sharjeelyunus/github-issues-dataset huggingface dataset:
Repository: ant-design
Issue: darkAlgorithm color palette does not include primary color
Labels: 💄 Design,Inactive

### Reproduction link

[https://ant.design/docs/spec/dark#color-palette-generator](https://ant.design/docs/spec/dark#color-palette-generator)

### Steps to reproduce

1. Enter the primary color of the app (e.g. #B3F14F)
2. The primary color is not included as any of the colors and the primary color used, color-6, is a different color (e.g. #9bd046)

<img width="529" alt="CleanShot 2023-08-03 at 09 27 51@2x" src="https://github.com/ant-design/ant-design/assets/99197390/9e6c0d96-2763-4371-9d10-adb4db5b3643">


### What is expected?

That the primary color I select will be the primary color used in the theme

### What is actually happening?

The darkAlgorithm alters all of the colors so that the primary color being used is a slightly different color from my brand color. For example, my brand color is #B3F14F. If I customize ConfigProvider like so:

```
<ConfigProvider
      theme={{
        algorithm: theme.darkAlgorithm,

        token: {
          colorPrimary: '#B3F14F',
          colorTextBase: '#eaeaea',
          colorBgBase: '#000',
          colorText: '#FFF',
          colorTextSecondary: '#1A1A1A',
          fontFamily: brandedFont.style.fontFamily,
          fontSize: 16,
        }
    >
```

The primary color being used throughout my app is #9bd046 which is not the color of my brand. I can't find the algorithm anywhere so I can't reverse engineer to figure out what color will give me my brand color.

If I try to add the primary color to each component within the configProvider, it works with some (e.g. button), but not all (e.g. badge, tag). 

| Environment | Info |
| --- | --- |
| antd | 5.8.1 |
| React | 18.2 |
| System | mac |
| Browser | chrome/brave/safari |

<!-- generated by ant-design-issue-helper. DO NOT REMOVE -->
Repository: electron
Issue: [Feature Request]: MacOS: Allow systemPreferences.subscribeNotification to specify the suspensionBehaviour
Labels: enhancement :sparkles:,platform/macOS,component/system-preferences

### Preflight Checklist

- [X] I have read the [Contributing Guidelines](https://github.com/electron/electron/blob/main/CONTRIBUTING.md) for this project.
- [X] I agree to follow the [Code of Conduct](https://github.com/electron/electron/blob/main/CODE_OF_CONDUCT.md) that this project adheres to.
- [X] I have searched the [issue tracker](https://www.github.com/electron/electron/issues) for a feature request that matches the one I want to file, without success.

### Problem Description

When an MacOS electron app registers for a Distributed Notification using [systemPreferences.subscribeNotification](https://www.electronjs.org/docs/latest/api/system-preferences#systempreferencessubscribenotificationevent-callback-macos), the default mode of [NSNotificationSuspensionBehaviorCoalesce](https://developer.apple.com/documentation/foundation/nsnotificationsuspensionbehavior/nsnotificationsuspensionbehaviorcoalesce) is used.
This means that the electron app will not receive the notification if it is suspended (ie., not currently focussed.)
Electron code: [electron_api_system_preferences.mm](https://github.com/electron/electron/blob/e6931a788fad3d3315d3911c1997f3cd98fa34d0/shell/browser/api/electron_api_system_preferences_mac.mm#L223)

It _is_ possible to send an event using the [DistributedNotificationCenter using a `deliverImmediately` flag](https://developer.apple.com/documentation/foundation/nsdistributednotificationcenter/1418360-postnotificationname) which will cause the electron app to immediately receive the notification. However, it is not always possible to set this flag (for example, when the notification is coming from an application that is not under our control).

### Proposed Solution

Ideally, the `systemPreferences.subscribeNotification` method would support a `suspensionBehaviour` parameter, allowing the caller to [specify the desired mode](https://developer.apple.com/documentation/foundation/nsnotificationsuspensionbehavior).

This would allow the electron app to wake up and process the notification immediately by specifying 'NSNotificationSuspensionBehaviorDeliverImmediately` for the suspensionBehaviour.


### Alternatives Considered

One alternative would be to change the existing code to always specify the suspensionBehaviour as DeliverImmediately:
```
  g_id_map[request_id] = [GetNotificationCenter(kind)
      addObserverForName:name
                  object:nil
                   queue:nil
+                 suspensionBehaviour: NSNotificationSuspensionBehaviorDeliverImmediately
```
An issue with this approach is that the other notification centers (local, workspace) do not appear to support this parameter.

Another alternative might be to add a separate method to set the default suspensionBehaviour, but that seems like more work.

### Additional Information

_No response_
Repository: flutter
Issue: [google_maps_flutter] Add basic native unit tests for creation
Labels: a: tests,platform-android,platform-ios,p: maps,package,team-ecosystem,P2,c: tech-debt,triaged-ecosystem

In https://github.com/flutter/packages/pull/4638 we should have been able to easily test that we were passing the map ID through to the underlying SDK in native unit tests, but we don't have any setup for that (e.g., a DI wrapper for the SDK's maps factory).

We should backfill that support in the plugin, and test the existing passthroughs that are currently untested.
Repository: flutter
Issue: [packages] Add a convience script to run all fast checks
Labels: team,package,team-ecosystem,P2,triaged-ecosystem

We have a bunch of checks that are very fast to run (changelog/version, readme, excerpts, etc.—most of `repo_checks`) but it's tedious to run each of them locally. We should make a convenience script in `script/` that runs all of them (by default using diffs against the branch point from `main`) so it's easy to do them as a quick pre-upload check.
Repository: material-ui
Issue: [examples] Updated remix example
Labels: external dependency,examples

### Duplicates

- [X] I have searched the existing issues

### Related page

https://github.com/mui/material-ui/tree/6cd17b871437af9a5fee58916fe4a53b77f647d4/examples/material-remix-ts

### Kind of issue

Other

### Issue description

I was looking for a remix example repo and it appears that the example is out of date.

E.g. it doesn't use `renderToPipeableStream`, which is required for [remix streaming](https://remix.run/docs/en/main/guides/streaming)


### Context 🔦

I want to use react 18. I'd like to use streaming, as well as new features from other libraries I use (e.g. [ably react hooks](https://github.com/ably-labs/react-hooks)), but they depend on react 18.

It's awesome that you have a remix example repo, and that has worked great for me up until now. I've tried to bring it up-to-date to use `renderToPipeableStream` but I'm struggling. It would be great if someone had worked on a MUI react 18 app and had an example repo.
Repository: stable-diffusion-webui
Issue: [Feature Request]: display `dir` , `ss_output_name`
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 ?

![image](https://github.com/AUTOMATIC1111/stable-diffusion-webui/assets/167966/6e57849a-9440-4e11-83f6-a92a37ae306c)



### Proposed workflow

1. Go to .... 
2. Press ....
3. ...


### Additional information

_No response_
Repository: transformers
Issue: MassFormer
Labels: New model

### Model description

We propose adding a new model, MassFormer, to predict tandem mass spectra accurately. MassFormer uses a graph transformer architecture to model long-distance relationships between atoms in the molecule. The transformer module is initialized with parameters obtained through a chemical pre-training task, then fine-tuned on spectral data. MassFormer outperforms competing approaches for spectrum prediction on multiple datasets and is able to recover prior knowledge about the effect of collision energy on the spectrum. We demonstrate that the model can identify relationships between fragment peaks by employing gradient-based attribution methods. To further highlight MassFormer’s utility, we show that it can match or exceed existing prediction-based methods on two spectrum identification tasks. Our code is the first open-source implementation of a deep-learning MS/MS spectrum predictor and may encourage future research in this area.

### Open source status

- [X] The model implementation is available
- [X] The model weights are available

### Provide useful links for the implementation

This model will be implemented according to the paper by @adamoyoung as listed below.

Reference:
Young, A., Wang, B. and Röst, H., 2021. MassFormer: Tandem mass spectrum prediction with graph transformers. arXiv preprint arXiv:2111.04824.
Repository: transformers
Issue: BertForSequenceClassification does not support 'device_map':"auto" yet
Labels: Good Second Issue

### System Info

I have trained a model and am now trying to load and quantise it but getting the error: 

BertForSequenceClassification does not support 'device_map':"auto" yet

Code for loading is simply:
   ` model = AutoModelForSequenceClassification.from_pretrained(model_dir, device_map='auto', load_in_8bit=True)`

Help would be greatly appreciated!

Thanks,

Lee

### Who can help?

_No response_

### Information

- [X] The official example scripts
- [ ] My own modified scripts

### Tasks

- [X] An officially supported task in the `examples` folder (such as GLUE/SQuAD, ...)
- [ ] My own task or dataset (give details below)

### Reproduction

model = AutoModelForSequenceClassification.from_pretrained(model_dir, device_map='auto', load_in_8bit=True)

### Expected behavior

The model would load and be usable.
Repository: pytorch
Issue: DISABLED test_cpp_wrapper_cpu (__main__.FreezingCpuTests)
Labels: triaged,skipped,oncall: pt2

Platforms: macos

This test was disabled because it is failing on master ([recent examples](http://torch-ci.com/failure/inductor%2Ftest_inductor_freezing.py%3A%3AFreezingCpuTests%3A%3Atest_cpp_wrapper_cpu)).

cc @ezyang @gchanan @zou3519 @kadeng @msaroufim @bdhirsh @anijain2305 @chauhang @wconstab @albanD
Repository: godot
Issue: Capitalization of the default name of the root node of the scene tree is inconsistent with the GDScript style guide.
Labels: discussion,topic:core

### Godot version

4.2.dev2

### System information

Windows 10.0.19045 - GLES3 (Compatibility)

### Issue description

Accessing the `get_tree().root.name` property shows that it is `root` - starting with a lowercase letter.
This is inconsistent with the [Naming conventions - Classes and nodes](https://docs.godotengine.org/en/latest/tutorials/scripting/gdscript/gdscript_styleguide.html#classes-and-nodes) section in the GDScript style guide that recommends using PascalCase for node names.
To be consistent with the guide the root node should be named `Root`.


### Steps to reproduce

Run the script:
```gdscript
print(get_tree().root.name)
```

### Minimal reproduction project

N/A
Repository: TypeScript
Issue: Unwanted auto-imports in script files
Labels: Suggestion,Help Wanted,Effort: Moderate,Experience Enhancement

# Bug Report

I have a mixture of module and non-module code.
The problem occurs when I edit non-module files (tsconfig: `"module": "none"`).

Sometimes when using auto-completion (in VisualStudio 2022) typescript finds a "matching" name from the module world and adds a line like
```ts
import { HmiHelper } from './helper/HmiHelper.js';
```
into the first line of my file. 
But as the current file was configured as `"module": "none"` this `import` pushes typescript into modules mode and the current code is invalid.

### 🔎 Search Terms

intellisense
auto-import
modules

### 🕗 Version & Regression Information

This bug is many years old and persists in Typescript 5.1.
Repository: pytorch
Issue: NotImplementedError: Could not run 'aten::multinomial' with arguments from the 'Meta' backend.
Labels: triaged,module: random

### 🐛 Describe the bug

The error says:
NotImplementedError: Could not run 'aten::multinomial' with arguments from the 'Meta' backend. This could be because the operator doesn't exist for thi
s backend, or was omitted during the selective/custom build process (if using custom build). If you are a Facebook employee using PyTorch on mobile, pl
ease visit https://fburl.com/ptmfixes for possible resolutions. 'aten::multinomial' is only available for these backends: [CPU, CUDA, BackendSelect, Py
thon, FuncTorchDynamicLayerBackMode, Functionalize, Named, Conjugate, Negative, ZeroTensor, ADInplaceOrView, AutogradOther, AutogradCPU, AutogradCUDA, 
AutogradHIP, AutogradXLA, AutogradMPS, AutogradIPU, AutogradXPU, AutogradHPU, AutogradVE, AutogradLazy, AutogradMeta, AutogradMTIA, AutogradPrivateUse1
, AutogradPrivateUse2, AutogradPrivateUse3, AutogradNestedTensor, Tracer, AutocastCPU, AutocastCUDA, FuncTorchBatched, FuncTorchVmapMode, Batched, Vmap
Mode, FuncTorchGradWrapper, PythonTLSSnapshot, FuncTorchDynamicLayerFrontMode, PythonDispatcher].


Code:
def sample_top_p(probs, p):
    probs_sort, probs_idx = torch.sort(probs, dim=-1, descending=True)
    probs_sum = torch.cumsum(probs_sort, dim=-1)
    mask = probs_sum - probs_sort > p
    probs_sort[mask] = 0.0
    probs_sort.div_(probs_sort.sum(dim=-1, keepdim=True))
    next_token = torch.multinomial(probs_sort, num_samples=1)
    next_token = torch.gather(probs_idx, -1, next_token)
    return next_token

### Versions

StatusCode        : 200
StatusDescription : OK
Content           :
                    # Unlike the rest of the PyTorch this file must be python2 compliant.
                    # This script outputs relevant system environment info
                    # Run it with `python collect_env.py`.
                    import datetime
                    import locale
                    impor...
RawContent        : HTTP/1.1 200 OK
                    Connection: keep-alive
                    Content-Security-Policy: default-src 'none'; style-src 'unsafe-inline'; sandbox
                    Strict-Transport-Security: max-age=31536000
                    X-Content-Type-Options: nosniff
                    ...
Forms             : {}
Headers           : {[Connection, keep-alive], [Content-Security-Policy, default-src 'none'; style-src 'unsafe-inline'; sandbox],
                    [Strict-Transport-Security, max-age=31536000], [X-Content-Type-Options, nosniff]...}
Images            : {}
InputFields       : {}
Links             : {}
ParsedHtml        : mshtml.HTMLDocumentClass
RawContentLength  : 21653


cc @pbelevich
Repository: flutter
Issue: Occasionally Autosubmit will not merge an issue with no clear reason in the logs
Labels: team-infra,P2,c: tech-debt,triaged-infra

There were two issues recent that were open for days and it took Autosubmit over an hour to merge a green PR with no tree status issues.

https://github.com/flutter/packages/pull/4573
https://github.com/flutter/packages/pull/4432

I took a look to try and identify why but there was no issue present. The logging we do was not sufficient enough to identify any one issue with why the pull requests were not merged in time.
Repository: next.js
Issue: Updating search params does not trigger suspense fallback or loading.tsx
Labels: Navigation

### Verify canary release

- [X] I verified that the issue exists in the latest Next.js canary release

### Provide environment information

```bash
Operating System:
      Platform: linux
      Arch: x64
      Version: #22 SMP Tue Jan 10 18:39:00 UTC 2023
    Binaries:
      Node: 18.14.2
      npm: 9.5.0
      Yarn: 1.22.19
      pnpm: N/A
    Relevant Packages:
      next: 13.4.12
      eslint-config-next: 13.4.12
      react: 18.2.0
      react-dom: 18.2.0
      typescript: 5.0.4
    Next.js Config:
      output: N/A
```


### Which area(s) of Next.js are affected? (leave empty if unsure)

App Router, Routing (next/router, next/navigation, next/link)

### Link to the code that reproduces this issue or a replay of the bug

https://codesandbox.io/p/sandbox/muddy-glade-hn895s

### To Reproduce

1. Create a component which uses search parameters in fetching data
2. Use a link to change the query param and load new data based on the search param
3. Observe that loading.tsx fallback does not invoke and the page hangs while new data is loaded

### Describe the Bug

Updating search params does not trigger suspense fallback or loading.tsx

### Expected Behavior

Fetching new data based on new search params trigger suspense fallbacks or loading.tsx

### Which browser are you using? (if relevant)

_No response_

### How are you deploying your application? (if relevant)

_No response_
Repository: flutter
Issue: Stack trace should not be partially parsed.
Labels: framework,P2,team-framework,triaged-framework
Repository: rust
Issue: Tweak output of E0599 to make it less verbose
Labels: A-diagnostics,T-compiler,D-papercut,D-verbose

### Code

```Rust
struct Foo;
trait Bar {}
trait Baz {}
trait Bat { fn bat(&self); }
impl<T> Bat for T where T: 'static + Bar + Baz { fn bat(&self) { println!("generic bat"); } }

pub fn main() {
    Foo::bat(());
}
```


### Current output

```Shell
error[E0599]: the function or associated item `bat` exists for struct `Foo`, but its trait bounds were not satisfied
 --> src/main.rs:8:10
  |
1 | struct Foo;
  | ----------
  | |
  | function or associated item `bat` not found for this struct
  | doesn't satisfy `Foo: Bar`
  | doesn't satisfy `Foo: Bat`
  | doesn't satisfy `Foo: Baz`
...
8 |     Foo::bat(());
  |          ^^^ function or associated item cannot be called on `Foo` due to unsatisfied trait bounds
  |
note: the following trait bounds were not satisfied:
      `&Foo: Bar`
      `&Foo: Baz`
      `&mut Foo: Bar`
      `&mut Foo: Baz`
      `Foo: Bar`
      `Foo: Baz`
 --> src/main.rs:5:38
  |
5 | impl<T> Bat for T where T: 'static + Bar + Baz { fn bat(&self) { println!("generic bat"); } }
  |         ---     -                    ^^^   ^^^ unsatisfied trait bound introduced here
  |                                      |
  |                                      unsatisfied trait bound introduced here
note: the traits `Bar` and `Baz` must be implemented
 --> src/main.rs:2:1
  |
2 | trait Bar {}
  | ^^^^^^^^^
3 | trait Baz {}
  | ^^^^^^^^^
```


### Desired output

```Shell
error[E0599]: the function or associated item `bat` exists for struct `Foo`, but its trait bounds were not satisfied
 --> src/main.rs:8:10
  |
1 | struct Foo;
  | ----------
  | |
  | function or associated item `bat` not found for this struct
  | `Foo` doesn't implement `Bar`, `Bat` or `Baz`
...
8 |     Foo::bat(());
  |          ^^^ function or associated item cannot be called on `Foo` due to unsatisfied trait bounds
  |
note: for `bat` to be available, `Foo` must implement `Bar` and `Baz`
 --> src/main.rs:5:38
  |
5 | impl<T> Bat for T where T: 'static + Bar + Baz { fn bat(&self) { println!("generic bat"); } }
  |         ---     -                    ^^^   ^^^ unsatisfied trait bound introduced here
  |                                      |
  |                                      unsatisfied trait bound introduced here
note: the traits `Bar` and `Baz` must be implemented
 --> src/main.rs:2:1
  |
2 | trait Bar {}
  | ^^^^^^^^^
3 | trait Baz {}
  | ^^^^^^^^^
```


### Rationale and extra context

_No response_

### Other cases

_No response_

### Anything else?

_No response_
Repository: pytorch
Issue: DTensor Sharding prop cache stats
Labels: oncall: distributed,triaged,module: dtensor

### 🚀 The feature, motivation and pitch

We have built `_CachingPropagator` and we need some stats to monitor cache miss rate so that we can understand potential perf regression in DTensor CPU overhead.

### Alternatives

_No response_

### Additional context

_No response_

cc @mrshenli @pritamdamania87 @zhaojuanmao @satgera @rohan-varma @gqchen @aazzolini @osalpekar @jiayisuse @H-Huang @kwen2501 @awgu @penguinwu
Repository: storybook
Issue: [Bug]: Loading external js script in svelte story
Labels: bug,svelte,needs triage

### Describe the bug

Hey team

Awesome library - thanks for all of your hard work!

I am running into an issue where I cannot load an external js script in my Svelte stories. I have followed the guidelines that show how to incorporate an external js script [here](https://storybook.js.org/docs/react/configure/story-rendering) and I can see this script included in the body of the iframe. However regardless of what I try, the Dropdown component in the Codesandbox (and my local machine) only works in Sveltekit but not in the story.

Note that I am using a combination of Skeleton UI and Flowbite (the standard library, not the dedicated Svelte library as this conflicts with Skeleton UI) as css styling libraries, which are both TailwindCSS based.

I tried to specifically include the flowbite js script (Flowbite cdn docs [here](https://flowbite.com/docs/getting-started/quickstart/#include-via-cdn)) in svelte using the `<svelte:head>` tag but this didn't work. I have tried to wrap the component within the story in my Svelte layout in hopes the js would "filter down" as it does when running Svelte on its own, but this didn't work either.

I understand (the theory, not necessarily the details) that svelte does SSR as much as possible, so maybe it has something to do with this?

### To Reproduce

I created a Codesandbox [here](https://codesandbox.io/p/sandbox/blue-shape-4yk7kp) - I think Sveltekit should open automatically to show a basic Dropdown, which works. However when you run storybook and look at the Dropdown story, nothing happens.

This has all of the same setup I am using, including the `preview-body.html` that I can see referenced within the iframe. 

### System

```shell
my local system below, but same issue occurs on Linux vm in codesandbox  

System:
    OS: macOS 13.4.1
    CPU: (8) arm64 Apple M1
  Binaries:
    Node: 19.8.1 - /opt/homebrew/bin/node
    Yarn: 1.22.19 - /opt/homebrew/bin/yarn
    npm: 9.5.1 - /opt/homebrew/bin/npm
  Browsers:
    Chrome: 115.0.5790.114
    Edge: 114.0.1823.51
    Safari: 16.5.2
  npmPackages:
    @storybook/addon-essentials: ^7.2.1 => 7.2.1
    @storybook/addon-interactions: ^7.2.1 => 7.2.1
    @storybook/addon-links: ^7.2.1 => 7.2.1
    @storybook/addon-styling: ^1.3.5 => 1.3.5
    @storybook/addon-svelte-csf: 3.0.7 => 3.0.7
    @storybook/addon-viewport: ^7.2.1 => 7.2.1
    @storybook/blocks: ^7.2.1 => 7.2.1
    @storybook/svelte: ^7.2.1 => 7.2.1
    @storybook/sveltekit: ^7.2.1 => 7.2.1
    @storybook/testing-library: ^0.2.0 => 0.2.0
```


### Additional context

Thanks for taking the time to read :)
Repository: transformers
Issue: Add zero-shot classification task for BLIP-2
Labels: Good Second Issue

### Feature request

I would like to add the support for the zero-shot classification task using BLIP2, computing text-image similarities with the normalized embeddings, that would be accessed from BLIP2 feature extractor. 

The idea is to enable calling the zero-shot classification pipeline using BLIP2, by implementing the `get_image_feature`and `get_text_features`methods.

I would love more guidance, if possible, on the criteria for accepting the PR.



### Motivation

This is related to the following the discussion on this issue on the hub, and the comment left by @NielsRogge here https://huggingface.co/Salesforce/blip2-opt-2.7b/discussions/3#64cbe5e487ec96aa473a1f54 .

### Your contribution

I would like to submit a PR to contribute for this feature.