sharjeelyunus/github-issues-dataset huggingface dataset:
Repository: pytorch
Issue: [Beta] Have a generic `no_sync` for all synchronized training features 
Labels: oncall: distributed,triaged,module: fsdp

https://github.com/pytorch/pytorch/pull/63881#discussion_r703976049
https://github.com/pytorch/pytorch/blob/5f0d937b4da76ec8a66728eb77c90a7eb5a849fa/torch/distributed/_fsdp/fully_sharded_data_parallel.py#L328-L330

cc @pietern @mrshenli @pritamdamania87 @zhaojuanmao @satgera @rohan-varma @gqchen @aazzolini @osalpekar @jiayisuse @agolynski @SciPioneer @H-Huang @mrzzd @cbalioglu @gcramer23
Repository: pytorch
Issue: Backend capability chart for nccl GPU send/recv may be stale
Labels: oncall: distributed,module: nccl

## 📚 Documentation

The backend capability chart https://pytorch.org/docs/master/distributed.html#backends says nccl can't do GPU send/recv. But the implementations of send/recv in ProcessGroupNCCL look reasonable to me.

Should we change the nccl GPU send and recv :x: s to :heavy_check_mark: s, or are the :x: s still deliberate (maybe you still consider the implementations WIP for some reason)?


cc @pietern @mrshenli @pritamdamania87 @zhaojuanmao @satgera @rohan-varma @gqchen @aazzolini @osalpekar @jiayisuse @agolynski @SciPioneer @H-Huang @mrzzd @cbalioglu @gcramer23
Repository: rust
Issue: rustc docs: Re-exported types' implementations are lost
Labels: T-rustdoc,P-medium,T-compiler,regression-from-stable-to-stable,A-docs,C-bug,A-cross-crate-reexports,A-contributor-roadblock

For example, `ObligationCause` is defined in `rustc_middle`, and its docs look like this:

![image](https://user-images.githubusercontent.com/37223377/132577592-337df64e-663d-42d0-b4e1-5f9f3f6a5115.png)

-----

But it is also re-exported by `rustc_trait_selection`, where its inherent and trait implementations don't appear in the docs:

![image](https://user-images.githubusercontent.com/37223377/132577718-d9a4f37d-1903-4526-b608-bae8d2617244.png)

-----

This regressed in 1.47.0 (look at `/1.46.0/nightly-rustc` vs `/1.47.0/nightly-rustc` to compare). That is also the release when the `rustc_private` warning stopped showing up in the docs, so I wonder if the two changes are connected somehow. Furthermore, I have never witnessed this bug outside of the rustc docs, which makes me even more suspicious that something about `rustc_private` or rustbuild is causing this.
Repository: electron
Issue: [Bug]: Mouse clicks on target="_blank" links inside webview don't seem to give an event
Labels: bug :beetle:,platform/all,status/confirmed,has-repro-gist,15-x-y

### Preflight Checklist

- [X] I have read the [Contributing Guidelines](https://github.com/electron/electron/blob/master/CONTRIBUTING.md) for this project.
- [X] I agree to follow the [Code of Conduct](https://github.com/electron/electron/blob/master/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.

### Electron Version

15.0.0-beta.3

### What operating system are you using?

Other Linux

### Operating System Version

Fedora 34

### What arch are you using?

x64

### Last Known Working Electron version

14.x.x

### Expected Behavior

Clicking a link in a webview with the "_blank" attribute should result in any kind of event somewhere, but it doesn't seem to work since enabling "nativeWindowOpen".

### Actual Behavior

No event is triggered, not the `new-window` on the webview, nor the `setWindowOpenHandler` on it's webContents. Other link events and window.open do show up in the handler and the new-window event listener, so that's not it either.

### Testcase Gist URL

_No response_

### Additional Information

You can make it work again for now by disabling the unreliable "nativeWindowOpen" on both the BrowserWindow and it's containing webview.
Repository: pytorch
Issue: _disabled_torch_function_impl is unimplementable (must be special cased)
Labels: triaged,module: __torch_function__

This is most easily seen in the following example, prior to fixing https://github.com/pytorch/pytorch/issues/64687

```
import torch
class A:
    @classmethod
    def __torch_function__(cls, func, types, args=(), kwargs=None):
        print(types)

a = A()
b = torch.nn.Parameter()

torch.add(a, b)
torch.overrides.handle_torch_function(None, (a, b), a, b)
```

this prints:

```
(<class '__main__.A'>,)
(<class '__main__.A'>, <class 'torch.nn.parameter.Parameter'>)
```

Parameter is completely omitted from the types in the first case, which goes through the C++ parser. The Python code path via buggy `handle_torch_function` shows what a naive implementation that didn't handle this case explicitly does: it includes Parameter in the types list, because, well, that's what it's supposed to do.

This is not very nice because although we originally motivated disabled_torch_function_impl as a pure performance optimization, it actually also has semantic meaning: classes who disable torch function impl don't show up in the types list. This is important because other implementations of torch function may query the types list to determine if they understand the arguments or not. 

Unfortunately, this behavior is also quite desirable. Canonically, we are supposed to be able to mark anything as a Parameter and expect everything to work as is with it. So if someone studiously goes through all the arguments and tests that they are, in fact, Tensors, would in fact fail if they were passed a Parameter. So having disabled_torch_function_impl work this way increases interoperability of said classes with other use cases (we are basically saying, "yeah, this is a subclass, but just pretend it is a Tensor for all intents and purposes).

There is a related problem observed by @albanD that suggests that we might need to fix Parameter is some other, very fancy way. Suppose that you have a tensor subclass, and you want it also to be a Parameter. You can't just do the normal thing of `Parameter(my_tensor)` because Parameter overrides the subclass. This suggests that we actually want some sort of boolean property on regular Tensor that says if something is a Parameter or not, and then Parameter is just some fancy class which overrides the meaning of issubclass to test for this boolean. This sounds very disruptive and I'm not sure if we can actually do it, but we should if we can as it would make `Parameter(my_tensor)` transparently work.

cc @hameerabbasi @rgommers @peterbell10
Repository: pytorch
Issue: Remove the dependency with CUDA_LIBRARIES in TorchConfig.cmake
Labels: module: build,triaged

## 🚀 Feature
Remove the dependency with CUDA_LIBRARIES in TorchConfig.cmake
As today, TorchConfig.cmake 
https://github.com/pytorch/pytorch/blob/7e4ebe06cab4aedc66c501239ca568a0d28fd755/cmake/TorchConfig.cmake.in#L156
imposes to install a cuda sdk, search for cuda at cmake time, link the user application with the ${CUDA_LIBRARIES} whereas it does not seem to be needed in order to build and run an app using libTorch (whatever cpu or cuda).

## Motivation
Motivation: remove an unnecessary hard dependency at compilation/linking time.
Is your feature request related to a problem?
1 Needs to install a cuda SDK just to build an app linking with libTorch.so when there is no need to
2 Could be related to/resolve 
https://github.com/pytorch/pytorch/issues/19969

## Pitch

Just remove ${CUDA_LIBRARIES} in 
https://github.com/pytorch/pytorch/blob/7e4ebe06cab4aedc66c501239ca568a0d28fd755/cmake/TorchConfig.cmake.in#L156
and see that it s possible to build/link/run an exec with libTorch without issue, without the need to install any cuda SDK.

## Alternatives

In the user cmake script, clearing/unset/hack ${CUDA_LIBRARIES} after find_package(CUDA)

## Additional context
See that all the needed libs in order to build and run a program using libTorch are already embedded in the libTorch archive: example:
https://download.pytorch.org/libtorch/cu102/libtorch-shared-with-deps-1.9.0%2Bcu102.zip
and there is no need to search/build/link directly with the nvidia cuda_libraries.
At exec time, only 2 nvidia libs are needed and already provided in the LibTorch package: 
```cpp
$ lddtree test-libtorch 
test-libtorch
    libtorch.so => libtorch-1.7.0/lib/libtorch.so
    libc10.so => libtorch-1.7.0/lib/libc10.so
    libtorch_cuda.so 
        libcudart-80664282.so.10.2 => libtorch-1.7.0/lib/libcudart-80664282.so.10.2
        libnvToolsExt-3965bdd0.so.1 => libtorch-1.7.0/lib/libnvToolsExt-3965bdd0.so.1
    libtorch_cpu.so
    libnvToolsExt.so.1 => libtorch-1.7.0/lib/libnvToolsExt.so.1
```


cc @malfet @seemethere
Repository: pytorch
Issue: Torchscript Variable Length Tuples
Labels: oncall: jit

## 🚀 Feature
<!-- A clear and concise description of the feature proposal -->

It would be nice if torchscript would support variable length tuples like `tuple[int, ...]`. Consider the following example:

```python
import torch

def scaled_norm(
    x: torch.Tensor,
    dim: tuple[int, ...] = (),
    p: float = 2.0,
    keepdim: bool = False,
) -> torch.Tensor: 
    return torch.mean(x**p, dim=dim, keepdim=keepdim) ** (1/p)
```

This is a commonly used variant of the p-norm which is averaged against the number of elements. 

Currently, it is **impossible** to torch-script this function in a satisfiable way. One can either live with break MyPy by either

```python
def scaled_norm(
    # type: (Tensor, float, list[int], bool) -> Tensor
    x: torch.Tensor,
    dim: tuple[int, ...] = (),
    p: float = 2.0,
    keepdim: bool = False,
) -> torch.Tensor: 
```

or 

```python
def scaled_norm(
    x: torch.Tensor,
    dim: list[int] = (),
    p: float = 2.0,
    keepdim: bool = False,
) -> torch.Tensor: 
```

Or make `dim` a mandatory `list[int]` argument:

```python
def scaled_norm(
    x: torch.Tensor,
    dim: list[int],
    p: float = 2.0,
    keepdim: bool = False,
) -> torch.Tensor: 
    return torch.mean(x**p, dim=dim, keepdim=keepdim) ** (1/p)
```
Repository: terminal
Issue: Adjust / reduce the rate that text is output to the screen for visual effect.
Labels: Issue-Feature,Area-Extensibility,Product-Terminal


-->

Slow the output of text to each line, replicating the slow modems of old, teletypes and sci-fi movie computer text.

Cathode, a now dead/obsolete fancy terminal for MacOS (similar to CoolRetroTerm) had a similar feature. 

<!-- 
I found this was: 

Made reading lists / text in the terminal much easier to follow as it outputs (follow along rather than sudden jump)
Visually awesome 

-->

# Proposed technical implementation details (optional)

Artificially reduce the speed new characters are output to a line in any given terminal session. 

<!-- 
The best example I could find of this effect was this clip on youtube: https://youtu.be/zuAWjiws2tc?t=206 - see the effect as the graphics load in this video. 

The effect as the graphics load in this video, but with all text, at an adjustable rate that can be set in the user config. 

-->
Repository: material-ui
Issue: Class name on TextField select is impossible and unintuitive.
Labels: component: select

- [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 😯

There are **four** ways to add input class names to a `<TextField select />` component, and _none_ of them add the class name to the input.

```
<TextField
  select
  inputProps={{
    className: 'one',
  }}
  SelectProps={{
    inputProps: {
      className: 'two',
    },
  }}
  InputProps={{
    className: 'three',
    inputProps: {
      className: 'four',
    },
  }}
/>
```

This will add _one_ of the four class names to the wrapping `<div />` around the input and nothing to the input itself. I've found that if you put an arbitrary property on the input prop, it will append to the input, but the `className` prop specifically will get moved to the wrapping div.

## Expected Behavior 🤔

For all four class names to append to the input.
Repository: flutter
Issue: [cross_file] Migrate web tests to integration_test
Labels: package,team-ecosystem,P2,p: cross_file,triaged-ecosystem

The `cross_file` package is still using flutter test --platform=chrome (and [@TestOn('chrome/vm')](https://github.com/flutter/packages/search?q=TestOn)) to run its web tests. That is deprecated.

Migrate the web tests of `cross_file` to an integration test in the example directory, similarly to how it's been done in the flutter/plugins repo.

NOTE: cross_file is only a single, multi-platform package. Ensure that web-only tests only run in web-only environments (with a conditional import, for example).
Repository: go
Issue: net: document the meaning of "Temporary" and "Timeout"
Labels: Documentation,NeedsInvestigation

The docs for `net` have a lot of `Temporary` and `Timeout` error methods in them, but the package level docs don't contain a discussion of what those errors mean. The `Temporary` methods are mentioned in [blog post about error handling](https://go.dev/blog/error-handling-and-go) but don't actually describe their meaning in detail.

And then for the errors types specifically, if an error type have both `Temporary` and `Timeout`, it'd be nice to document if both can be true at once and what that means semantically. (This originally cropped up when trying to explain if and when an error in a lower-level network protocol would or would not be counted against a rate limit in a higher-level one.)
Repository: pytorch
Issue: Add out= resize warning to cat and maybe_native_stack
Labels: triaged,better-engineering,module: viewing and reshaping

Per title. Like with other BC-breaking changes we should ensure that our internal code base doesn't throw this warning, and there are some places where PyTorch relies on out= resizing a tensor when using cat or stack, like 

https://github.com/pytorch/pytorch/blob/149f1114fe94dc90fbb7000669a98c2337e25a54/torch/utils/data/_utils/collate.py#L56
Repository: pytorch
Issue: Improve Docs builds to not have to push to a repository to update
Labels: module: docs,triaged,enhancement,module: doc infra

## 🚀 Feature
<!-- A clear and concise description of the feature proposal -->

I'd like to make it so that docs builds do not have to push to a repository to update

## Motivation

<!-- Please outline the motivation for the proposal. Is your feature request related to a problem? e.g., I'm always frustrated when [...]. If this is related to another GitHub issue, please link here too -->

Docs builds / updates currently rely on pushes to both https://github.com/pytorch/pytorch.github.io and https://github.com/pytorch/cppdocs which creates a lot of commits and makes cloning / contributing to these repositories problematic (see https://github.com/pytorch/pytorch.github.io/issues/825)

## Pitch

<!-- A clear and concise description of what you want to happen. -->

### Using S3 / Cloudfront

For this approach we can choose to redirect `docs.pytorch.org` and `pytorch.org/docs` to an s3 bucket that can be fronted by cloudfront, similar to `download.pytorch.org`

Updates will still be handled similarly to how they're handled today and not much changes outside of the push location

## Alternatives

<!-- A clear and concise description of any alternative solutions or features you've considered, if any. -->

## Additional context

<!-- Add any other context or screenshots about the feature request here. -->


cc @brianjo @mruberry @ezyang @zou3519
Repository: transformers
Issue: add non auto regressive model?
Labels: New model

This research area is developing very fast in the past two years, which could improve latency  significantly with quality on par. Will huggingface team be interested into the implementation of it? Thanks.
Repository: flutter
Issue: MaterialBanner cannot be dismissed once creation context is deactivated
Labels: framework,f: material design,has reproducible steps,found in release: 2.5,found in release: 2.6,team-design,triaged-design

Error Info:

```console
Looking up a deactivated widget's ancestor is unsafe.
At this point the state of the widget's element tree is no longer stable.
To safely refer to a widget's ancestor in its dispose() method, save a reference to the ancestor by calling dependOnInheritedWidgetOfExactType() in the widget's didChangeDependencies() method.
```
Repository: ant-design
Issue: The maxCount configuration item of the message component does not take effect after switching the browser tab
Labels: Inactive

- [ ] I have searched the [issues](https://github.com/ant-design/ant-design/issues) of this repository and believe that this is not a duplicate.

### Reproduction link
[![Edit on CodeSandbox](https://codesandbox.io/static/img/play-codesandbox.svg)](https://codesandbox.io/s/antd-reproduction-template-forked-cz4t0?file=/index.js)

### Steps to reproduce
1. Make a function of timing the message, and set the maxCount of the message to 1, and set the duration to 0.5
2. After switching the browser tab for a period of time, switch back to the problem tab

### What is expected?
2. After switching the browser tab for a period of time, switch back to the problem tab. There will be at most one message pop-up window.

### What is actually happening?
2. After switching the browser tab for a period of time, then switch back to the problem tab, and found that many message pop-ups appeared

| Environment | Info |
|---|---|
| antd | 4.10.3 |
| React | 16.14.0 |
| System | window10 |
| Browser |  91.0.4472.164 |


<!-- generated by ant-design-issue-helper. DO NOT REMOVE -->
Repository: godot
Issue: "Unwrap UV2" doesn't notify that UV2s can't be saved for OBJs
Labels: bug,confirmed,usability,topic:import,topic:3d

### Godot version

v3.4.beta4.official [6a058cbf3]

### System information

Windows 10, GLES3

### Issue description

(related to https://github.com/godotengine/godot/issues/32746 ?)

If this is to be expected, can the option at least notify that it can't generate UV2s because the format does not support them? (not unlike how it does notify about unsupported MeshRenderer types)

### Steps to reproduce

* Open the attached sample project
* Open Test.tscn
* Click on the single Mesh on the scene
* Pick Mesh➜Unwrap UV2
* Re-open the scene
* Note that UV2 is nowhere to be seen

![godot-uv2](https://user-images.githubusercontent.com/731492/132620162-41560836-f165-4abc-9fb1-795d2783ff52.gif)


### Minimal reproduction project

[Portals34.zip](https://github.com/godotengine/godot/files/7133265/Portals34.zip)
Repository: godot
Issue: Converting an OBJ to import as a scene and back prevents containing scenes from loading
Labels: bug,topic:import,topic:3d

### Godot version

v3.4.beta4.official [6a058cbf3]

### System information

Windows 10, GLES3

### Issue description

After reproduction steps, TSCN looks as following:
```ini
[gd_scene load_steps=3 format=2]

[ext_resource path="res://Test.lmbake" type="BakedLightmapData" id=1]
[ext_resource path="res://test.obj" type="PackedScene" id=2]

[node name="Spatial" type="Spatial"]

[node name="test" parent="." instance=ExtResource( 2 )]

[node name="BakedLightmap" type="BakedLightmap" parent="."]
environment_mode = 1
light_data = ExtResource( 1 )

[node name="DirectionalLight" type="DirectionalLight" parent="."]
transform = Transform( -0.95401, 0.121417, -0.274084, -0.168999, 0.537323, 0.82627, 0.247595, 0.834591, -0.492093, -2.59119, 2.3551, -6.79807 )
light_bake_mode = 2

[node name="Camera" type="Camera" parent="."]
transform = Transform( -0.129013, 0.421938, -0.897398, 0.0600421, 0.906625, 0.417644, 0.989824, 3.68738e-09, -0.142301, -4.87034, 2.65535, 0 )
current = true
```
Manually removing `test.obj`-related lines fixes the issue - I take it that the editor tries to parse the OBJ as a scene file? Could be good to only abort loading the sub-scene so that it can be removed easier.

### Steps to reproduce

1. Open the attached sample
2. Pick `test.obj`, Import tab, switch type to "Scene", click Reimport
3. After editor restarts, open `Test.tscn`, remove MeshRenderer, add the obj-scene by dragging and dropping `test.obj` into the scene tree.
4. Pick `test.obj` again, Import tab, switch type to "OBJ as Mesh", click Reimport
5. After editor restarts, try to open `Test.tscn`, note the "unexpected end of file"

### Minimal reproduction project

[Portals34.zip](https://github.com/godotengine/godot/files/7133265/Portals34.zip)
Repository: godot
Issue: Godot silently crashes if no _init is specified in GDNative class
Labels: bug,topic:gdextension,crash

### Godot version

Godot_v3.3.3-stable_win64

### System information

Windows 10

### Issue description

It is perfectly possible to compile a GDNative C++ class that does not define a `_init` method without any warnings or compile errors. However once the class gets instantiated like this:

`onready var test = preload("res://bin/test.gdns").new()` 

the game will just silently exit without any warnings, logs or errors to indicate a crash. The crash happens in this method in Object.cpp

```
void Object::_init() {
	___godot_icall_void(___mb.mb__init, (const Object *) this);
}
```

where `___mb` is a nullptr resulting in an obvious nullptr exception that (without a debugger attached) gets silently discarded and crashes the engine.

### Steps to reproduce

Create GDNative class without `_init` method and then try to instantiate it.

### Minimal reproduction project

_No response_
Repository: opencv
Issue: Movenet model of onnx cannot read by opencv dnn
Labels: feature,category: dnn,category: dnn (onnx)

opencv : opencv4.5.3(5ac5da35249e0e8e1f787f7f44f5de6e74297c1a)
os : ubuntu20.04
compiler : g++ (Ubuntu 9.3.0-17ubuntu1~20.04) 9.3.0

Process to download and convert the models

```
wget -q -O movenet_singlepose_lightning_4.tar.gz https://tfhub.dev/google/movenet/singlepose/lightning/4?tf-hub-format=compressed
!mkdir movenet_singlepose_lightning_4
!tar -zxvf movenet_singlepose_lightning_4.tar.gz -C movenet_singlepose_lightning_4/
python -m tf2onnx.convert --opset 11 \
    --saved-model movenet_singlepose_lightning_4 \
    --output movenet_singlepose_lightning_4.onnx
```

Load model from c++

```
#include <opencv2/dnn.hpp>

#include <iostream>
#include <stdexcept>

using namespace std;

int main(int argc, char *argv[])try
{    
    auto net = cv::dnn::readNet(std::string(argv[1]) + "/models/onnx/movenet_singlepose_lightning_4.onnx");

}catch(std::exception const &ex){
    cerr<<ex.what()<<endl;
}
```

Error message:

```
[ERROR:0] global /home/yyyy/cv_projects/3rdLibs/opencv/modules/dnn/src/onnx/onnx_importer.cpp (627) handleNode DNN/ONNX: ERROR during processing node with 1 inputs and 1 outputs: [ArgMax]:(StatefulPartitionedCall/ArgMax:0)
exception = OpenCV(4.5.3-dev) /home/yyyy/cv_projects/3rdLibs/opencv/modules/dnn/src/onnx/onnx_importer.cpp:648: error: (-2:Unspecified error) in function 'handleNode'
> Node [ArgMax]:(StatefulPartitionedCall/ArgMax:0) parse error: OpenCV(4.5.3-dev) /home/yyyy/cv_projects/3rdLibs/opencv/modules/dnn/src/dnn.cpp:615: error: (-2:Unspecified error) Can't create layer "StatefulPartitionedCall/ArgMax:0" of type "ArgMax" in function 'getLayerInstance'
> 
```

[Link of the model](https://drive.google.com/file/d/1ALtgsgwownfyAURc0UrpEaFvz-cH1paX/view?usp=sharing)

Works well with onnx.