sharjeelyunus/github-issues-dataset huggingface dataset:
Repository: pytorch
Issue: Enabling `swap_tensors` path by default for all tensor subclasses errors on some transformer tests
Labels: module: nn,triaged

### 🐛 Describe the bug

The specific issue this tracks is https://github.com/pytorch/pytorch/pull/122755#discussion_r1541541639 

We see that the reference count of layernorm's weight is 3 in this test. However, the [swap_tensors test for `LayerNorm`/`TransformerEncoder`](https://github.com/pytorch/pytorch/blob/main/test/test_modules.py?fbclid=IwAR3ytpr8RQjdgcxIW_z5sMEOaAEcTftAYDOHwqWiiXBbV8oIMiS2K_pDNtA#L866-L983)does not catch this.

Worth investigating whether this is due to the way the test is written or an inherent problem with `TransformerEncoder`/`LayerNorm` and the `swap_tensors` path in `nn.Module._apply`

```
<class 'torch.nn.parameter.Parameter'>
E
======================================================================
ERROR: test_transformerencoder_batch_first_False_training_True_enable_nested_tensor_False_cpu (__main__.TestTransformersCPU)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/home/tristanr/pytorch/torch/nn/modules/module.py", line 819, in _apply
    torch.utils.swap_tensors(param, param_applied)
  File "/home/tristanr/pytorch/torch/utils/__init__.py", line 68, in swap_tensors
    torch._C._swap_tensor_impl(t1, t2)
RuntimeError: Expected single reference to a's Tensor object but got 3

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/home/tristanr/pytorch/torch/testing/_internal/common_utils.py", line 2741, in wrapper
    method(*args, **kwargs)
  File "/home/tristanr/pytorch/torch/testing/_internal/common_device_type.py", line 432, in instantiated_test
    raise rte
  File "/home/tristanr/pytorch/torch/testing/_internal/common_device_type.py", line 419, in instantiated_test
    result = test(self, **param_kwargs)
  File "/home/tristanr/pytorch/test/test_transformers.py", line 643, in test_transformerencoder
    _test(batch_first, training, enable_nested_tensor)
  File "/home/tristanr/pytorch/test/test_transformers.py", line 615, in _test
    enable_nested_tensor=enable_nested_tensor).to(device)
  File "/home/tristanr/pytorch/torch/nn/modules/module.py", line 1174, in to
    return self._apply(convert)
  File "/home/tristanr/pytorch/torch/nn/modules/module.py", line 778, in _apply
    module._apply(fn)
  File "/home/tristanr/pytorch/torch/nn/modules/module.py", line 823, in _apply
    raise RuntimeError(f"_apply(): Couldn't swap {self._get_name()}.{key}") from e
RuntimeError: _apply(): Couldn't swap LayerNorm.weight

To execute this test, run the following from the base repo dir:
     python test/test_transformers.py -k test_transformerencoder_batch_first_False_training_True_enable_nested_tensor_False_cpu

This message can be suppressed by setting PYTORCH_PRINT_REPRO_ON_FAILURE=0
```

### Versions

main

cc @albanD @mruberry @jbschlosser @walterddr @d4l3k
Repository: pytorch
Issue: In Inductor-wrapped tests, reset() before and after each test and turn off suppress_errors=True
Labels: module: tests,triaged,oncall: pt2,module: inductor

We did this for the Dynamo-wrapped (i.e. PYTORCH_TEST_WITH_DYNAMO=1) tests but didn't get around to the Inductor-wrapped tests (i.e. PYTORCH_TEST_WITH_INDUCTOR=1).

cc @mruberry @ZainRizvi @ezyang @msaroufim @bdhirsh @anijain2305 @chauhang @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @peterbell10 @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 @aakhundov @ColinPeppler @amjames @desertfire
Repository: pytorch
Issue: Deprecate accessing FakeTensor outside of torch.compile
Labels: triaged,module: fakeTensor

We'd like to make FakeTensor semantics the same inside and outside of torch.compile. 

cc @eellison
Repository: tauri
Issue: Problems with window customization's rounded corners and shadows
Labels: type: bug,status: needs triage

### Describe the bug

Because tauri does not support the extension of native windows, I have to manually implement custom windows.  I tried to simulate macos' window implementation and expand on it, such as menus, tabs, and titles.
I implemented some basic functions through the [tauri-controls](https://github.com/agmmnn/tauri-controls) library, but there are still some issues.
### 1. Incomplete implementation of rounded corners
To support rounded corners, I made some settings:
```json
"windows": [
      {
        "title": "myapp",
        "shadow": true,
        "width": 1000,
        "height": 700,
        "fullscreen": false,
        "center": true,
        "transparent": true,
        "decorations": false,
        "resizable": true
      }
 ],
```
and then (styles.css):
```css
:root {
    border-radius: 12px;
    ...
}
body{
    background: #fff;
    position: absolute;
    top: 0;
    left: 0;
    width: 100%;
    height: 100%;
    border: none;
    margin: 0;
    padding: 0;
    overflow: hidden;
}
```
The final effect:
![11111](https://github.com/tauri-apps/tauri/assets/17827693/14f36526-c0a3-4ede-90c2-af6a364d5921)

Obviously, the corners on the top left and top right are not rounded.  The background seems to be transparent, but it still has a border that affects the implementation of rounded corners. How can I fix it?

### 2. Shadow enhancement
I want to make some modifications to the shadow to enhance it. How can I do that?
![2222](https://github.com/tauri-apps/tauri/assets/17827693/70b5b54f-0b4d-4aec-9ef3-0dcdb1b374da)

About tauri v2, I hope the official can provide a complete case of customizing windows, including simulating native windows, as well as customizing menus, tabs, titles, and other features.


### Reproduction

_No response_

### Expected behavior

_No response_

### Full `tauri info` output

```text
nothing
```


### Stack trace

_No response_

### Additional context

system: macOS monterey
version: 12.6
tauri version:
```toml
tauri = { version = "2.0.0-beta.13", features = ["macos-private-api"] }
tauri-plugin-os = "2.0.0-beta.3"
tauri-plugin-shell = "2.0.0-beta.3"
```
```json
{
   "@tauri-apps/api": "v2.0.0-beta.6",
    "@tauri-apps/plugin-os": "2.0.0-beta.2",
    "@tauri-apps/cli": "2.0.0-beta.11"
}
```
Repository: pytorch
Issue: DISABLED test_custom_op_1_cuda_cuda_wrapper (__main__.TestCudaWrapper)
Labels: module: rocm,triaged,skipped

Platforms: rocm

This test was disabled because it is failing on main branch ([recent examples](https://torch-ci.com/failure?failureCaptures=%5B%22inductor%2Ftest_cuda_cpp_wrapper.py%3A%3ATestCudaWrapper%3A%3Atest_custom_op_1_cuda_cuda_wrapper%22%5D)).

Broken by https://github.com/pytorch/pytorch/pull/122554.  This issue is faster than landing a skip decorator.

cc @sunway513 @jithunnair-amd @pruthvistony @ROCmSupport @dllehr-amd @jataylo @hongxiayang
Repository: pytorch
Issue: cpu performance for int4mm kernels
Labels: module: performance,module: cpu,enhancement,oncall: pt2,oncall: cpu inductor

### 🐛 Describe the bug

Repro: https://github.com/pytorch-labs/ao/pull/93

currently the cpu time for running weight only int4 quantization seems to be slow in x86, looks the same as unlowered cpu model (without torch.compile):

```
fp32 time: 1820.7485029697418
unlowered cpu time: 5.564050674438477
lowered cpu time: 6.455274343490601
lowered cpu time: 9.147282600402832
lowered cpu time: 7.690609931945801
lowered cpu time: 6.081359624862671
lowered cpu time: 9.295523405075073
lowered cpu time: 9.140728235244751
lowered cpu time: 4.560685873031616
lowered cpu time: 4.906892776489258
lowered cpu time: 8.88036060333252
lowered cpu time: 8.990303754806519
avg cpu time: 7.514902114868164
```

cc @jgong5 @mingfeima @XiaobingSuper @sanchitintel @ashokei @jingxu10 @ezyang @msaroufim @bdhirsh @anijain2305 @chauhang @malfet


### Versions

pytorch main
Repository: pytorch
Issue: torchdim as torch_function subclass exploration
Labels: triaged,module: __torch_function__

One method of productionizing torchdim is to turn the abstractions into tensor subclasses. I made a quick prototype of that over at https://gist.github.com/zou3519/3b1961f7fb4eddc36690801f13e5fa9a so that we can do some testing.

It looks like we don't support torch_function subclass + torch.compile too well (or, at least, I saw a bunch of error messages and gave up). Opening this issue to figure it out.

cc @hameerabbasi @rgommers @peterbell10 @ezyang
Repository: vscode
Issue: File explorer only supports drag and drop of a single item
Labels: bug,file-explorer

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Does this issue occur when all extensions are disabled?: Yes/No

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Version: 1.87.2 (user setup)
Commit: 863d2581ecda6849923a2118d93a088b0745d9d6
Date: 2024-03-08T15:20:17.278Z
Electron: 27.3.2
ElectronBuildId: 26836302
Chromium: 118.0.5993.159
Node.js: 18.17.1
V8: 11.8.172.18-electron.0
OS: Windows_NT x64 10.0.22631

Steps to Reproduce:

1. In the Explorer sidebar, select multiple files using Ctrl+Click or Shift+Click.
2. Drag and drop the files into a folder in File Explorer or onto the desktop.

Expected behavior:
The files are copied into the folder they were dropped into.

Actual behavior:
Only one of the selected files is copied. Typically the first file selected, but can also be the one at the top of the selection.
Repository: godot
Issue: Godot Editor freezes 4.2.1-stable_mono_win64
Labels: bug,topic:editor,needs testing

### Tested versions

4.2.1stable

### System information

Windows 11

### Issue description

The Editor freezes and just a taskmanager kill can close the editor

### Steps to reproduce

load the project. Click Scene and the + symbol the ui freezes.

### Minimal reproduction project (MRP)

[godotEditorCrash.zip](https://github.com/godotengine/godot/files/14780035/godotEditorCrash.zip)
Repository: neovim
Issue: Core logging mechanism
Labels: enhancement,logging

### Problem

Having a robust logging mechanism in Neovim core would allow plugins to easily log to a singular location that users know to look for, making it easier users to provide more useful context for plugin authors.

### Expected behavior

Not entirely sure the best approach, but I think something similar in spirit to VSCode's [Output Panel](https://code.visualstudio.com/docs/getstarted/userinterface#_basic-layout) would be nice.

Key benefits would be having logging channels per LSP client and plugins (in VSCode, an extensions can make arbitrary "output channels" and name them whatever they'd like).

They are easy to view and locate in the UI.

I have a plugin that mimics this behavior for LSP clients, but can't currently be used for arbitrary output. https://github.com/mhanberg/output-panel.nvim

These logs are not persisted, but just live in memory.

I'm not sure what a core nvim UI for this would look like (tab per channel?, floating window with tab in in the winbar?) or if it would just provide a core api, and a plugin can provide a nicer UI for it.

Thanks for the consideration!
Repository: angular
Issue: rxjs-interop: bidirectional interop
Labels: feature,area: core,cross-cutting: signals,core: rxjs interop

### Which @angular/* package(s) are relevant/related to the feature request?

core

### Description

Currently, `toSignal` and `toObservable` functions always return read-only primitives - `Signal` and `Observable` respectively. It would be really handy if passing a writable primitive to interop functions created a writable counterpart of passed value.

Examples:

```ts
const someSignal = signal(1)
effect(() => {
  const value = someSignal()
  console.log('signal changed:', value)
})

const someSubject = toObservable() // returned a Subject!
someSubject.next(2) // signal changed: 2
```

```ts
const someSubject = new Subject(1)
someSubject.subscribe(value => console.log('subject changed:', value)

const someSignal = toSignal(someSubject) // returned a WritableSignal!
someSignal.set(2) // => subject changed: 2
someSignal.update(prev => prev * 2) // => subject changed: 4
```

### Proposed solution

Return a `WritableSignal` from `toSignal` if argument is `next`-able. Whenever a value is written to the signal manually, push it to the target observable.

In `toObservable`, return a subject if argument is a `WritableSignal`. Whenever a value is pushed to the subject manually, write it to the target signal.

### Alternatives considered

Leave everything as is.
Repository: angular
Issue: [i18n] `ng insert-i18n` (reverse `ng extract-i18n`)
Labels: area: i18n

### Which @angular/* package(s) are relevant/related to the feature request?

localize

### Description

There is a barrier for using Angular's i18n solution because eventually the source code and source language file will differ and to keep them in sync the source code needs to be manually updated which means a developer has to spend time on an automatable task.

If the process was two-way, the i18n package would be way more useful; and not only for its core intent but also for simply maintaining the text content of an app.

### Proposed solution

Ideally the cli supports a command to write the strings from the extracted source language file back into the source code.

```bash
ng insert-i18n
```

### Alternatives considered

Right now the differences between language file and source code need to be cleaned up manually or by writing a custom automation script. Both alternatives are imho dealbreakers and made me implement a custom way to deal with i18n every single time.
Repository: vscode
Issue: Ctrl+A flakyiness in HTML Notebook outputs
Labels: bug,notebook-output

Originally reported here https://github.com/microsoft/vscode/issues/204950#issuecomment-2022920553

`ctrl+A` doesn't seem to work quite right. I only see that everything in an output cell is shown after focusing out of the output:

![Recording 2024-03-27 at 15 31 01](https://github.com/microsoft/vscode/assets/38270282/90aa3df8-691d-4969-9a70-5bfbafdc4b09)
Repository: ant-design
Issue: Dropdown is missing critical accessibility attributes
Labels: help wanted,Inactive,⌨️ Accessibility

### What problem does this feature solve?

Currently the Dropdown component does not meet WAI-ARIA standards for Menu Button Pattern (https://www.w3.org/WAI/ARIA/apg/patterns/menu-button/):

Specifically:
- The element with role button has aria-haspopup set to either menu or true.
- When the menu is displayed, the element with role button has aria-expanded set to true. When the menu is hidden, aria-expanded is set to false.
- The element that contains the menu items displayed by activating the button has role menu.
Optionally, the element with role button has a value specified for aria-controls that refers to the element with role menu.

And furthermore from the Menu and MenuBar Pattern (https://www.w3.org/WAI/ARIA/apg/patterns/menubar/), though neither of these roles are used in Dropdown, it can be reasonably deduced that in Dropdown, the element with role=button should accept an aria-label prop to assist those with screen readers properly identifying it.

The Dropdown component currently does accept an aria-label prop, but it does not seem to actually get applied anywhere in the DOM structure.

### What does the proposed API look like?

Most of the above is satisfied by internal definitions, but the Dropdown component must expose an aria-label prop that maps to the aria-label attribute on the element that has role=button.

<!-- generated by ant-design-issue-helper. DO NOT REMOVE -->
Repository: flutter
Issue: [web] Cryptic error when renderer does not support multiview.
Labels: engine,platform-web,e: web_html,P2,c: tech-debt,team-web,triaged-web

When deploying a normal Flutter app (with "auto" renderer), the error in mobile when the HTML renderer attempts to run is cryptic:

![cryptic-renderer-error](https://github.com/flutter/flutter/assets/1255594/16e436aa-b30b-4967-8b82-83f37ace60f3)

Do something in the Multiview mode/HTML renderer so that error has a more specific message.
Repository: pytorch
Issue: DISABLED test_custom_op_1_cuda_dynamic_shapes_cuda_wrapper (__main__.DynamicShapesCudaWrapperCudaTests)
Labels: module: rocm,triaged,skipped

Platforms: rocm

This test was disabled because it is failing on main branch ([recent examples](https://torch-ci.com/failure?failureCaptures=%5B%22inductor%2Ftest_cuda_cpp_wrapper.py%3A%3ADynamicShapesCudaWrapperCudaTests%3A%3Atest_custom_op_1_cuda_dynamic_shapes_cuda_wrapper%22%5D)).

Hoping that this is the last test that needs skipping after https://github.com/pytorch/pytorch/pull/122554 landed.  https://github.com/pytorch/pytorch/issues/122811 was created to skip another test broken by the same PR.  If it goes beyond these 2 issues, will ask for a revert.  CC @desertfire 

cc @sunway513 @jithunnair-amd @pruthvistony @ROCmSupport @dllehr-amd @jataylo @hongxiayang
Repository: flutter
Issue: [ci] Update version of actions/cache in flutter/packages release workflow.
Labels: team,package,team-ecosystem,P2,c: tech-debt,triaged-ecosystem

The release workflow has started emitting a warning similar to this:

> [!WARNING]
> **release** 
> Node.js 16 actions are deprecated. Please update the following actions to use Node.js 20: actions/cache@v3. For more information see: https://github.blog/changelog/2023-09-22-github-actions-transitioning-from-node-16-to-node-20/.

Update the [`actions/cache`](https://github.com/marketplace/actions/cache) we use in the `release` workflow to `@v4`.

(Looks like a transient dependency, though!)
Repository: stable-diffusion-webui
Issue: [Bug]: inpaint zoom is broken on firefox
Labels: bug-report

### Checklist

- [X] The issue exists after disabling all extensions
- [X] The issue exists on a clean installation of webui
- [X] The issue is caused by an extension, but I believe it is caused by a bug in the webui
- [X] The issue exists in the current version of the webui
- [X] The issue has not been reported before recently
- [X] The issue has been reported before but has not been fixed yet

### What happened?

alt+wheel up makes the image either go super zoom without any way to navigate it or goes micro. No mid stages.

### Steps to reproduce the problem

alt+wheel up on inpaint

### What should have happened?

have an incremental zoom, controllable

### What browsers do you use to access the UI ?

Mozilla Firefox

### Sysinfo

:__

### Console logs

```Shell
____
```


### Additional information

_No response_
Repository: pytorch
Issue: a log_softmax kernel get much worse perf with padding
Labels: triaged,oncall: pt2,module: inductor

### 🐛 Describe the bug

I'm debugging the perf loss of a longformer model for PR (https://github.com/pytorch/pytorch/pull/120758). One thing I found is, for the following log-softmax kernel, padding the output of a log_softmax kernel slow it down from 1.1ms to 1.6ms. This is counter-intuitive since in general padding should help here. Full runnable kernel: https://gist.github.com/shunting314/20c3249c9b206f1abc8f7c9db208d712 .

```
@triton.jit
def triton_red_fused__log_softmax_6(in_ptr0, out_ptr2, xnumel, rnumel, XBLOCK : tl.constexpr, RBLOCK : tl.constexpr):
    xnumel = 4096
    rnumel = 50265
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:, None]
    xmask = xindex < xnumel
    rbase = tl.arange(0, RBLOCK)[None, :]
    x0 = xindex
    _tmp3 = tl.full([XBLOCK, RBLOCK], float("-inf"), tl.float32)
    for roffset in range(0, rnumel, RBLOCK):
        rindex = roffset + rbase
        rmask = rindex < rnumel
        r1 = rindex
        tmp0 = tl.load(in_ptr0 + (r1 + (50272*x0)), rmask, eviction_policy='evict_last', other=0.0).to(tl.float32)
        tmp1 = tmp0.to(tl.float32)
        tmp2 = tl.broadcast_to(tmp1, [XBLOCK, RBLOCK])
        tmp4 = triton_helpers.maximum(_tmp3, tmp2)
        _tmp3 = tl.where(rmask, tmp4, _tmp3)
    tmp3 = triton_helpers.max2(_tmp3, 1)[:, None]
    _tmp10 = tl.full([XBLOCK, RBLOCK], 0, tl.float32)
    for roffset in range(0, rnumel, RBLOCK):
        rindex = roffset + rbase
        rmask = rindex < rnumel
        r1 = rindex
        tmp5 = tl.load(in_ptr0 + (r1 + (50272*x0)), rmask, eviction_policy='evict_last', other=0.0).to(tl.float32)
        tmp6 = tmp5.to(tl.float32)
        tmp7 = tmp6 - tmp3
        tmp8 = tl_math.exp(tmp7)
        tmp9 = tl.broadcast_to(tmp8, [XBLOCK, RBLOCK])
        tmp11 = _tmp10 + tmp9
        _tmp10 = tl.where(rmask, tmp11, _tmp10)
    tmp10 = tl.sum(_tmp10, 1)[:, None]
    for roffset in range(0, rnumel, RBLOCK):
        rindex = roffset + rbase
        rmask = rindex < rnumel
        r1 = rindex
        tmp12 = tl.load(in_ptr0 + (r1 + (50272*x0)), rmask, eviction_policy='evict_first', other=0.0).to(tl.float32)
        tmp13 = tmp12.to(tl.float32)
        tmp14 = tmp13 - tmp3
        tmp15 = tl_math.log(tmp10)
        tmp16 = tmp14 - tmp15
        tmp17 = tmp16.to(tl.float32)

        # 1.6ms with this
        tl.store(out_ptr2 + (r1 + (50272*x0)), tmp17, rmask)
        # 1.1ms with this
        # tl.store(out_ptr2 + (r1 + (50265*x0)), tmp17, rmask)
```

cc @ezyang @msaroufim @bdhirsh @anijain2305 @zou3519 @chauhang @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @peterbell10 @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 @aakhundov @ColinPeppler @amjames @desertfire @jansel 
cc @htyu not sure if it's due to triton or not.

### Error logs

_No response_

### Minified repro

_No response_

### Versions

..