sharjeelyunus/github-issues-dataset huggingface dataset:
Repository: create-react-app
Issue: After Build , the page performance degradation,  react ^17.0.37
Labels: needs triage

I just created the code framework with this command today .
```
npx create-react-app my-app
cd my-app
npm start
```
In development mode, my code, page performance is OK .  Average 50 FPS . There are only a few requestAnimationFrame warnings

But after Build, the page performance degradation, only about 15fps, and the error `[Violation] 'requestAnimationFrame' handler 用时 <N> 毫秒`  is not stopped. 

normal , dev :
![image](https://user-images.githubusercontent.com/5111701/144027512-d7019a96-fdab-4912-8a59-ac2b22c8b082.png)

error , build :
![image](https://user-images.githubusercontent.com/5111701/144026204-69c9e2c1-6f8e-48d3-89dc-7402bb47f1fe.png)
![image](https://user-images.githubusercontent.com/5111701/144027145-ecedef08-dde9-44f7-97e8-33e3a21a5d90.png)

http://zyzx.jingge.com:45231/releases/%E7%BA%AF%E7%94%B5%E5%8A%A8%E6%B1%BD%E8%BD%A6%E4%BA%A4%E6%B5%81%E5%85%85%E7%94%B5%E7%B3%BB%E7%BB%9F3D%E7%BB%93%E6%9E%84%E5%B1%95%E7%A4%BA/index.html

package.json
```
{
  "name": "w3dres-web-cra-three",
  "homepage": ".",
  "version": "0.1.0",
  "private": true,
  "dependencies": {
    "@testing-library/jest-dom": "^5.11.4",
    "@testing-library/react": "^11.1.0",
    "@testing-library/user-event": "^12.1.10",
    "@types/jest": "^27.0.3",
    "@types/node": "^16.11.11",
    "@types/react": "^17.0.37",
    "@types/react-dom": "^17.0.11",
    "antd": "^4.17.2",
    "axios": "^0.24.0",
    "gsap": "^3.8.0",
    "hox": "^1.1.4",
    "mitt": "^3.0.0",
    "react": "^17.0.2",
    "react-device-detect": "^2.1.2",
    "react-dom": "^17.0.2",
    "react-helmet-async": "^1.1.2",
    "react-scripts": "4.0.3",
    "three": "^0.134.0",
    "three-spritetext": "^1.6.3",
    "typescript": "^4.5.2",
    "web-vitals": "^1.0.1"
  },
  "scripts": {
    "start": "react-scripts start",
    "build": "react-scripts build",
    "test": "react-scripts test",
    "eject": "react-scripts eject"
  },
  "eslintConfig": {
    "extends": [
      "react-app",
      "react-app/jest"
    ]
  },
  "browserslist": {
    "production": [
      ">0.2%",
      "not dead",
      "not op_mini all"
    ],
    "development": [
      "last 1 chrome version",
      "last 1 firefox version",
      "last 1 safari version"
    ]
  },
  "devDependencies": {
    "@types/three": "^0.134.0"
  }
}
```

------------------------2021-12-02---------------------------------------------------------------------
It feels like a compression plugin problem
https://github.com/umijs/umi/issues/7644
Repository: flutter
Issue: Provide a way to suppress output written to stdout that may violate communication protocols like DAP
Labels: c: new feature,tool,c: proposal,P2,team-tool,triaged-tool

Sometimes when you run a flutter command there is additional output printed to `stdout`, such as:

- downloading the Dart SDK
- downloading other components
- waiting for another Flutter process to release startup lock

There are some commands that use `stdout` for communication, such as `flutter run --machine`, `flutter test --machine`, `flutter debug-adapter` and this violates their protocols. For the first two, client editors just know to handle non-JSON output too, however for `flutter debug-adapter` the output must conform to [the debug adapter protocol](https://microsoft.github.io/debug-adapter-protocol/overview#base-protocol) because it will be used by standard DAP clients that can't make exceptions.

I think some of this output comes from Dart code so the `debug-adapter` command could perhaps opt-out of it, but I think some also comes from the shell scripts (eg. downloading the Dart SDK) so doing it based on the command might be a little trickier (for ex. require parsing the command in the shell scripts).

@christopherfujino do you have any thoughts/opinions on the best way to do this?
Repository: pytorch
Issue: Libtorch dll versioning
Labels: module: binaries,triaged,enhancement,Stale

## 🚀 Feature
Build libraries like torch_cpu, c10, torch_cuda etc. with proper versioning, mode (cpu vs. gpu) and debug / release information in the name.

## Motivation
Let's say I have two dll's, a.dll and b.dll. a.dll depends on libtorch 1.9 cpu version and b.dll depends on libtorch 1.10 cuda version. With the current naming scheme it's not possible to have an application load both a.dll and b.dll. After a.dll is loaded, e.g. c10.dll (cpu version, 1.9.) is already loaded so b.dll will be fed with a wrong version of c10.dll

## Pitch
Libraries could be built in the format library_name_version_backend.dll. E.g.,  c10.dll in version 1.10 would become either c10_110_cpu.dll or c10_110_cuda.dll. This also implies, that torch_cpu_110_cpu.dll now depends on c10_110_cpu.dll.

## Alternatives
Maybe side-by-side assemblies, however I haven't found a solution for the scenario described above yet.

## Additional context
-


cc @ezyang @seemethere @malfet
Repository: nodebestpractices
Issue: New bullet: Choose your framework - Express vs Nest vs Fastify
Labels: stale

I'm about to PR a new architecture bullet that suggests making a thoughtful decision between the major frameworks. The main message is about WHEN to use each. A detailed comparison table will be included as well.

Help me here with ideas about what dimensions/features should we compare between the three.

These ideas will then be put in the comparison table.

Any Ideas?

cc @mikicho @rluvaton
Repository: tensorflow
Issue: [Feature Request] Make tf.unique operations return mask
Labels: stat:awaiting tensorflower,type:feature,comp:ops

**System information**
- TensorFlow version (you are using): 2.7 (request independent of version)
- Are you willing to contribute it (Yes/No): No

**Describe the feature and the current behavior/state.**
tf.unique (also tf.raw_ops versions) return the indices of first occurrence for each element in a tensor as well as the unique
elements themselves. In addition, I would like the API to return a boolean_mask. The reason is that I need to filter the values of a 
tensor B depending on the unique values of a tensor A. Right now I need to construct the mask from indices which is tedious,
error-prone, not very clean and slower since the result is basically already computed. 

**Will this change the current api? How?**
Yes. tf.raw_ops.Unique* methods accept an additional parameter "return_mask" with "False" as default. Using "True" an additional
output ".mask" is included in the result.

**Who will benefit with this feature?**
People who would like to filter a set of tensors based on the result of another.
Repository: material-ui
Issue: [Button] small button text not vertically centered with Roboto
Labels: bug 🐛,design: material,component: button

### Current behavior 😯

The text inside of a button with `size="small"` is not centered vertically. This is especially obvious when used with an icon or a contained/outlined button.

### Expected behavior 🤔

The text inside of a button with `size="small"` is centered vertically.

### Steps to reproduce 🕹

Steps:

1. Use `<Button size="small">text</Button>`
2. Observe text

### Context 🔦

[Codesandbox link](https://codesandbox.io/s/iconlabelbuttons-material-demo-forked-m96yo?file=/demo.tsx)

Screenshots:
Medium (alignment ok)
![medium](https://user-images.githubusercontent.com/1258230/144050249-baaa07ac-af3d-4649-92c1-7b6a8b42e70c.png)

Small (text too high)
![small](https://user-images.githubusercontent.com/1258230/144050251-7e55a463-1a53-4140-8dd9-dfc3e3682577.png)


### Your environment 🌎

<details>
  <summary>`npx @mui/envinfo`</summary>

```
  Don't forget to mention which browser you used.
  Output from `npx @mui/envinfo` goes here.
```
</details>
Repository: storybook
Issue: Storybook 6.4 with Angular 13 breaks lifecycle hooks of abstract component
Labels: bug,has workaround,angular

**Describe the bug**
In my Angular 13 project using Storybook 6.4, I am using an abstract component to destroy Observables. There I provide a subject, and in `ngOnDestroy()` that subject is completed. Since Storybook 6.4, I am getting a runtime error in those stories where I use that abstract component:

> this.destroy$.next is not a function

It seems like the subject is already destroyed.

**To Reproduce**
https://github.com/dsimon-onventis/storybook-lifecycle-errors-repro

Open one of the "Button" stories, and then navigate to another story.

**System**
Environment Info:

  System:
    OS: Linux 5.10 Ubuntu 20.04.3 LTS (Focal Fossa)
    CPU: (8) x64 Intel(R) Core(TM) i5-8365U CPU @ 1.60GHz
  Binaries:
    Node: 14.18.1 - /usr/local/bin/node
    Yarn: 3.1.1 - /usr/bin/yarn
    npm: 8.1.4 - ~/.npm-global/bin/npm
  Browsers:
    Chrome: 96.0.4664.45
  npmPackages:
    @storybook/addon-actions: ^6.4.1 => 6.4.1
    @storybook/addon-docs: ^6.4.1 => 6.4.1
    @storybook/addon-essentials: ^6.4.1 => 6.4.1
    @storybook/addon-links: ^6.4.1 => 6.4.1
    @storybook/angular: ^6.4.1 => 6.4.1
    @storybook/builder-webpack5: ^6.4.1 => 6.4.1
    @storybook/manager-webpack5: ^6.4.1 => 6.4.1

**Additional context**
With `angularLegacyRendering` set to true, there are no runtime errors.
Repository: deno
Issue: FFI: Loading libraries as dependencies/URLs
Labels: suggestion,FFI

Currently `Deno.dlopen` takes a file path to load a binary library for use with FFI. However, in developing third party packages that use FFI, it seems like we would want the binary library to be treated like another dependency, like modules, accessible as a URL as part of the distribution (either absolutely or relatively). If I understand correctly, Deno works hard to abstract away the concept of "files" when dealing with modules, preferring to access them through URLs (and caching them in its own directory). It seems somewhat antithetical that FFI should be based on direct access to files. In particular, this seems like it creates a problematic distribution process; in order to load the binary library as part third-party package, we would need to:
* Check if the binary library file exists
* If it does not exists, fetch it from the source URL
* Save it to the file system (and figure out a good place to save it)

All of this is basically reinventing the wheel of dependency fetching/caching that Deno usually provides, and requires unnecessarily elevated permissions to accomplish.

Perhaps I am missing something about how this is supposed to work? Or should there be a way to access and load FFI binary libraries in a similar referencing manner as other dependencies/modules?

I know this has been discussed a little bit previously, so there may already be ideas for how this should work, but if you are looking for suggestions, maybe something like this would be a reasonable way to load an FFI library:
```
// URL/path is pretty much always going to be dynamic
const urlForBinary = 'https://cdn.com/lib.' + (os == 'windows' ? 'dll' : 'so');
const binaryFile = await import(urlForBinary, { assert: { type: 'binary' } });
const lib = Deno.dlopen(binaryFile, { ... all my symbols ... });
```
(`binaryFile` could be a `File` or something completely opaque that Deno could use to pass the cached file path to the OS to load the library).
Repository: react
Issue: Bug: Rendering content inside an iFrame using createPortal with Firefox is blank
Labels: Type: Bug,Status: Unconfirmed

<!--
  Please provide a clear and concise description of what the bug is. Include
  screenshots if needed. Please test using the latest version of the relevant
  React packages to make sure your issue has not already been fixed.
-->
I'm trying to render JSX content inside an iFrame using createPortal. It works fine in Edge, Chrome, but in Firefox the iframe body stays empty. 
React version: 17.0.2

## Steps To Reproduce

1. Render an iframe
2. Use createPortal inside the iframe with an element i.e <p>test</p>

<!--
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Link to code example: https://n6lyi.csb.app/

<!--
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  repository on GitHub, or provide a minimal code example that reproduces the
  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
In Firefox, the iframe content shows for like 300ms, then goes blank.

## The expected behavior
It should show content we passed using createPortal.
Repository: godot
Issue: `OS.shell_open()` does not build newlines correctly on HTML5
Labels: bug,platform:web,topic:core,topic:porting

### Godot version

3.4.stable

### System information

Linux

### Issue description

I use shell_open to open an email. The body for the email is inline in the code:

    var _ignore = OS.shell_open("mailto:?body=First line\r\nSecond line")

I would expect this to make a newline on all platforms. However, when i compile to HTML5 and load the website in android or on MacOS, the two lines are together without separator.

### Steps to reproduce

Compile an HTML5 application that has the line

    var _ignore = OS.shell_open("mailto:?body=First line\r\nSecond line")

on a linux machine, then load it in a webbrowser.

### Minimal reproduction project

_No response_
Repository: pytorch
Issue: RuntimeError: Global alloc not supported yet in TorchScript
Labels: oncall: jit

I am trying run a torch.jit.script model on Nvidia 1030 GPU and model does inferencing on RTX3060 but not on 1030 and throws a runtime error RuntimeError: Global alloc not supported yet

```
  File "/usr/local/lib/python3.8/dist-packages/torch/nn/modules/module.py", line 1102, in _call_impl
    return forward_call(*input, **kwargs)
RuntimeError: Global alloc not supported yet
```
More details about the implementation
- Torchscript runs properly on the 1030 as a python implementation
- But not working as expected when using with ROS2 
- I get this error at RUN time 
- The error persisted in normal python implementation as well but changing the batchsize fixed it 
- But when using with ROS2 batchsize fix not working
Please help @iseeyuan @gmagogsfm @cbalioglu
Repository: material-ui
Issue: [Select] TypeScript example for Object values
Labels: support: question,component: select

### Duplicates

- [X] I have searched the existing issues

### Latest version

- [X] I have tested the latest version

### Summary 💡

I would like to use an object as a value for my select field with TypeScript, without having to use IDs and going back and forth between index, string and object conversions.

I got a working example, but TypeScript still complains about incorrect typings.

Help would be greatly appreciated.

### Examples 🌈

I couldn't find a decent template for MUI-5 + typescript, but here's the code example:

```typescript
type ItemType = {
  myStr: string,
  myNbr: number,
  myBool: boolean
};

const items: ItemType[] = [
  {
    myStr: "myStr1",
    myNbr: 1,
    myBool: false
  },
  {
    myStr: "myStr2",
    myNbr: 2,
    myBool: true
  }
];

export default function Test() {
  const [selectedItem, setSelectedItem] =
    React.useState<ItemType | undefined>(undefined);

  return (
    <Select
      value={selectedItem}
      onChange={(selectEvent) => setSelectedItem(selectEvent.target.value)}
    >
      <MenuItem value={undefined}>All</MenuItem>
      {items.map((item) => (
        <MenuItem key={item.myStr} value={item}>{item.myStr}</MenuItem>
      ))}
    </Select>
  );
}
```

I'm getting errors, because onChange is expecting `string | ItemType` instead of `undefined | ItemType` and same error for `MenuItem` value.

### Motivation 🔦

_No response_
Repository: flutter
Issue: [Suggestion] Provide a way to assert that a given Widget is a Sliver
Labels: c: new feature,framework,f: scrolling,c: proposal,P3,team-framework,triaged-framework

## Use case

Currently a `CustomScrollView` accepts a list of slivers.
This list is currently a `List<Widget>`.

However this creates a bit of confusion.
If I put a `Container` or any other regular widget in that list,
I will get an exception since I used a Widget that is not a Sliver implementation.

Secondly, there is no easy option to assert that a given `Widget` is actually a `Sliver` implementation 
(aside from checking against all known Sliver types, i.e. `assert(widget is SliverList || widget is SliverGrid || ...)`).
The current slivers are divided into implementations of `SingleChildRenderObjectWidget` and `SliverMultiBoxAdaptorWidget` (and others?).

There is no way to easily assert that a Widget is a Sliver, regardless of its actual runtime type.

## Proposal

Make it possible to use an assert to check if a Widget is actually a Sliver.
I.e. `assert(myWidget is SliverWidget, "This widget must be a Sliver.")`

Perhaps the different Sliver implementations implement a common (but empty) interface?
```
/// All the Sliver widgets implement this interface.
/// This makes it easier to check if a given [Widget] is a Sliver.
abstract class SliverWidget {}
```
Repository: godot
Issue: Help search shows overriden properties in results
Labels: bug,topic:editor,usability

### Godot version

3.4 / 4.0 2a702cf

### System information

W10

### Issue description

Title.
![image](https://user-images.githubusercontent.com/2223172/144078802-4449c5bf-8840-480a-acda-9d26022c6052.png)
They shouldn't be here. In case above, only the last `mouse_filter` should be displayed, because it's Control property.

### Steps to reproduce

1. F1
2. mouse_filter

### Minimal reproduction project

_No response_
Repository: pytorch
Issue: Generalized matmul
Labels: feature,triaged,module: linear algebra

## 🚀 Feature

There are many different matmul-like operations:
- mm
- mv
- bmm
- baddmm
- baddbmm
- addbmm
- matmul
- linear

Tensor extension writers have to worry about all of these operations:
- these all exist at the `__torch_function__` level
- many of these are primitives (mm, mv, bmm, ...) at the `__torch_dispatch__` level

We should try to unify all of them into calling a single primitive matmul operation.

## Motivation

Tensor extension writers have a difficult time writing overrides for all of the following 

## Pitch

Needs design. One possibility is that we make `matmul` the base operation and write decompositions of all of the above into using `add` + `matmul` and make the decompositions available for Tensor extension writers.

## Alternatives

n/a


cc @jianyuh @nikitaved @pearu @mruberry @walterddr @IvanYashchuk @xwang233 @Lezcano
Repository: flutter
Issue: making `buildTextSpan` a parameter inside `TextField`
Labels: c: new feature,framework,f: material design,c: proposal,team-design,triaged-design

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     to what you're looking for, then fill out the template below. Please read
     our guide to filing a bug first: https://flutter.dev/docs/resources/bug-reports
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## Use case

I always wanted to build a textfield of multiple features with flutter. The current feature that the flutter textfield lack is the dynamic annotation and rendering of the text inside the `TextField`. For example i want give user feature to write bold text, italic, monospace(for codes) or mentioning anybody with @ symbol in a single `Textfield` like a super textField. I found few solutions online but they are extending the `EditableText` class but the issue for me is to not lose all the feature that `TextField` comes with and write a `TextField` like widget from scratch. Also there are few packages in pub, but none of them are fully customisable or not having enough support for all kind of usage. 

## Proposal

`EditableText` has a method override called `buildTextSpan` which only used for obscuring the password by dynamically changing the text. If this method could be made available inside the `TextField` widget as a parameter, the rendering of text inside `TextField` can be done on user's end.
Repository: pytorch
Issue: Unicode Normalization with Torchscript
Labels: oncall: jit,Stale

## ❓ Questions and Help
I am writing a AlbertTokenizer based preprocessor which can be serialized using Torchscript. 

One of the preprocessor steps is doing unicode normalization (ref implementation in HFs's [AlbertTokenizer](https://github.com/huggingface/transformers/blob/master/src/transformers/models/albert/tokenization_albert.py#L210))
```
outputs = unicodedata.normalize("NFKD", outputs)
```

However, when I try to serialize the preprocesor with this code, I get following error

```
Python builtin <built-in function normalize> is currently not supported in Torchscript:
  File "<ipython-input-9-dcefac57d541>", line 53
        outputs = text
        if not self.keep_accents:
            outputs = unicodedata.normalize("NFKD", outputs)
                      ~~~~~~~~~~~~~~~~~~~~~ <--- HERE
    #             outputs = "".join([c for c in outputs if not unicodedata.combining(c)])
        return outputs

```

What is the recommended way to perform Unicode Normalization while making sure the code is serializable?
Repository: pytorch
Issue: Confusing value of `TORCH_CUDA_ARCH_LIST`
Labels: module: build,triaged,Stale

I am not sure about semantic meaning of `TORCH_CUDA_ARCH_LIST` but it seems that in this [branching][code] wrong CMake command is used. As far as I understand CMake [reference][ref], command `EXISTS` in conditional expression is applicable only to filesystem objects. It's confusing
```diff
diff --git a/cmake/public/utils.cmake b/cmake/public/utils.cmake
index 15f5afd319..75a4fdebde 100644
--- a/cmake/public/utils.cmake
+++ b/cmake/public/utils.cmake
@@ -361,7 +361,7 @@ endmacro()
 #
 macro(torch_cuda_get_nvcc_gencode_flag store_var)
   # setting nvcc arch flags
-  if((NOT EXISTS ${TORCH_CUDA_ARCH_LIST}) AND (DEFINED ENV{TORCH_CUDA_ARCH_LIST}))
+  if((NOT DEFINED TORCH_CUDA_ARCH_LIST) AND (DEFINED ENV{TORCH_CUDA_ARCH_LIST}))
     message(WARNING
         "In the future we will require one to explicitly pass "
         "TORCH_CUDA_ARCH_LIST to cmake instead of implicitly setting it as an "
```
Please state the proper way to specify CUDA archs in the future.

[code]: https://github.com/pytorch/pytorch/blob/master/cmake/public/utils.cmake#L364-L371
[ref]: https://cmake.org/cmake/help/latest/command/if.html#exists

cc @malfet @seemethere
Repository: pytorch
Issue: [FX] `concrete_args` with unpacking breaks `fx.Interpreter`
Labels: triaged,Stale,module: fx

```
import torch
import torch.fx
from typing import List

class MyMod(torch.nn.Module):
  def forward(self, x : List[torch.Tensor]):
    return torch.cat(x)

traced = torch.fx.symbolic_trace(MyMod(), concrete_args=([torch.fx.PH, torch.fx.PH],))

interp = torch.fx.Interpreter(traced)

interp.run([(torch.randn(5, 3), torch.randn(5, 3))])
"""
---------------------------------------------------------------------------
StopIteration                             Traceback (most recent call last)
<ipython-input-5-af2fe140814d> in <module>()
      1 interp = torch.fx.Interpreter(traced)
      2 
----> 3 interp.run([(torch.randn(5, 3), torch.randn(5, 3))])
"""
```

`fx.Interpreter` doesn't know about the unpacking routine it needs to call when running a `Module` with such concrete_arg unpacking. We should fix this

cc @ezyang