sharjeelyunus/github-issues-dataset huggingface dataset:
Repository: deno
Issue: Error: Not implemented: cluster.fork
Labels: node compat,node:cluster

Version: Deno v2.1.4

Attempting to use the node:cluster module to cluster.fork() throws an error
`Error: Not implemented: cluster.fork`

Code to duplicate:

```ts
import cluster from 'node:cluster';
import http from 'node:http';
import { availableParallelism } from 'node:os';
import process from 'node:process';

const numCPUs = availableParallelism();

if (cluster.isPrimary) {
  console.log(`Primary ${process.pid} is running`);

  // Fork workers.
  for (let i = 0; i < numCPUs; i++) {
    cluster.fork();
    console.log('fork cpu:', i);
  }
} else {
  // Workers can share any TCP connection
  // In this case it is an HTTP server
  http.createServer((req, res) => {
    res.writeHead(200);
    res.end('hello world\n');
  }).listen(8000);

  console.log(`Worker ${process.pid} started`);
}
```
Repository: transformers
Issue:  Compatibility Issue with Python 3.13
Labels: dependencies,bug

### System Info

Python 3.13

### Who can help?

_No response_

### Information

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

### Tasks

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

### Reproduction

pip install transformers

### Expected behavior

Issue: Compatibility Issue with Python 3.13
Description:
When attempting to install safetensors as a dependency for transformers on Python 3.13, the installation fails during the metadata generation step. The issue seems to be related to the maturin build tool and its handling of the pyproject.toml. This problem does not occur on Python 3.12.

Steps to Reproduce:

Install Python 3.13.1 (official build).
Run the command:
bash
复制代码
pip install safetensors
Observe the following error:
plaintext
复制代码
error: subprocess-exited-with-error
× Preparing metadata (pyproject.toml) did not run successfully.
│ exit code: 1
╰─> [5 lines of output]
    💥 maturin failed
      Caused by: `project.version` field is required in pyproject.toml unless it is present in the `project.dynamic` list
    Error running maturin: Command '['maturin', 'pep517', 'write-dist-info', '--metadata-directory', ...]' returned non-zero exit status 1.
Environment:

Python Version: 3.13.1
OS: Windows 10 (64-bit)
Pip Version: 23.x
Rust Version: [Provide output of rustc --version]
Temporary Solution:
Switching to Python 3.12 resolves the issue. Dependencies (safetensors and transformers) install successfully on Python 3.12.

Expected Behavior:
The package should install successfully on Python 3.13.

Additional Context:
This issue might be due to the pyproject.toml configuration or an incompatibility in the maturin build tool when used with Python 3.13.

Suggestions:

Investigate the pyproject.toml for compatibility with Python 3.13.
Ensure dependencies like maturin and Rust are compatible with the latest Python version.
Repository: transformers
Issue: Allow static cache to be larger than sequence length / batch size for encoder-decoder models
Labels: Feature request

### Feature request

In encoder decoder models using an encoder-decoder cache object when using a static cache:
1. the cross-attention cache size must equal the encoder sequence length.
2. batch size for both self-attention and cross-attention caches must be the same as the generating batch size.

### Motivation

I have been working on executorch export for encoder-decoder models. as part of that I have been digging into the implementation of the encoder-decoder cache and static cache. 

How I would expect static caches to work is that when you initialize the cache, then as long as your generation (batch size, encoder sequence length, decoder sequence length) is less than the associated cache values, it should work.

Currently however:
1. The cross attention cache must be exactly the size as the encoder sequence length.
2. The batch size that the cache is initialized with must be exactly the batch size that the cache is run with.


### Your contribution

As I was digging through this, I updated the T5 attention and the static cache implementation in an attempt to handle both these cases.

#35445 

That being said, I am just starting to learn transformers (both the hf library and in general), and have no real idea what I am doing.

#### Here is the code I have been using to generate the issue:

```python
import torch
from transformers import (
    AutoTokenizer,
    AutoModelForSeq2SeqLM,
)
from transformers.cache_utils import (
    StaticCache,
    EncoderDecoderCache,
)

model_name = "google-t5/t5-small"

dtype = torch.float16

tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForSeq2SeqLM.from_pretrained(
    model_name,
    torch_dtype=dtype,
)


encoder_cache = StaticCache(
    model.config, max_cache_len=170, max_batch_size=4, dtype=dtype
)
decoder_cache = StaticCache(
    model.config, max_cache_len=200, max_batch_size=4, dtype=dtype
)
cache = EncoderDecoderCache(decoder_cache, encoder_cache)

strings_1 = [
    "When the night has come and the land is dark, and the moon is the only light we will see.",
    "Abba is the best",
    # "No lindy is the best",
    # "No Elton john is the absolute best.",
]
input_ids = tokenizer(strings_1, return_tensors="pt", padding=True)
tokens = model.generate(**input_ids, past_key_values=cache)
text_translated = [tokenizer.decode(t, skip_special_tokens=False) for t in tokens]
print(text_translated)
```
Repository: vscode
Issue: "Unable to resolve resource vscode" codespaces firefox - #169930
Labels: *duplicate

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- VS Code Version: 
- OS Version: 

Steps to Reproduce:

1. be on firefox in strict modde
2. try to open codespaces on browser


i had the exact same error as https://github.com/microsoft/vscode/issues/169930

![Image](https://github.com/user-attachments/assets/2cc9563e-10c2-4cfb-8978-1a62c8d131c8)

I changed the seeting on firefox from strict to normal and solved the bug

just posting here for the case of someone struggling with  it  and needing help, was two weeks trying to solve it

![Image](https://github.com/user-attachments/assets/f277ba00-9842-4b03-94f4-c2b4bc05b2a6)


![Image](https://github.com/user-attachments/assets/58fd2845-465e-465b-b1c3-9581ed3890e2)


![Image](https://github.com/user-attachments/assets/351afa1d-eacb-4a1e-9530-908c1d2fbeb7)
Repository: transformers
Issue: `tokenizer` should be replaced to `processing_class` in `Seq2SeqTrainer`?
Labels: Core: Tokenization,trainer,bug

### System Info

- `transformers` version: 4.47.1
- Platform: Linux-5.4.0-200-generic-x86_64-with-glibc2.31
- Python version: 3.10.16
- Huggingface_hub version: 0.27.0
- Safetensors version: 0.4.5
- Accelerate version: 1.2.1
- Accelerate config:    not found
- PyTorch version (GPU?): 2.5.1+cu124 (True)
- Tensorflow version (GPU?): not installed (NA)
- Flax version (CPU?/GPU?/TPU?): not installed (NA)
- Jax version: not installed
- JaxLib version: not installed
- Using distributed or parallel set-up in script?: <fill in>
- Using GPU in script?: <fill in>
- GPU type: NVIDIA GeForce RTX 2070 SUPER

### Who can help?

@amyeroberts @ArthurZucker 

### Information

- [ ] The official example scripts
- [X] My own modified scripts

### Tasks

- [ ] An officially supported task in the `examples` folder (such as GLUE/SQuAD, ...)
- [X] My own task or dataset (give details below)

### Reproduction

In [`trainer_seq2seq.py`](https://github.com/huggingface/transformers/blob/5c75087aeee7081025370e10d1f571a11600f1ae/src/transformers/trainer_seq2seq.py#L372) file, there is still calling `self.tokenizer.` which produces deprecation warning "Trainer.tokenizer is now deprecated. You should use Trainer.processing_class instead."

```python
def _pad_tensors_to_max_len(self, tensor, max_length):
    if self.tokenizer is not None and hasattr(self.tokenizer, "pad_token_id"):
        # If PAD token is not defined at least EOS token has to be defined
        pad_token_id = (
            self.tokenizer.pad_token_id if self.tokenizer.pad_token_id is not None else self.tokenizer.eos_token_id
        )
```

### Expected behavior

I believe self.tokenizer should be replaced to self.processing_class

```python
def _pad_tensors_to_max_len(self, tensor, max_length):
    if self.processing_class is not None and hasattr(self.processing_class, "pad_token_id"):
        # If PAD token is not defined at least EOS token has to be defined
        pad_token_id = (
            self.processing_class.pad_token_id if self.processing_class.pad_token_id is not None else self.processing_class.eos_token_id
        )
```

Is it okay for me to make a PR for this issue? :smile:
Repository: godot
Issue: Auto Converting C# 3.x project to 4.3 is replacing wrong function spellings.
Labels: bug,topic:editor,topic:dotnet

### Tested versions

- Godot 3.6
- Godot 4.3

### System information

Windows 11

### Issue description

I searched through the issues and couldn't find this.

I just let 4.3 convert a C# 3.6 project.  Lots of unnecessary errors because it is replacing functions with incorrect spelled ones.:

**Particles2D** converted to GPUParticles2D (should be GpuParticles2D)
**[Remote]** converted to [RPC(MultiplayerAPI.RPCMode.AnyPeer)] (should be [Rpc(MultiplayerApi.RpcMode.AnyPeer)])
**JSON** (should be Json)

I have over 1600+ errors so I haven't found all the misspellings, but these are the ones I found. The names were probably capitalized and one point in 4.x and changed but never updated in the converter.  Even in the documentation they are wrongly spelled. 



### Steps to reproduce

Create a C# project in 3.6 and include Particles2D, [Remote], and Godot.JSON. 
Now open it in 4.3 and let it convert the project.

### Minimal reproduction project (MRP)

[Test.zip](https://github.com/user-attachments/files/18268396/Test.zip)
Repository: rust
Issue: Pin::new_unchecked docs need to warn about Ptr: Drop too
Labels: T-libs-api,A-docs,A-pin

### Location

https://doc.rust-lang.org/std/pin/struct.Pin.html#method.new_unchecked

### Summary

The `pin` [module-level doc](https://doc.rust-lang.org/std/pin/index.html#projections-and-structural-pinning) says

> It should further be noted that creating a pinning pointer of some type `Ptr` *also* carries with it implications on the way that `Ptr` type must implement `Drop` (as well as `Deref` and `DerefMut`)! When implementing a pointer type that may be used as a pinning pointer, you must also take the same care described above not to *move* out of or otherwise invalidate the pointee during `Drop`, `Deref`, or `DerefMut` implementations.

However, the [doc for `Pin::new_unchecked`](https://doc.rust-lang.org/std/pin/struct.Pin.html#method.new_unchecked) says

> By using this method, you are also making a promise about the `Deref` and `DerefMut` implementations of `Ptr`, if they exist. Most importantly, they must not move out of their `self` arguments: [...]

If I understand correctly (which I may well not, given the subject matter...), these two sections are talking about the same thing: there are some _safe_ traits that you implement by writing a method that takes a bare `&mut self`, and when those traits are implemented for the `Ptr` type in a `Pin<Ptr<T>>`, unless `T: Unpin`, you really need to treat that `&mut self` as if it were pinned (maybe by stuffing it inside a `Pin` ASAP), or you are in danger of breaking invariants that unsafe code is allowed to assume. And because this is a safety requirement, there's got to be an `unsafe` somewhere stating that you believe those safe traits are implemented appropriately, and that place is, I think, the invocation of `Pin::new_unchecked` for a specific choice of `Ptr` type.

But the doc for `Pin::new_unchecked` only mentions `Deref` and `DerefMut` as part of the safety contract of invoking it. If these sections are talking about the same thing, then properly implementing `Drop` is also part of the safety burden and the doc should mention it.
Repository: svelte
Issue: Allow to set custom types from data-attributes
Labels: types / typescript

### Describe the problem

I would like to restrict the values allowed in a data-attribute similarly to what is already possible with completely non-standard attributes using the `svelteHTML` namespace.

Today svelte will accept any value in any data-attribute and there seems to be no way to restrict it, even overriding the svelte's internal .d.ts (like `non-ambient.d.ts` and `elements.d.ts`) files seems to not have any effect.

### Describe the proposed solution

Allow this:

```ts
// See https://kit.svelte.dev/docs/types#app
// for information about these interfaces
declare global {
	namespace App {
		// interface Error {}
		// interface Locals {}
		// interface PageData {}
		// interface PageState {}
		// interface Platform {}
	}

	namespace svelteHTML {
		// enhance elements
		interface IntrinsicElements {
			// 'my-custom-element': { someattribute: string; 'on:event': (e: CustomEvent<any>) => void };
		}
		// enhance attributes
		interface HTMLAttributes<T> {
			// If you want to use the beforeinstallprompt event
			// onbeforeinstallprompt?: (event: any) => any;
			// If you want to use myCustomAttribute={..} (note: all lowercase)
			// mycustomattribute?: any; // You can replace any with something more specific if you like

			'data-hello'?: 'hello';
		}
	}
}

export {};
```

### Importance

nice to have
Repository: pytorch
Issue: Issue with aten::_sparse_coo_tensor_with_dims_and_tensors on Apple Silicon GPU (MPS) Backend when Using Whisper Model
Labels: module: sparse,feature,triaged,module: mps

### 🐛 Describe the bug

## Description

Error occurs while running Whisper model on MPS. The operation `aten::_sparse_coo_tensor_with_dims_and_tensors` fails to fallback to CPU with `PYTORCH_ENABLE_MPS_FALLBACK=1`.

### Minimal Code to Reproduce the Issue

```python
import whisper

device = "mps" if torch.backends.mps.is_available() else "cpu"
model = whisper.load_model("large-v3", device=device)
result = model.transcribe("/path/to/audio/file.m4a")
```

### Versions

## Description

Error occurs while running Whisper model on MPS. The operation `aten::_sparse_coo_tensor_with_dims_and_tensors` fails to fallback to CPU with `PYTORCH_ENABLE_MPS_FALLBACK=1`.

### Minimal Code to Reproduce the Issue

```python
import whisper

device = "mps" if torch.backends.mps.is_available() else "cpu"
model = whisper.load_model("large-v3", device=device)
result = model.transcribe("/path/to/audio/file.m4a")
```

cc @alexsamardzic @nikitaved @pearu @cpuhrsch @amjames @bhosmer @jcaip @kulinseth @albanD @malfet @DenisVieriu97 @jhavukainen
Repository: vscode
Issue: `--enable-wayland-ime` is not supported in `~/.vscode/argv.json`
Labels: feature-request

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<!-- Describe the feature you'd like. -->
`--enable-wayland-ime` is a command line option that can be used with VSCode, and is sometimes necessary when using a language that requires an IME, such as Japanese, Chinese or Korean, in a VSCode environment running on Wayland.

VSCode also has a feature that treats the contents of `~/.vscode/argv.json` as the default command line arguments. Unfortunately, `--enable-wayland-ime` is currently not supported in `~/.vscode/argv.json`.

This issue is to request that `--enable-wayland-ime` be supported in `argv.json`.
There are many other known workarounds for adding default command line arguments (e.g. write alias on my .zshrc), but using `argv.json` is a simple and good approach.
Repository: godot
Issue: Warnings when combining enums inside function parameter field of type Control.FlagSizes
Labels: discussion,topic:gdscript

### Tested versions

v4.3.stable.custom_build [77dcf97d8]
v4.3.stable.mono.official [77dcf97d8]

### System information

Godot v4.3.stable (77dcf97d8) - Windows 10.0.19045 - Vulkan (Mobile) - dedicated NVIDIA GeForce RTX 2070 (NVIDIA; 32.0.15.6094) - AMD Ryzen 7 2700X Eight-Core Processor (16 Threads)

### Issue description

I wanted to create a custom function to create various control nodes and I didn't know how to do it.
On the official Discord someone helped me and I learned about this '|' operator to combine the enums for the [SizeFlags](https://docs.godotengine.org/en/stable/classes/class_control.html#enum-control-sizeflags).
But that brought up warnings despite working perfectly, and when doing the combination outside the function it worked perfectly without warnings.
(would be nice if the documentation showed how to combine these enums - I had no idea you can even do that)

Looks similar to the warnings in issue #76223

### Steps to reproduce

1. Create a function with a 'Control.FlagSizes' type as a parameter.
2. Call the function (or enter default value) with an enum mixture: _Control.SIZE_SHRINK_END | Control.SIZE_EXPAND_

The warnings you get are:
![Image](https://github.com/user-attachments/assets/d25ae2eb-993c-40e8-943b-625df97a4ff0)


### Minimal reproduction project (MRP)

Make a new Control scene, add a child VBoxContainer and then add a child PanelContainer and Just copy the following:
```gdscript
extends Control

@onready var panel_container: PanelContainer = $VBoxContainer/PanelContainer


func _ready() -> void:
	panel_container.size_flags_vertical = Control.SIZE_SHRINK_END | Control.SIZE_EXPAND # no warning


func change_container_sizing(vertical: Control.SizeFlags = Control.SIZE_SHRINK_END | Control.SIZE_EXPAND) -> void:
	panel_container.size_flags_vertical = vertical


func call_function() -> void:
	change_container_sizing(Control.SIZE_SHRINK_END | Control.SIZE_EXPAND)
	var not_enum: int = Control.SIZE_SHRINK_END | Control.SIZE_EXPAND # no warning
	change_container_sizing(not_enum) # no warning
```
Repository: godot
Issue: Loading resources containing typed `Dictionary`s with values of type `Resource` causes a parse error
Labels: bug,topic:core,regression

### Tested versions

- Reproducible in v4.4.dev2 [97ef3c837] and later snapshots (tested in v4.4.dev2, v4.4.dev5, v4.4.dev6, and v4.4.dev7)
- Not reproducible in earlier versions, as support for typed dictionaries had not been added yet.

### System information

Godot v4.4.dev7 - Windows 10 (build 19045) - Multi-window, 2 monitors - Vulkan (Forward+) - dedicated Quadro M2200 - Intel(R) Core(TM) i7-6820HQ CPU @ 2.70GHz (8 threads)

### Issue description

When using the `load` function to load a .tres file containing a typed `Dictionary` with values of type `Resource` (e.g. `Dictionary[int, Resource]`), the resource fails to load and the following errors are present:
```
E 0:00:01:0172   main.gd:5 @ _ready(): user://save.tres:7 - Parse Error: Expected ']'
  <C++ Source>   scene/resources/resource_format_text.cpp:41 @ _printerr()
  <Stack Trace>  main.gd:5 @ _ready()

E 0:00:01:0172   main.gd:5 @ _ready(): Failed loading resource: user://save.tres. Make sure resources have been imported by opening the project in the editor at least once.
  <C++ Error>    Condition "found" is true. Returning: Ref<Resource>()
  <C++ Source>   core/io/resource_loader.cpp:323 @ _load()
  <Stack Trace>  main.gd:5 @ _ready()
```
The expected behavior is that the resource loads successfully without errors.

The issue does not occur when using a class that inherits `Resource`. For example, using a custom class called `CustomResource` that extends `Resource` will not cause the error.

Additionally, adding an extra mismatched closing square bracket to the .tres file stops the error as well:
```
data = Dictionary[int, Resource]]({})
```

### Steps to reproduce

1. Download and open the minimal reproduction project
2. Run the project
3. Check the Errors tab of the debugger, the above errors appear
4. In `SaveData.gd`, replace `Dictionary[int, Resource]` with `Dictionary[int, CustomResource]`
5. Run the project again and check the debugger, the errors are no longer thrown

### Minimal reproduction project (MRP)

[resource-loading-error.zip](https://github.com/user-attachments/files/18268655/resource-loading-error.zip)
Repository: godot
Issue: PhysicsDirectSpaceState3D.collide_shape fails on various Shape3Ds
Labels: documentation,topic:physics,needs testing,topic:3d

### Tested versions

- Tested in 4.3.stable.custom_build (Guix Build)
- Tested on 4.3 stable on Windows Downloaded from https://godotengine.org/download/windows/

### System information

Godot v4.3.stable unknown - Guix System #1 SMP PREEMPT_DYNAMIC 1 - X11 - Vulkan (Forward+) - dedicated AMD Radeon RX 7900 XT (RADV NAVI31) - AMD Ryzen 5 1600 Six-Core Processor (12 Threads)

### Issue description

When running PhysicsDirectSpaceState3D.collide_shape(query_parameters) where query_parameters is a PhysicsShapeQueryParameters3D with its `shape` set to either a `SeperationRayShape3D`, ~~`ConvexPolygonShape3D`~~, or a ~~`ConcavePolygonShape3D`~~ [(Working as intended)](https://github.com/godotengine/godot/issues/100890#issuecomment-2575668172), the collision will fail to check on all targets.

However, if the `PhysicsShapeQueryParameters3D.shape` is set to none of the above types, but hits any of the above types, it will successfully have a collision, seemingly meaning that this is a one-way problem.

This issue seems to be related to #65030

### Steps to reproduce (Imperfect now, [see this comment](https://github.com/godotengine/godot/issues/100890#issuecomment-2575668172))

1. Create two StaticBody3Ds, one as a ConcavePolygon3D and one as a Box3D (or any other shape) and ensure they intersect each other.
2. In code, Create a PhysicsShapeQueryParameters3D.new() with PhysicsShapeQueryParameters3D.shape set to a ConcavePolygon3d
3. Obtain the direct space state of the node that the ConcavePolygon3d belongs to
4. Run collide_shape() with the created PhysicsShapeQueryParameters3D as the query on the direct space state obtained from the PhysicsBody3D that ConcavePolygon3d belongs to.
5. Print the results and see that, no matter the circumstance, collide_shape() always fails to return a collision 

### Minimal reproduction project (MRP)

[PhysicsShapeQueryParameters3dFailedCollisions.zip](https://github.com/user-attachments/files/18335629/PhysicsShapeQueryParameters3dFailedCollisions.zip)
Repository: terminal
Issue: Implement (Contour's) Color Palette Update Notification and report
Labels: Issue-Feature,Product-Conhost,Help Wanted,Area-VT,Product-Terminal,Priority-3

### Description of the new feature

Implement Dark and Light Mode detection protocol adopted by few terminals and apps (neovim being the most well known i guess) 
the specification is presented here: https://github.com/contour-terminal/contour/blob/master/docs/vt-extensions/color-palette-update-notifications.md

### Proposed technical implementation details

_No response_