749
pythonptprofiler:30281270
vshan820:30294714
vstes263:30335439
vscoreces:30445986
pythondataviewer:30285071
vscod805cf:30301675
binariesv615:30325510
bridge0708:30335490
bridge0723:30353136
cmake_vspar411:30581797
vsaa593:30376534
pythonvs932:30410667
cppdebug:30492333
vsclangdc:30486549
c4g48928:30535728
dsvsc012cf:30540253
azure-dev_surveyone:30548225
pyindex848:30577860
nodejswelcome1:30587005
fc301958:30595537
2e4cg342:30596373

```

</details>

<!-- generated by issue reporter -->
Repository: angular
Issue: [FR] Automatically unwrap Observables in component views (without async pipe)
Labels: area: core,core: binding & interpolation,cross-cutting: observables,P3

### Which @angular/* package(s) are relevant/related to the feature request?

core

### Description

In some cases, you may have an observable property on a component, potentially multiple observable properties, which haven't been subscribed to in order to follow the rule of not explicitly subscribing to them creating the need to unsubscribe later, or opening your app up to memory leaks.

In your view, you then have to call the async pipe on this observable to 'unwrap' them - internally retrieving and rendering the value for them.

My main line of thinking - is there a reason that you wouldn't want to unwrap your observable in your view, if you're using it there in the first place?

As an example, let's take rendering content for different device screen sizes:

```ts
@Component({
  selector: 'app-x',
  templateUrl: './x.component.html',
  styleUrls: ['./x.component.scss'],
})
export class XComponent {
  isHandset$: Observable<boolean> = this.someFacade.isHandset$;

  constructor(private someFacade: SomeFacade){

  }
}
```

In your view:
```html
<div *ngIf="(isHandset$ | async) === false">
... some content relevant for mobile
</div>

<div *ngIf="(isHandset$ | async)">
... some content relevant for  larger devices
</div>
```

### Proposed solution

I propose handling the detection of an Observable in the view internally too, and essentially doing exactly what the async pipe already does, but without the need to explicitly call it. 

Using the same example:

```ts
@Component({
  selector: 'app-x',
  templateUrl: './x.component.html',
  styleUrls: ['./x.component.scss'],
})
export class XComponent {
  isHandset$: Observable<boolean> = this.someFacade.isHandset$;

  constructor(private someFacade: SomeFacade){

  }
}
```

In your view:
```html
<div *ngIf="!isHandset$">
... some content relevant for mobile
</div>

<div *ngIf="isHandset$">
... some content relevant for  larger devices
</div>
```

### Alternatives considered

As mentioned, I've considered subscribing to the observable internally. 

Additionally, I've also tried potentially creating a view template with template variables referencing the observable, but haven't gotten too far with mapping that solution out.