sharjeelyunus/github-issues-dataset huggingface dataset:
Repository: vscode
Issue: Consider using a new grammar for Groovy: Failed to highlight multi-lined regexp in Groovy code
Labels: feature-request,grammar

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- VS Code Version: 1.65.2
- OS Version: all

Steps to Reproduce:

1. The following syntax highlighting failed as mentioned in https://github.com/textmate/groovy.tmbundle/pull/20

    - Able to capture:

        ```groovy
        ~/multi-lined[\/]
            regexp/
        ```

    - But failed to capture:

        ```groovy
        ~/multi-lined
            regexp/
        ```
Repository: flutter
Issue: Go Router: Multi language support
Labels: c: new feature,a: internationalization,package,P3,p: go_router,team-go_router,triaged-go_router

**This is a feature request.**

This issue is For the [go_router](https://github.com/flutter/packages/tree/main/packages/go_router) package

In my App, I want to have multi-language support, as well as for the routes. 
for example:
`myapp.com/post/12` -> should redirect to the post with the id 12, with setting the app language to **English**
`myapp.com/gonderi/12` -> should redirect to the post with the id 12, with setting the app language to **Turkish**

The syntax could be something like:

```
GoRoute(
  paths: {
    'en': 'post',
    'tr': 'gonderi',
  },
```

and in the GoRouterState, the route that redirected would be saved as a `MapEntry`. so the language key would be reachable using `state.path.key`, and the route name `state.path.value`.

this functionality obviously can be reachable by duplicating the routes, however, when you start considering even 2 languages, this gives you 2x the code, which is very hard to maintain.
Repository: flutter
Issue: Flutter displays high quality images with noise
Labels: framework,a: quality,a: images,has reproducible steps,P2,found in release: 2.10,found in release: 2.13,team-framework,triaged-framework

Hello,  I found a lot of noise when using Flutter to load local high quality images.

my image's info:  jpg  7.30MB  4380*6570

I tried using the basic Image widget and the Canvas method, and the results were the same.

I only tested Android and Desktop.

![17](https://user-images.githubusercontent.com/58471330/158330124-3f8023f6-db21-4ebe-8920-891c88e70f2a.png)

The second one should be the same as the third one, because the third one is a screenshot by PC, so the quality looks worse.

Doctor summary (to see all details, run flutter doctor -v):
[√] Flutter (Channel stable, 2.10.3, on Microsoft Windows [Version 10.0.19044.1586], locale zh-CN)
[√] Android toolchain - develop for Android devices (Android SDK version 32.1.0-rc1)
[√] Chrome - develop for the web
[√] Visual Studio - develop for Windows (Visual Studio Community 2022 17.1.1)
[√] Android Studio (version 2021.1)
[√] Connected device (4 available)
[!] HTTP Host Availability
    X HTTP host https://maven.google.com/ is not reachable. Reason: An error occurred while checking the HTTP host:
      信号灯超时时间已到


! Doctor found issues in 1 category.
Repository: pytorch
Issue: RuntimeError: CUDA error: unspecified launch failure
Labels: module: cudnn,module: cuda,triaged

## Issue description
 

> RuntimeError: CUDA error: unspecified launch failure
Error occurring on any training script. Occurrence is not deterministic. Can occur at anytime during the course of training.
All the codes work fine on RTX 3090.


/lib/python3.8/site-packages/torch/autograd/__init__.py
Variable._execution_engine.run_backward(
RuntimeError: CUDA error: unspecified launch failure


## System Info
PyTorch version: 1.10.2+cu113
Is debug build: False
CUDA used to build PyTorch: 11.3
ROCM used to build PyTorch: N/A

OS: Pop!_OS 20.04 LTS (x86_64)
GCC version: (Ubuntu 9.3.0-17ubuntu1~20.04) 9.3.0
Clang version: Could not collect
CMake version: Could not collect
Libc version: glibc-2.31

Python version: 3.8.10 (default, Nov 26 2021, 20:14:08)  [GCC 9.3.0] (64-bit runtime)
Python platform: Linux-5.15.15-76051515-generic-x86_64-with-glibc2.29
Is CUDA available: True
CUDA runtime version: 11.2.67
GPU models and configuration: 
GPU 0: NVIDIA RTX A6000
GPU 1: NVIDIA RTX A6000

Nvidia driver version: 470.86
cuDNN version: Probably one of the following:
/usr/lib/cuda-11.2/targets/x86_64-linux/lib/libcudnn.so.8.1.1
/usr/lib/cuda-11.2/targets/x86_64-linux/lib/libcudnn_adv_infer.so.8.1.1
/usr/lib/cuda-11.2/targets/x86_64-linux/lib/libcudnn_adv_train.so.8.1.1
/usr/lib/cuda-11.2/targets/x86_64-linux/lib/libcudnn_cnn_infer.so.8.1.1
/usr/lib/cuda-11.2/targets/x86_64-linux/lib/libcudnn_cnn_train.so.8.1.1
/usr/lib/cuda-11.2/targets/x86_64-linux/lib/libcudnn_ops_infer.so.8.1.1
/usr/lib/cuda-11.2/targets/x86_64-linux/lib/libcudnn_ops_train.so.8.1.1
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True

Versions of relevant libraries:
[pip3] numpy==1.22.3
[pip3] torch==1.10.2+cu113
[pip3] torchaudio==0.10.2+cu113
[pip3] torchvision==0.11.3+cu113
[conda] Could not collect

```

- PyTorch or Caffe2: PyTorch
- How you installed PyTorch (conda, pip, source): pip
- Build command you used (if compiling from source):
- OS: Pop OS 20.04
- PyTorch version: '1.10.2+cu113'
- Python version: 3.8
- CUDA/cuDNN version: 11.3
- GPU models and configuration: A6000
- GCC version (if compiling from source):
- CMake version:
- Versions of any other relevant libraries:


cc @csarofeen @ptrblck @xwang233 @ngimel
Repository: pytorch
Issue: "histogram_cpu" not implemented for 'Int'
Labels: triaged,module: sorting and selection

### 🐛 Describe the bug

```python
import torch

a=torch.zeros(2, dtype=torch.int, device='cpu')
b=a.histc(bins=2, min=0, max=1)
```
When using the CPU to execute "torch.histc()", an error is generated:
 **RuntimeError: "histogram_cpu" not implemented for 'Int'**


### Versions

Collecting environment information...
PyTorch version: 1.10.1
Is debug build: False
CUDA used to build PyTorch: 11.3
ROCM used to build PyTorch: N/A

OS: Ubuntu 20.04.3 LTS (x86_64)
GCC version: (Ubuntu 9.3.0-17ubuntu1~20.04) 9.3.0
Clang version: Could not collect
CMake version: Could not collect
Libc version: glibc-2.31

Python version: 3.9.9 | packaged by conda-forge | (main, Dec 20 2021, 02:41:03)  [GCC 9.4.0] (64-bit runtime)
Python platform: Linux-4.14.262-200.489.amzn2.x86_64-x86_64-with-glibc2.31
Is CUDA available: False
CUDA runtime version: No CUDA
GPU models and configuration: No CUDA
Nvidia driver version: No CUDA
cuDNN version: No CUDA
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True

Versions of relevant libraries:
[pip3] mypy-extensions==0.4.3
[pip3] numpy==1.22.0
[pip3] torch==1.10.1
[pip3] torchaudio==0.10.1
[pip3] torchvision==0.11.2
[conda] blas                      2.112                       mkl    conda-forge
[conda] blas-devel                3.9.0            12_linux64_mkl    conda-forge
[conda] cudatoolkit               11.3.1               ha36c431_9    conda-forge
[conda] libblas                   3.9.0            12_linux64_mkl    conda-forge
[conda] libcblas                  3.9.0            12_linux64_mkl    conda-forge
[conda] liblapack                 3.9.0            12_linux64_mkl    conda-forge
[conda] liblapacke                3.9.0            12_linux64_mkl    conda-forge
[conda] mkl                       2021.4.0           h8d4b97c_729    conda-forge
[conda] mkl-devel                 2021.4.0           ha770c72_730    conda-forge
[conda] mkl-include               2021.4.0           h8d4b97c_729    conda-forge
[conda] mypy-extensions           0.4.3                    pypi_0    pypi
[conda] numpy                     1.22.0           py39h91f2184_0    conda-forge
[conda] pytorch                   1.10.1          py3.9_cuda11.3_cudnn8.2.0_0    pytorch
[conda] pytorch-mutex             1.0                        cuda    pytorch
[conda] torchaudio                0.10.1               py39_cu113    pytorch
[conda] torchvision               0.11.2               py39_cu113    pytorch
Repository: storybook
Issue: support .eslintrc.json
Labels: bug,compatibility with other tools,cli

**Describe the bug**

running `sb init` and choosing to install the eslint plugin fails when the eslint config is in `.eslintrc.json`.

![Screenshot_20220315_103157](https://user-images.githubusercontent.com/20753323/158348331-e14d0d18-9fe7-4bcd-bd0a-8d4a1aa961d2.png)

also, it does not work at all with a `eslintConfig` field in `package.json`

**To Reproduce**

- `yarn create next-app . && npx sb init`
- choose to install the eslint plugin

**System**

  System:
    OS: Linux 5.13 KDE neon 5.24
    CPU: (4) x64 Intel(R) Core(TM) i5-6400T CPU @ 2.20GHz
  Binaries:
    Node: 16.14.0 - /usr/bin/node
    Yarn: 1.22.17 - /usr/bin/yarn
    npm: 8.3.1 - /usr/bin/npm
  Browsers:
    Chrome: 99.0.4844.51
    Firefox: 98.0
  npmPackages:
    @storybook/addon-actions: ^6.4.19 => 6.4.19 
    @storybook/addon-essentials: ^6.4.19 => 6.4.19 
    @storybook/addon-interactions: ^6.4.19 => 6.4.19 
    @storybook/addon-links: ^6.4.19 => 6.4.19 
    @storybook/react: ^6.4.19 => 6.4.19 
    @storybook/testing-library: ^0.0.9 => 0.0.9 

**Additional context**
Repository: TypeScript
Issue: MSBuild Typescript integration adds elements to the compilation using the full path on Linux
Labels: Bug

# Bug Report

We recently received a bug report in the ASP.NET Core repo ([here](https://github.com/dotnet/aspnetcore/issues/40640)) of a user having issues using Typescript + our JS Modules feature. The user claims that the issue only happens on Linux and upon investigation, it turns out that it seems that Typescript is adding the compilation outputs to the build using the full path instead of the relative path on Linux. 

On windows it exposes the "correct" behavior adding the element to the item group using the relative path, which avoids the issue as the file is not added twice.

The result is that the build is broken in Linux (and possibly Mac OS) when the user tries to use TypeScript + ASP.NET Core.

### 🔎 Search Terms

MSBuild

### 🕗 Version & Regression Information

This is happening with ASP.NET Core .NET 6.0 and "Microsoft.TypeScript.MSBuild" Version="4.6.2"

### 💻 Code

There is a repro attached in the  issue above

### 🙁 Actual behavior

Build fails because an asset is added twice to the build pipeline, in one case with the relative path and in the other with the absolute path, so they are considered different assets.

### 🙂 Expected behavior

Typescript adds the asset with the relative path in all OSes which avoids the asset being accounted twice.
Repository: opencv
Issue: Propose a new retrieval mode
Labels: feature


##### Detailed description

Following the exemple given here https://forum.opencv.org/t/issue-with-precision-of-cv2-findcontours/7947/3 , one can see that cv2.findContours is not able to separate an object and hole that are only one pixel apart. This generate issues when building a label array using the solution given here https://stackoverflow.com/questions/71034691/label-associated-to-findcontour-with-opencv that is then used with skimage.measure.regionprops (for which an issue has been opened here https://github.com/opencv/opencv/issues/21587)

##### Steps to reproduce

As stated by @[crackwitz](https://github.com/crackwitz) the idea would be to propose a retrieval mode that follow the edges of the image instead of the center of the pixel.
Repository: tensorflow
Issue: `tf.strided_slice()` option for `inclusive_end`
Labels: stat:awaiting tensorflower,type:feature,comp:ops

<em>Please make sure that this is a feature request. As per our [GitHub Policy](https://github.com/tensorflow/tensorflow/blob/master/ISSUES.md), we only address code/doc bugs, performance issues, feature requests and build/installation issues on GitHub. tag:feature_template</em>


**System information**
- TensorFlow version (you are using): Latest (2.8)
- Are you willing to contribute it (Yes/No): Yes



**Describe the feature and the current behavior/state.**

I am maintainer of the [R interface to tensorflow](https://github.com/rstudio/tensorflow). The convention in R is for subsetting with `[` to be 1-based, and inclusive of the slice end. In most situations it is trivial to adapt the `[` tensor method in R to Python convention of 0-based indices and a half-open interval. Except for one case: when the slice end is also the first element of the container.

For example,
```
x = [1, 2, 3, 4, 5, 6]
```
An R call like `x[3:1]` would return `[3, 2, 1]`. To translate this to Python, the call would be `x[2::-1]`. This translation is easy enough to do in eager mode, but it's difficult in graph mode if the user supplied the slice end as a tensor, because that would make the dtype of `end` a varient (An integer or `None`, depending on the tensor value at run time).

Wrapping the `end` in a `tf.experimental.Optional()` doesn't work, nor does `tf.strided_slice()` accept a tensor value for `end_mask`. This means that there is no way to faithfully translate an R call like `x[start:end]` if `end` is a tensor and `end` could potentially resolve to the first element of the tensor.


**Will this change the current api? How?**

There are a couple of ways to resolve this, but the simplest I believe is to add an argument with default to `tf.strided_slice(..., inclusive_end=False)`. This would be no breaking change to existing code. From the R interface, we can then call `tf.strided_slice(..., inclusive_end = True)`.

**Who will benefit with this feature?**

All Tensorflow users from R, as well as interfaces to Tensorflow from other languages with 1-based and closed interval slice semantics (e.g., Julia).

**Any Other info.**

Having an additional arg `tf.strided_slice(..., one_based = False)` would be icing on the cake :). Having `tf.strided_slice()` automatically infer when `stride` should be negative would be the cherries on top :)
Repository: storybook
Issue: viewMode won't work in storyStoreV7 properly
Labels: bug,addon: docs

Following snippet is in the preview.js to display the 'docs' tab as default.
```
export const parameters = {
  viewMode: "docs",
};
```
This works like a charm as it should, but as soon as the `storyStoreV7` feature flag is set in the main.js, the viewMode setting seems to be ignored.

[Reproduction Code](https://github.com/Davo911/storybook_storyStoreV7-viewMode_reproduction.git)

Environment Info:
  System:
    OS: Windows 10 10.0.19044
    CPU: (6) x64 Intel(R) Core(TM) i5-8400 CPU @ 2.80GHz
  Binaries:
    Node: 16.14.0 - C:\Program Files\nodejs\node.EXE
    Yarn: 3.2.0 - ~\AppData\Roaming\npm\yarn.CMD
    npm: 8.3.1 - C:\Program Files\nodejs\npm.CMD
  Browsers:
    Edge: Spartan (44.19041.1266.0), Chromium (99.0.1150.36)
Repository: deno
Issue: tools/wpt/expectation.json should support jsonc 
Labels: tests
Repository: neovim
Issue: API function to cancel Visual mode (enhance `interrupt()`?)
Labels: enhancement,api,vimscript,lua,visual-mode



### How to reproduce the issue

On a lua config:

```lua
vim.keymap.set({'v'}, '<space><space>', function()
  print(vim.inspect{
      vim.fn.visualmode(),
      vim.fn.getpos("'<'"),
      vim.fn.getpos("'>'"),
      vim.fn.line('v'),
      vim.fn.col('v')
})
end, { silent = true })
```

Then, on visual selection, run `<space><space>`

### Expected behavior

Inspect result would show correct visual mode as well as correct positions for `getpos` and `col/line` pair.

### Actual behavior

Visual mode is kept, not being able to extract any meaningful values from the visual mode. On the second call to that mapping we can get the first set of values.

Even if force breaking out of visual mode by adding a `vim.api.nvim_input("<ESC>")` line before the inspect function call, it will still show the wrong values, leading me to assume the visual values are set before the keymap is executed.
Repository: flutter
Issue: Use non sparkling m3 ripple in non Android platforms when `useMaterial3` is enabled
Labels: framework,f: material design,team-design,triaged-design

There are 2 implementations of material 3 ripples:

1. Soft edges with sparkles (uses shader)
2. Soft edges no sparkles (no shader)

For non Android platform, useMaterial3 should default to case 2.

blocked by https://github.com/flutter/flutter/issues/100077
Repository: PowerToys
Issue: Keyboard Manager shortcut bindings do not account for key bindings.
Labels: Issue-Bug,Product-Keyboard Shortcut Manager,Status-Reproducible

### Microsoft PowerToys version

0.56.2

### Running as admin

- [X] Yes

### Area(s) with issue?

Keyboard Manager

### Steps to reproduce

Bind a key to another key (such as "Pause" to "Play/Pause Media".)
Bind a shortcut that uses that key. (such as "LShift+Pause" to "Next Track".)
Attempt to use shortcut.

See the [PowerToysReport_2022-03-15-13-51-53.zip](https://github.com/microsoft/PowerToys/files/8256018/PowerToysReport_2022-03-15-13-51-53.zip) for configuration.

### ✔️ Expected Behavior

"Next Track" keypress gets simulated.

### ❌ Actual Behavior

"Play/Pause Media" gets simulated.
Note that binding the shortcut to "Shift+Play/Pause Media" instead of "Shift+Pause" is detected properly and simulates the "Next Track" keypress when using the shortcut.

### Other Software

_No response_
Repository: pytorch
Issue: dir() on torch.ops.aten doesn't work
Labels: triaged,enhancement,tensor subclass

### 🐛 Describe the bug

It would be nice to get a list of all ATen operators by running dir on the module, but this does not work as they are lazily populated.

### Versions

master
Repository: rust
Issue: Type inference on HashSet
Labels: A-diagnostics,A-collections,T-compiler,A-inference

I've recently used HashSet in one of my project and I had to explicitly state the full type when initializing because rust was unable to infer from what I inserted inside. I've replicated the exact problem on a simpler structure on the following playground: https://play.rust-lang.org/?version=stable&mode=debug&edition=2021&gist=ca668a190a8de1e47b5505508b8fe419.

Basically the issue is when an `if let Some(value) = hashset.get(&anitem)` type inference completely falls apart and you must specify `let mut set: HashSet<StructureType> = HashSet::new()`even if you call `set.insert(an_instance_of_structure_type)`.

The unofficial Rust IRC on Libera.chat hints this is a limitation of accessing items of a HashSet before inserting elements inside and is related to the Borrow trait. It does indeed work if the let binding is moved after the calls to `insert`.
Repository: rust
Issue: Tracking issues for unstable language features used by `std`
Labels: metabug,T-lang,T-libs

`std` uses a lot of unstable language features. While `core` will most likely always have to use language features because it defines things that are part of the core of the language, we can strive for `std` to eventually be free of unstable language features.

Some of these we'll need to stabilize, but some others we might be able to simply remove with some small changes to the code.

(See also https://github.com/rust-lang/rust/issues/94971 for the library features used by `std`.)

These are the language features we currently use in `std`: (This does not include `core` or `alloc`.)

- Macro related:
  - [ ] allow_internal_unsafe
  - [ ] allow_internal_unstable
  - [ ] concat_idents
  - [ ] decl_macro
  - [ ] rustc_attrs: rustc_macro_transparency
- Const eval:
  - [ ] const_mut_refs
  - [ ] const_trait_impl
- Panic related:
  - [ ] rustc_attrs: rustc_builtin_macro(std_panic)
  - [ ] lang_items: begin_panic
  - [ ] rustc_attrs: rustc_do_not_const_check
  - [ ] needs_panic_runtime
- Global allocator: (RFC 2492 might be of help here)
  - [ ] alloc_error_handler
  - [ ] allocator_internals
- Diagnostics:
  - [ ] deprecated_suggestion
  - [ ] must_not_suspend
  - [ ] rustc_attrs: rustc_conversion_suggestion
  - [ ] rustc_attrs: rustc_diagnostic_item
  - [ ] rustc_attrs: rustc_insignificant_dtor
  - [ ] rustc_attrs: rustc_lint_query_instability
- Rustdoc:
  - [ ] doc_cfg
  - [ ] doc_cfg_hide
  - [ ] rustdoc_internals
  - [ ] doc_masked
  - [ ] doc_notable_trait
  - [ ] intra_doc_pointers
- Other language features:
  - [ ] lang_items: start
  - [ ] lang_items: termination
  - [ ] lang_items: f32_runtime, f64_runtime
     - Fixed if we move all f32 and f64 methods to core. Libm -> compiler_builtins?
  - [x] associated_type_bounds: https://github.com/rust-lang/rust/pull/95587
  - [x] box_syntax
  - [ ] try_blocks
  - [x] c_unwind: https://github.com/rust-lang/rust/pull/116088
  - [ ] dropck_eyepatch
  - [ ] exhaustive_patterns
  - [ ] linkage
  - [ ] min_specialization
  - [ ] negative_impls
      - We can remove this if we switch to just using `PhantomData` everywhere.
  - [ ] never_type
  - [x] nll
  - [x] platform_intrinsics: https://github.com/rust-lang/rust/pull/121516
  - [ ] prelude_import
  - [ ] staged_api
  - [ ] thread_local
  - [ ] cfg_target_thread_local
  - [ ] rustc_attrs: rustc_std_internal_symbol
  - [ ] rustc_attrs: rustc_specialization_trait
  - [ ] rustc_attrs: rustc_layout_scalar_valid_range_start, rustc_layout_scalar_valid_range_end