sharjeelyunus/github-issues-dataset huggingface dataset:
Repository: material-ui
Issue: [Autocomplete] Can't select helper text content
Labels: bug 🐛,component: autocomplete

- [x] The issue is present in the latest release.
- [x] I have searched the [issues](https://github.com/mui-org/material-ui/issues) of this repository and believe that this is not a duplicate.

## Current Behavior 😯

When providing a `helperText` using the `Autocomplete` component with the `TextField` component, it's not possible to select the actual helper text content.

## Expected Behavior 🤔

I expect the help text content to be selectable. As it works with just using the `TextField` component.

Working example: https://codesandbox.io/s/material-demo-forked-l8rom
Non-working example: https://codesandbox.io/s/material-demo-forked-102o6

## Steps to Reproduce 🕹

Steps:

1. Visit https://codesandbox.io/s/material-demo-forked-102o6
2. Try to select the helper text

## Context 🔦

I am trying to select the help text content that belongs to the text field.

## Your Environment 🌎

<details>
  <summary>`npx @material-ui/envinfo`</summary>
  
```
  System:
    OS: macOS 10.15.6
    CPU: (8) x64 Intel(R) Core(TM) i5-8279U CPU @ 2.40GHz
    Memory: 47.25 MB / 16.00 GB
    Shell: 5.0.11 - /usr/local/bin/bash
  Binaries:
    Node: 14.16.1 - ~/.nvm/versions/node/v14.16.1/bin/node
    npm: 6.14.12 - ~/.nvm/versions/node/v14.16.1/bin/npm
  Managers:
    Homebrew: 2.5.8 - /usr/local/bin/brew
    pip2: 19.3 - /Library/Frameworks/Python.framework/Versions/2.7/bin/pip2
    pip3: 19.2.3 - /Library/Frameworks/Python.framework/Versions/3.7/bin/pip3
    RubyGems: 3.0.3 - /usr/bin/gem
  Utilities:
    Make: 3.81 - /usr/bin/make
    GCC: 4.2.1 - /usr/bin/gcc
    Git: 2.23.0 - /usr/local/bin/git
    Clang: 11.0.3 - /usr/bin/clang
  Servers:
    Apache: 2.4.41 - /usr/sbin/apachectl
  Virtualization:
    Docker: 20.10.5 - /usr/local/bin/docker
    Parallels: 13.3.2 - /usr/local/bin/prlctl
    VirtualBox: 6.0.4 - /usr/local/bin/vboxmanage
  SDKs:
    iOS SDK:
      Platforms: iOS 13.6, DriverKit 19.0, macOS 10.15, tvOS 13.4, watchOS 6.2
  IDEs:
    IntelliJ: 2020.3
    Nano: 2.0.6 - /usr/bin/nano
    Sublime Text: 3211 - /usr/local/bin/subl
    VSCode: 1.55.2 - /usr/local/bin/code
    Vim: 8.1 - /usr/local/bin/vim
    Xcode: 11.6/11E708 - /usr/bin/xcodebuild
  Languages:
    Bash: 5.0.11 - /usr/local/bin/bash
    Perl: 5.30.0 - /usr/local/bin/perl
    PHP: 7.3.11 - /usr/bin/php
    Python: 2.7.16 - /Library/Frameworks/Python.framework/Versions/2.7/bin/python
    Python3: 3.7.7 - /Library/Frameworks/Python.framework/Versions/3.7/bin/python3
    Ruby: 2.6.3 - /usr/bin/ruby
  Databases:
    MySQL: 10.14 - /usr/local/bin/mysql
    PostgreSQL: 11.5 - /usr/local/bin/postgres
    SQLite: 3.28.0 - /usr/bin/sqlite3
  Browsers:
    Chrome: 90.0.4430.93
    Edge: 90.0.818.51
    Safari: 14.0
```
</details>
Repository: pytorch
Issue: Unknown builtin op: torchvision::nms in LibTorch
Labels: oncall: jit,module: serialization,module: vision

## Unknown builtin op: torchvision::nms in LibTorch
pytorch vision: 1.8.0
libtorch version: 1.8.1

Try to trace the implementation of YOLOV5 [here](https://github.com/ultralytics/yolov5) and load it from LibTorch, which uses `torchvision.ops.nms` in the postprocessing step.

The model can be traced successfully, but error occurs when trying to load the traced model in LibTorch:
```
terminate called after throwing an instance of 'torch::jit::ErrorReport'
  what():
Unknown builtin op: torchvision::nms.
Could not find any similar ops to torchvision::nms. This op may not exist or may not be currently supported in TorchScript.
```
Are torchvision.ops supported in LibTorch at present? and what should I do to solve the problem?


cc @mruberry @fmassa @vfdev-5 @pmeier @gmagogsfm
Repository: material-ui
Issue: Add Responsive nav bar component
Labels: new feature,component: app bar

<!-- Provide a general summary of the feature in the Title above -->

<!--
  Thank you very much for contributing to Material-UI by creating an issue! ❤️
  To avoid duplicate issues we ask you to check off the following list.
-->

<!-- Checked checkbox should look like this: [x] -->

- [x] I have searched the [issues](https://github.com/mui-org/material-ui/issues) of this repository and believe that this is not a duplicate.

## Summary 💡
The app bar should automatically stack up depending on the width of the window. This is a very common use case of the responsive top navbar.
<!-- Describe how it should work. -->

## Examples 🌈
A similar component is available in bootstrap which is very handy and easy to code.
https://getbootstrap.com/docs/5.0/components/navbar/#responsive-behaviors 
The codepen implementation shows it:
https://codepen.io/Hendawy/pen/BPgNrx
<!--
  Provide a link to the Material design specification, other implementations,
  or screenshots of the expected behavior.
-->

## Motivation 🔦
The current app bar requires so much effort/code to make it responsive. Since this use case is very common and widely used in all websites, it would be great if there simple method available built-in material UI app bar component.
<!--
  What are you trying to accomplish? How has the lack of this feature affected you?
  Providing context helps us come up with a solution that is most useful in the real world.
-->

## Benchmarks

- https://getbootstrap.com/docs/5.0/components/navbar/
Repository: rust
Issue: Reserved Prefixes RFC: How to handle `TokenStream::from_str`?
Labels: F-reserved_prefixes

@m-ou-se [raised a point](https://github.com/rust-lang/rfcs/pull/3101#issuecomment-832686934) on rust-lang/rfcs#3101 that needs to be resolved in some way:

> Since this makes the lexer edition-dependent, what will this mean for `proc_macro::TokenStream::from_str`? That takes a string without any span/edition info. Does it use the edition of the proc macro crate? Or of the crate the proc macro was invoked from? (And if so, what does that mean if it was invoked by a macro_rules macro from an edition 2018 crate which was in turn invoked from a 2021 crate?) Or does it always use the latest edition?
Repository: pytorch
Issue: nn.TransformerEncoder cannot deal with large negative value even when this value is masked by src_key_padding_mask
Labels: module: nn,triaged,module: correctness (silent)

## 🐛 Bug

<!-- A clear and concise description of what the bug is. -->
nn.TransformerEncoder cannot input large negative value even when this value is masked by src_key_padding_mask

theoretically the value is masked by the padding mask will have no effect to the output, but in pytorch this will cause the whole batch become NaN value

## To Reproduce

Steps to reproduce the behavior:

1.
![image](https://user-images.githubusercontent.com/37648124/117289639-2d27eb00-aeb0-11eb-87bf-db530029da66.png)

2.
![image](https://user-images.githubusercontent.com/37648124/117289686-3ca73400-aeb0-11eb-997d-d36937f4e0ea.png)

3.
![image](https://user-images.githubusercontent.com/37648124/117289925-8b54ce00-aeb0-11eb-9824-64b426fef137.png)


## Environment

PyTorch version: 1.7.1
Is debug build: False
CUDA used to build PyTorch: 11.0
ROCM used to build PyTorch: N/A

OS: Arch Linux (x86_64)
GCC version: (GCC) 10.2.0
Clang version: 11.1.0
CMake version: version 3.20.2

Python version: 3.8 (64-bit runtime)
Is CUDA available: True
CUDA runtime version: 11.3.58
GPU models and configuration: GPU 0: NVIDIA GeForce RTX 3090
Nvidia driver version: 465.27
cuDNN version: Could not collect
HIP runtime version: N/A
MIOpen runtime version: N/A

Versions of relevant libraries:
[pip3] numpy==1.19.2
[pip3] numpydoc==1.1.0
[pip3] torch==1.7.1
[pip3] torchaudio==0.7.0a0+a853dff
[pip3] torchvision==0.8.2
[conda] blas                      1.0                         mkl  
[conda] cudatoolkit               11.0.221             h6bb024c_0  
[conda] mkl                       2020.2                      256  
[conda] mkl-service               2.3.0            py38he904b0f_0  
[conda] mkl_fft                   1.2.0            py38h23d657b_0  
[conda] mkl_random                1.1.1            py38h0573a6f_0  
[conda] numpy                     1.19.2           py38h54aff64_0  
[conda] numpy-base                1.19.2           py38hfa32c7d_0  
[conda] numpydoc                  1.1.0              pyhd3eb1b0_1  
[conda] pytorch                   1.7.1           py3.8_cuda11.0.221_cudnn8.0.5_0    pytorch
[conda] torchaudio                0.7.2                      py38    pytorch
[conda] torchvision               0.8.2                py38_cu110    pytorch



cc @albanD @mruberry @jbschlosser @walterddr @mikaylagawarecki @zhangguanheng66
Repository: pytorch
Issue: Incorporate Posit Support
Labels: triaged,needs research

## 🚀 Feature
Incorporate support for Posit number format as another dtype of PyTorch

## Motivation
The Posit number format (introduced in [Beating Floating Point at its Own Game](http://www.johngustafson.net/pdfs/BeatingFloatingPoint.pdf)) has been sparking a lot of interest in the research community lately, in particular for its potential on low precision training and inference of Neural Networks. 
Researchers have been building their own frameworks for deep learning on top of Posit, some based on PyTorch (such as [PositNN](https://github.com/hpc-ulisboa/posit-neuralnet)), others on TensorFlow (such as [Deep PeNSieve](https://github.com/RaulMurillo/deep-pensieve)).
However, it would be much nicer to have PyTorch support Posit, so that it could be used directly for research without the need to build a framework from scratch.

## Ideas For Implementation
Following [Issue#52673](https://github.com/pytorch/pytorch/issues/52673) and after some discussion with @RaulMurillo, I believe that the best way to do this is by having different Posit types be supported as another dtype, backed by an external library such as [Universal](https://github.com/stillwater-sc/universal) and register kernel implementations to the dispatcher for each method.
[Issue#755](https://github.com/pytorch/pytorch/issues/755) and [Issue#33152](https://github.com/pytorch/pytorch/issues/33152) hold a history of the process that complex numbers went through until they became supported, and I was thinking that a similar process could be undergone for Posits.
Since I am quite inexperienced in PyTorch and its internals, I would love to have some insights on this suggestion: if it makes sense to go this way, if there are obstacles that I should be aware of, etc.
@albanD @ezyang (and other people interested), is this a good way forward?
Repository: go
Issue: x/pkgsite: better error message on bad path
Labels: NeedsFix,pkgsite

https://pkg.go.dev/github.com/gomarkdown displays a page that just says "400 Bad Request". It should say more about the problem.
Repository: go
Issue: database/sql: SetConnMaxIdleTime, SetConnMaxLifetime order impacts close time
Labels: NeedsInvestigation

### What version of Go are you using (`go version`)?

<pre>
$ go version
go version go1.16.3 linux/amd64
</pre>

### Does this issue reproduce with the latest release?
Yes

### What operating system and processor architecture are you using (`go env`)?

<details><summary><code>go env</code> Output</summary><br><pre>
$ go env
GO111MODULE=""
GOARCH="amd64"
GOBIN=""
GOCACHE="/home/carsten/.cache/go-build"
GOENV="/home/carsten/.config/go/env"
GOEXE=""
GOFLAGS=""
GOHOSTARCH="amd64"
GOHOSTOS="linux"
GOINSECURE=""
GOMODCACHE="/home/carsten/go/pkg/mod"
GONOPROXY="dev.azure.com/xtp"
GONOSUMDB="dev.azure.com/xtp"
GOOS="linux"
GOPATH="/home/carsten/go"
GOPROXY="https://proxy.golang.org,direct"
GOROOT="/snap/go/7360"
GOSUMDB="sum.golang.org"
GOTMPDIR=""
GOTOOLDIR="/snap/go/7360/pkg/tool/linux_amd64"
GOVCS=""
GOVERSION="go1.16.3"
GCCGO="gccgo"
AR="ar"
CC="gcc"
CXX="g++"
CGO_ENABLED="1"
GOMOD="/dev/null"
CGO_CFLAGS="-g -O2"
CGO_CPPFLAGS=""
CGO_CXXFLAGS="-g -O2"
CGO_FFLAGS="-g -O2"
CGO_LDFLAGS="-g -O2"
PKG_CONFIG="pkg-config"
GOGCCFLAGS="-fPIC -m64 -pthread -fmessage-length=0 -fdebug-prefix-map=/tmp/go-build3305456222=/tmp/go-build -gno-record-gcc-switches"
GOROOT/bin/go version: go version go1.16.3 linux/amd64
GOROOT/bin/go tool compile -V: compile version go1.16.3
uname -sr: Linux 5.8.0-50-generic
Distributor ID:	Ubuntu
Description:	Ubuntu 20.04.2 LTS
Release:	20.04
Codename:	focal
/lib/x86_64-linux-gnu/libc.so.6: GNU C Library (Ubuntu GLIBC 2.31-0ubuntu9.2) stable release version 2.31.
gdb --version: GNU gdb (Ubuntu 9.2-0ubuntu1~20.04) 9.2
</pre></details>

### What did you do?
When using
```go
db.SetConnMaxIdleTime(5 * time.Second)
db.SetConnMaxLifetime(5 * time.Hour)
```
idle connections get closed after 5 hours. While setting the parameters in reverse order works fine.
```go
db.SetConnMaxLifetime(5 * time.Hour)
db.SetConnMaxIdleTime(5 * time.Second)
```

### What did you expect to see?
Closing idle connections after ~5s.


### What did you see instead?
Closing connections after ~5h

I think this is due to [sql.go#L1041](https://github.com/golang/go/blob/b4ca1cec69f8248b77d8d8ce019943ced5235ed0/src/database/sql/sql.go#L1041) only checking if `maxIdleTime` has been reduced and not also if its smaller than `maxLifetime`.
Repository: godot
Issue: VisualShaders don't like being externally updated while Godot is running
Labels: bug,topic:editor,topic:visualscript,topic:shaders

**Godot version:**
3.3


**OS/device including version:**
Windows 10 (19042.928)


**Issue description:**
When you change your files (a git pull in this case) while the editor is running, a change is detected by Godot and it asks you what to do with the changed files. If you press reload, it will throw a bunch of errors and overwrites with the old state.

<details>
<summary>Error</summary>

```
 scene/resources/visual_shader.cpp:322 - Condition "p_node.is_null()" is true.
 scene/resources/visual_shader.cpp:359 - Condition "!g->nodes.has(p_id)" is true.
 scene/resources/visual_shader.cpp:517 - Index p_to_port = 1 is out of bounds (g->nodes[p_to_node].node->get_input_port_count() = 0).
 scene/resources/visual_shader.cpp:517 - Index p_to_port = 0 is out of bounds (g->nodes[p_to_node].node->get_input_port_count() = 0).
 scene/resources/visual_shader.cpp:516 - Condition "!g->nodes.has(p_to_node)" is true.
 scene/resources/visual_shader.cpp:516 - Condition "!g->nodes.has(p_to_node)" is true.
 scene/resources/visual_shader.cpp:514 - Condition "!g->nodes.has(p_from_node)" is true.
```

</details>

**Steps to reproduce:**
1. Open the project
2. Overwrite CubeMaterial.tres with the one not in the project
3. Enjoy red text and a broken Material

**Minimal reproduction project:**
[shaderupdate.zip](https://github.com/godotengine/godot/files/6434664/shaderupdate.zip)
Repository: godot
Issue: Godot won't start with monitor over dockingstation
Labels: bug,platform:windows,topic:porting,needs testing

**Godot version:**
3.3 Standard, 64/32-bit (both)

**OS/device including version:**
HP EliteBook 850 G5 i7-8550U 15.6 UHD
AMD Radeon R59
Intel UHD Graphics 620
Targus ACP71EU DisplayLink

GLES2 and GLES3

**Issue description:**
When starting godot "nothing" happens:
  C:\...\Godot_v3.3-stable_win64.exe>Godot_v3.3-stable_win64.exe --verbose --debug
  Godot Engine v3.3.stable.official - https://godotengine.org

  C:\...\Godot_v3.3-stable_win64.exe>   

This only happens when the dock is connected. The same monitor connected directly to the laptop works as expected.


**Steps to reproduce:**
Plug in to a Targus ACP7 dock. Try to open godot (from cmd or via double click).

**Minimal reproduction project:**
not related to any project
Repository: godot
Issue: SkeletonIK acting oddly
Labels: bug,topic:animation,topic:3d

<!-- Please search existing issues for potential duplicates before filing yours:
https://github.com/godotengine/godot/issues?q=is%3Aissue
-->

**Godot version:** 3.2.3, 3.3
<!-- Specify commit hash if using non-official build. -->


**OS/device including version:**
<!-- Specify GPU model, drivers, and the backend (GLES2, GLES3, Vulkan) if graphics-related. -->
Ubuntu Linux 64 bit 20.04, OpenGL ES 3.0 Renderer: GeForce GTX 960/PCIe/SSE2, NVidia 460.73.01


**Issue description:**
<!-- What happened, and what was expected. -->
Attached video shows that when I do a simple export from Blender and bring into godot, and set up a SkeletonIK, a weird stair stepping bend happens to the object when I "Play IK" and move the target object. I tried asking in some user group areas but nobody seemed to have any idea why this was happening. So, I am filing this issue for more "official" help :) .

https://user-images.githubusercontent.com/12647891/117310473-4d748d00-ae51-11eb-9f9a-564ef0835ef4.mp4


**Steps to reproduce:**
See video

**Minimal reproduction project:**
<!-- A small Godot project which reproduces the issue. Drag and drop a zip archive to upload it. -->
Repository: PowerToys
Issue: [Github] Add checkbox for user searched duplicated
Labels: Area-GitHub workflow

Maybe add on all templates a checkbox "I've searched for existing issues with the same problem/suggestion"

_Originally posted by @Aaron-Junker in https://github.com/microsoft/PowerToys/issues/11105#issuecomment-832154533_
Repository: vscode
Issue: Git - Add ability to have ignored repository wildcards
Labels: feature-request,git

<!-- ⚠️⚠️ Do Not Delete This! feature_request_template ⚠️⚠️ -->
<!-- Please read our Rules of Conduct: https://opensource.microsoft.com/codeofconduct/ -->
<!-- Please search existing issues to avoid creating duplicates. -->

<!-- Describe the feature you'd like. -->
When I open a file from a bazel output, it opens a separate git repository (which is just a mirror of my current repository since it is just the bazel directory). I would like to be able to ignore all files in my bazel cache via a wildcard as shown in the screenshot, but currently it only takes direct paths. This is not useful since bazel adds a unique hash to the cache folder.
<img width="856" alt="Screen Shot 2021-05-06 at 10 12 22 AM" src="https://user-images.githubusercontent.com/15133828/117313909-4e5aee00-ae54-11eb-9089-aef9b1a77bcd.png">
Repository: pytorch
Issue: object with __torch_functon__ does not work with jit function 
Labels: oncall: jit

## 🐛 Bug

Following https://pytorch.org/docs/stable/notes/extending.html#extending-torch to extend a python object to have an `__torch_function__` method does not work with functions created with torch.jit.script
## To Reproduce

```python

import torch


def _to_tensor(val):
    if isinstance(val, State):
        return val.state
    return val


class State:
    def __init__(self):
        super().__init__()
        self.state = torch.ones(1)
    def __repr__(self):
        return f"{self.__class__.__name__}: {self.state}"
    @classmethod
    def __torch_function__(cls, func, types, args=(), kwargs=None):
        if kwargs is None:
            kwargs = {}
        with torch._C.DisableTorchFunction():
            args = [_to_tensor(arg) for arg in args]
            kwargs = {key: _to_tensor(val) for key, val in kwargs.items()}
            ret = func(*args, **kwargs)
            return ret

def add(a, b):
    return torch.add(a, b)

state=State()
add(state, state) # == tensor([2.]) 
torch.jit.script(add)(state, state) # RuntimeError

```
## Expected behavior
I would expect that functions created with `torch.jit.script` would utilize `__torch_function__` and work just like the non jited function

## Environment
PyTorch version: 1.8.1+cu102
Is debug build: False
CUDA used to build PyTorch: 10.2
ROCM used to build PyTorch: N/A

OS: Manjaro Linux (x86_64)
GCC version: (GCC) 10.2.0
Clang version: Could not collect
CMake version: Could not collect

Python version: 3.7 (64-bit runtime)
Is CUDA available: True
CUDA runtime version: Could not collect
GPU models and configuration: GPU 0: GeForce MX250
Nvidia driver version: 460.73.01
cuDNN version: Could not collect
HIP runtime version: N/A
MIOpen runtime version: N/A

Versions of relevant libraries:
[pip3] numpy==1.17.5
[pip3] torch==1.8.1
[pip3] torchvision==0.9.1
[conda] Could not collect


cc @gmagogsfm
Repository: go
Issue: go/build: should not arbitrarily resolve conflicting package names
Labels: NeedsInvestigation

https://play.golang.org/p/ZnGePWG7Fqs illustrates (at least) two problems with the `go/build` API:

1. When `ImportDir` is called on a directory containing files with conflicting `package` declarations, the returned `build.Package` has its `Name` field set (arbitrarily!) to the first package-name seen in any of the files, and the `InvalidGoFiles` listed for the package include only the files with package names other than the arbitrary one. That seems wrong to me: if the package has conflicting names, it isn't up to `go/build` to decide which of those is “correct” — it should report _all_ of the files as erroneous.

2. The same file is listed twice in `InvalidGoFiles`.

This issue is about problem (1). (I will fix problem (2) separately, because it seems trivial.)

CC @jayconrod @matloob @rsc
Repository: pytorch
Issue: [structured] Meta-impl split implies redundant dtype tests
Labels: triaged,better-engineering

A meta function is supposed to raise an error if input dtypes are incorrect. So we must do a condition on the input dtype to check if they are valid.

A typical kernel needs to do a dispatch on dtype to actually get to the dtype-specialized kernel.

This means that the meta-impl split means we have to redundantly condition on dtypes twice, whereas previously it only needed to be done once. It would be nice if this weren't the case.
Repository: create-react-app
Issue: react-dev-utils uses a vulnerable version of browserslist as a dependency
Labels: stale,needs triage,issue: bug report

react-dev-utils package uses a vulnerable version (4.14.2) of browserslist as a dependency.
See: https://nvd.nist.gov/vuln/detail/CVE-2021-23364

react-dev-utils should be updated to use the latest version 4.16.6 of browserslist.
Repository: tauri
Issue: Generate beautiful DMG files on CI
Labels: type: feature request

A limitation of the bundler is that it uses [applescript](https://github.com/tauri-apps/tauri/blob/e37e187d4a3c7568463c2546099d03dd5a314f40/tooling/bundler/src/bundle/macos/templates/dmg/bundle_dmg#L328) to set the window size, icon position etc (so the DMG looks good). It doesn't work on CI because it accesses the Finder, which prompts for access.

The node-appdmg library creates a .DS_Store file instead of using applescript: https://github.com/LinusU/node-appdmg/blob/e1394d24b1be7799a3949ad0686cd9abb64339ee/lib/appdmg.js#L359

Maybe we could do the same? We would need to port [node-ds-store](https://github.com/LinusU/node-ds-store) to Rust.