sharjeelyunus/github-issues-dataset huggingface dataset:
Repository: flutter
Issue: Ability to change the name of the APK/IPA when building
Labels: c: new feature,platform-android,platform-ios,tool,c: proposal,P3,team-tool,triaged-tool

### Use case

Currently on Android and iOS the default name of the final artifacts is something like:
```
app-release.aab
app-release.apk
Runner.app
MyApp.ipa
```
It's generic and with the name only I can't distinguish the version on where it came from. Specially on "whitelabel" projects, that can generate many artifacts for different clients or modules.

### Proposal

But both Gradle and the Info.plist containg ways to change the name of the final artifact.
I haven't used the one for iOS, but on Android I've used a configuration to change the name to include a variant and version, so the final package would be generated with a name that would make clear which version it is. Like:
```
MyCustomApp-v1.3.2.apk
MyProduct_ClientName_v3.2.1.apk
```

For Android would be something like the below:
```
android {
  tasks.whenTaskAdded {
    val newFileName = "${baseName}_${apkVersionName()}"
    doLast {
      val apkFile = outputs.files.files.last().listFiles().find { it.extension == "apk" }
        ?: throw RuntimeException("APK file not found")
      apkFile.renameTo(File(apkFile.parent, "$newFileName.apk"))
    }
  }
}
```
For iOS I've readed that this are the variables on the Info.plist to change in order to change the name of the final artifact:
```
<key>CFBundleDisplayName</key>
<string>MyApp</string>
<key>CFBundleName</key>
<string>MyApp</string>
```
Repository: flutter
Issue: tech-debt: move `readJsonResults` to utils
Labels: team-infra,P3,c: tech-debt,triaged-infra

This method is used by more than just microbenchmarks. It should be moved.

https://github.com/flutter/flutter/blob/8c1a93508b4ffa813cea0648f0dc85ca5b458de9/dev/devicelab/lib/microbenchmarks.dart#L12
Repository: next.js
Issue: Error: headers was called outside a request scope, when using Authjs v5.0.0-beta.19 and next dev --turbo
Labels: bug,Turbopack

### Link to the code that reproduces this issue

https://github.com/cogb-jclaney/authjs-issue

### To Reproduce

Hi, I'm bringing this issue https://github.com/nextauthjs/next-auth/issues/11076 to here as its related to turbopack.

<img width="972" alt="image" src="https://github.com/user-attachments/assets/a3d1123d-1640-4266-8f2a-ed55632069b0">

### Current vs. Expected behavior

Expected behavior should be to work, as it does when there is no --turbo flag.

### Provide environment information

```bash
Operating System:
  Platform: darwin
  Arch: arm64
  Version: Darwin Kernel Version 23.6.0: Mon Jul 29 21:14:21 PDT 2024; root:xnu-10063.141.2~1/RELEASE_ARM64_T8103
  Available memory (MB): 16384
  Available CPU cores: 8
Binaries:
  Node: 22.0.0
  npm: 10.5.1
  Yarn: 3.6.3
  pnpm: 9.8.0
Relevant Packages:
  next: 14.2.7 // Latest available version is detected (14.2.7).
  eslint-config-next: 14.2.7
  react: 18.3.1
  react-dom: 18.3.1
  typescript: 5.5.4
Next.js Config:
```


### Which area(s) are affected? (Select all that apply)

Turbopack

### Which stage(s) are affected? (Select all that apply)

next dev (local)

### Additional context

_No response_
Repository: transformers
Issue: prune_heads() method for AutoModelForCausalLM
Labels: Feature request

### Feature request

We have `prune_heads()` method for `AutoModel` class, but not for `AutoModelForCausalLM`. Please provide `prune_heads()` method to `AutoModelForCausalLM` class.

### Motivation

Mechanistic interpretability study from the paper [Are Sixteen Heads Really Better than One?](https://arxiv.org/abs/1905.10650) explore how pruning attention heads effect the model's (BERT) performance. I want to do something similar for LLMs. Since LLMs are supported via `AutoModelForCausalLM` class, I am unable to do this experiment.


### Your contribution

Just getting started with HuggingFace. Not confident about implementing this feature on my own as of now.
Repository: deno
Issue: Environment variable for npm auto install
Labels: feat

We should add an environment variable (ex. `DENO_NPM_AUTO_INSTALL=1`) that someone can set to get the Deno 1.x auto-install behaviour for those who like that more.
Repository: flutter
Issue: CI builds for windows desktop can fail if Visual Studio installation is incomplete
Labels: team-infra,P2,triaged-infra

For example: https://ci.chromium.org/ui/p/flutter/builders/try/Windows%20build_tests_1_7/16262/infra

Note:
1. In step 10, we check if Visual Studio is already installed (https://flutter.googlesource.com/recipes/+/663697664d556d1e8725ac6ab2d53dd972b5145d/recipe_modules/os_utils/api.py#837). We are only looking for the version.
2. However, the actual output of vswhere.exe has the field `"isComplete": false` https://logs.chromium.org/logs/flutter/buildbucket/cr-buildbucket/8738150602716059217/+/u/VSBuild/Detect_installation/json.output
3. The tool parses this `isComplete` field and will fail to build a windows app if it is not complete: https://github.com/flutter/flutter/blob/7aace1c5f97f5b433b08468f9712e8c5c29e8e0d/packages/flutter_tools/lib/src/windows/visual_studio.dart#L545
Repository: pytorch
Issue: SyntaxError when Running repro.py
Labels: triaged,oncall: pt2,module: dynamo,module: minifier

### 🐛 Describe the bug

(Might be a duplicate of #128830)

When running a repro.py generated with `TORCHDYNAMO_REPRO_AFTER="aot" TORCHDYNAMO_REPRO_LEVEL=4` on nightly (`2.5.0.dev20240830+cu124`), I run into the following error:

```
    self.fw_graph = <lambda>()
                    ^
SyntaxError: invalid syntax
```

Quite odd! If I had to guess it's because the instability is in the backwards pass. Could also be that it is interacting poorly with Flex Attention.

```
class Repro(torch.nn.Module):
    def __init__(self) -> None:
        super().__init__()
        self.fw_graph = <lambda>()
        self.joint_graph = <lambda>()
        self.mask_graph = <lambda>()
```

### Versions

2.5.0.dev20240830+cu124

cc @ezyang @chauhang @penguinwu @voznesenskym @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @amjames @rec
Repository: rust
Issue: Suboptimal Assembly Output from a Modulo on a Power of Two
Labels: A-LLVM,I-slow,T-compiler,llvm-fixed-upstream,C-optimization

<!--
Thank you for filing a bug report! 🐛 Please provide a short summary of the bug,
along with any information you feel relevant to replicating the bug.
-->

I tried this code:

```rust
#[no_mangle]
pub fn index(key: usize, buckets: usize) -> usize {
    assert!(buckets.is_power_of_two());
    key % buckets
}
```

Since `assert!(buckets.is_power_of_two())` is run (and `.is_power_of_two()` is an inbuilt function), the latter modulus operation should reduce to `key & (buckets - 1)`.

Instead, the outputted assembly [here](https://godbolt.org/z/r8564sEfE) shows that this reduction does not take place.

### Meta
The compiler in the GodBolt link is version 1.80.0.
Repository: next.js
Issue: Import .ts files in Instrumentation
Labels: examples

### Verify canary release

- [X] I verified that the issue exists in the latest Next.js canary release


I can use in my tsconfig.json:
- allowImportingTsExtensions:true

To use:

```javascript
const path = 'test.ts'
await import(path)
```

However, when I will run the same code inside of the Instrumentation I get:
- TypeError [ERR_UNKNOWN_FILE_EXTENSION]: An error occurred while loading instrumentation hook: Unknown file extension ".ts"

Is the Instrumenation not working with the tsconfig.json?


### Expected Behavior

Instrumenation works with dynamic import of .ts files
Repository: godot
Issue: Export MeshLibrary - Apply MeshInstance Transform does not work for GLTF-based Node3D
Labels: bug,topic:editor,topic:import,topic:3d

### Tested versions

- Reproducible in 4.3.stable, 4.2.2

### System information

Godot v4.3.stable - macOS 14.6.1 - Vulkan (Forward+) - integrated Apple M3 Max - Apple M3 Max (16 Threads)

### Issue description

When using Scene -> Export As -> MeshLibrary with `Apply MeshInstance Transforms` enabled, the transform to Node3Ds that are imported from a GLTF are not added to the MeshLibrary.  

Due to the explicit phrasing of "`MeshInstance` Transforms" I believe this is expected behaviour, but it's unexpected behavior from a user perspective.  Tilesets frequently come in GLTF format, and it is very confusing to enable "Apply [...] Transform", but not have it applied to the exported meshes.

I can understand if this is an immediate close bug, but I was unable to find any documentation of this limitation.  Developers should be aware that if they PoC with MeshInstances, switching to GLTF assets later will not work if any transform is needed.

The only workaround I've found is to manually update the MeshLibrary in the editor for the transform.

### Steps to reproduce

* Add GLTF imported scene to a new scene and translate it.
* Export with "Apply MeshInstance Transforms"
* Edit the MeshLibrary and examine the offset fields for the Mesh Transform

Demo:

(Added grass tile from kaykit midevil hexagon pack, and translated it up 1.0)
<img width="1323" alt="Screenshot 2024-08-30 at 6 06 10 PM" src="https://github.com/user-attachments/assets/082036cb-d3cd-459b-95b2-4c215411ea9d">

(Export with "Apply MeshInstance Transforms" enabled)
<img width="1279" alt="Screenshot 2024-08-30 at 6 07 01 PM" src="https://github.com/user-attachments/assets/7d3f0eae-8596-4adb-a05b-7f89bfd79ccf">

(Editing the Mesh in the MeshLibrary, the Mesh Transform has a y offset = 0; it should be 1.0)
<img width="1323" alt="Screenshot 2024-08-30 at 6 07 36 PM" src="https://github.com/user-attachments/assets/f41f3a68-07c9-4588-a7be-1231811efda2">


### Minimal reproduction project (MRP)

[mesh-library-export-apply-transform.zip](https://github.com/user-attachments/files/16822709/mesh-library-export-apply-transform.zip)
Repository: svelte
Issue: TypeError: Cannot read properties of null (reading 'nodeType') (Astro + Svelte 5)
Labels: awaiting submitter

### Describe the bug

I am getting this error and my svelte component will not load at all. It works perfectly fine in dev environment but when I build or run preview it stops working and the error is thrown in the console.

### Reproduction

https://gist.github.com/AdrianButler/4b04009c797bf37599c6763d09111a0b

This component is being used in a astro file with the client directive of load
<FaqQuestion faqEntry={faqEntry} client:load />

This only happens in production build and the component works perfectly fine in dev environment

### Logs

```shell
faq/:1 [astro-island] Error hydrating /_astro/FaqQuestion.B9nkJrIu.js TypeError: Cannot read properties of null (reading 'nodeType')
    at Ut (template.BZob6Wd_.js:1:8993)
    at G (FaqQuestion.B9nkJrIu.js:1:1234)
    at render.Eek01tEQ.js:1:1270
    at Sn (template.BZob6Wd_.js:1:5360)
    at U (template.BZob6Wd_.js:1:6097)
    at k (template.BZob6Wd_.js:1:2186)
    at bt (template.BZob6Wd_.js:1:2805)
    at render.Eek01tEQ.js:1:1212
    at Sn (template.BZob6Wd_.js:1:5360)
    at U (template.BZob6Wd_.js:1:6097)
```


### System Info

```shell
System:
    OS: Windows 11 10.0.22631
    CPU: (24) x64 13th Gen Intel(R) Core(TM) i7-13700K
    Memory: 17.34 GB / 31.77 GB
  Binaries:
    Node: 22.6.0 - ~\AppData\Roaming\JetBrains\WebStorm2024.2\node\versions\22.6.0\node.EXE
    npm: 10.8.2 - ~\AppData\Roaming\JetBrains\WebStorm2024.2\node\versions\22.6.0\npm.CMD
  Browsers:
    Edge: Chromium (127.0.2651.74)
    Internet Explorer: 11.0.22621.3527
```


### Severity

blocking all usage of svelte
Repository: vscode
Issue: [Accessibility] Tooltips under user settings for extensions missing aria attributes.
Labels: bug,accessibility,settings-editor

**Issue**: The "Applies to all profiles" button which opens the tooltip is missing role information and aria-describedby attribute.

**Impact**: Screen reader users will be unable to determine that these tooltips are present.

[Code Reference]
`<span class="setting-item-overrides setting-indicator" tabindex="0" style="display: inline;">Applies to all profiles</span>`

**Steps to repro:**
1. Open VScode Editor
2. Go to User settings -> For any extension setting, check for a tooltip like "Applies to all Profiles"
3. The Accessibility screen reader doesn't announce the presence of a **ToolTip** inside the Toolbar.

For tooltips, the following information is expected:
- The control that opens the tooltip must have aria-describedby set to the ID of the tooltip element.
- The tooltip element must have role="tooltip".

I believe the Tooltip is being rendered by VSCode due to the `Scope` property being added in `contributes.configuration`
Reference: https://code.visualstudio.com/api/references/contribution-points#contributes.configuration

Screenshot of issue:
<img width="1784" alt="Screenshot 2024-09-02 at 9 58 39 PM" src="https://github.com/user-attachments/assets/9b466341-7424-44ed-928c-368824f2959c">
Repository: godot
Issue: Engine.time_scale affects the display of button presses while using shortcuts
Labels: bug,topic:input,topic:gui

### Tested versions

v4.3.stable.official [77dcf97d8] and v4.4.dev1.official [28a72fa43]

### System information

Debian GNU/Linux 12 (bookworm) 12 - X11 - Vulkan (Forward+) - dedicated AMD Radeon RX 470 Graphics (RADV POLARIS10) - AMD Phenom(tm) II X6 1090T Processor (6 Threads)

### Issue description

While switching buttons (toggle mode, in the same button group) with keyboard shortcuts `Engine.time_scale` value affects time between select the new button and unselect the old one. Problem do not occurs while use mouse to activated buttons (but buttons previously activated by shortcuts remain displayed as active).

### Steps to reproduce

`bug.tscn`:

- define 3 toggle buttons in the same button group, 2 with keyboard shortcuts
- set `Engine.time_scale = 0.05` on startup

usage:

0. use mouse to click on buttons → everything works OK
1. use keyboard shortcuts (`a` / `b`) to switch between `AAA` and `BBB` buttons → both buttons will be shown as selected
2. use mouse to select button `CCC` → all buttons will be show as selected
3. use mouse to select button `AAA` → button `AAA` and `BBB` will be show as selected
4. wait some time → only button `AAA` will be show as selected
    - decreasing `Engine.time_scale` value increases this waiting time

### Minimal reproduction project (MRP)

[Archive.zip](https://github.com/user-attachments/files/16822805/Archive.zip)
Repository: terminal
Issue: Add an option to revert to old alpha-based selection colors
Labels: Area-Rendering,Area-Settings,Product-Terminal,Issue-Task

In v1.22, selection colors were changed significantly to make the selection have uniform foreground and background color. However, the new colors are imo hard to read due to excessive contrast and they interact poorly with text with varying background and foreground color (see image 4 and 5). Also, using glyphs to create rounded corners on blocks with different background colors breaks with the new selection behavior (see image 3).

Personally, I much prefer the previous alpha-based selection. Could you add an option to revert to the previous behavior?

v1.21, the pretty alpha-based selection:
![image](https://github.com/user-attachments/assets/6d448502-83a9-4192-a908-1294ca5a2b0d)

v1.22, too much contrast, imo does not look as good:
![image](https://github.com/user-attachments/assets/df5efd53-6a5a-493a-93ad-3f70241767e0)

---

Bad rendering for rounded corners using glyphs:
![image](https://github.com/user-attachments/assets/820cd7e0-a4fc-46a0-ad79-2cc8f9e99ee5)

---

v1.22 hides all background colors:
![image](https://github.com/user-attachments/assets/0e4f91e6-41f0-4191-93ad-f8b20a3c27cf)

v1.21 preserves background colors, which imo looks better:
![image](https://github.com/user-attachments/assets/c0bb3fd9-13fa-4ab6-b27a-8cb8f945bd3e)
Repository: pytorch
Issue: `weight` argument of `nn.CrossEntropyLoss()` works with `int`, `complex` and `bool` type
Labels: module: docs,triaged

### 🐛 Describe the bug

[The doc](https://pytorch.org/docs/stable/generated/torch.nn.CrossEntropyLoss.html) of `nn.CrossEntropyLoss()` says `weight` argument has to be `float` as shown below:

> - weight ([Tensor](https://pytorch.org/docs/stable/tensors.html#torch.Tensor), optional) – a manual rescaling weight given to each class. If given, has to be a Tensor of size C and floating point dtype

But, `weight` argument works with `int`, `complex` and `bool` type as shown below:

```python
import torch
from torch import nn

tensor1 = torch.tensor([5., 3., 8.])
tensor2 = torch.tensor([2., 7., 1.])

cel = nn.CrossEntropyLoss(weight=torch.tensor([0, 1, 2])) # Here
cel(input=tensor1, target=tensor2)
# tensor(35.4949)

cel = nn.CrossEntropyLoss(weight=torch.tensor([0.+0.j, 1.+0.j, 2.+0.j])) # Here
cel(input=tensor1, target=tensor2)
# tensor(35.4949-0.j)

cel = nn.CrossEntropyLoss(weight=torch.tensor([True, False, True])) # Here
cel(input=tensor1, target=tensor2)
# tensor(6.1650)
```

### Versions

```python
import torch

torch.__version__ # 2.4.0+cu121
```

cc @svekars @brycebortree @tstatler
Repository: tensorflow
Issue:  Aborted (core dumped): Check failed: d < dims() (1 vs. 1)
Labels: stat:awaiting tensorflower,type:bug,comp:ops,2.17

### Issue type

Bug

### Have you reproduced the bug with TensorFlow Nightly?

Yes

### Source

source

### TensorFlow version

tf-nightly 2.18.0.dev20240817

### Custom code

Yes

### OS platform and distribution

_No response_

### Mobile device

_No response_

### Python version

_No response_

### Bazel version

_No response_

### GCC/compiler version

_No response_

### CUDA/cuDNN version

_No response_

### GPU model and memory

_No response_

### Current behavior?

I encountered an `aborted issue` in TensorFlow when I used API `array_ops.scatter_nd` . The code is as follows:

```python
import numpy as np
from tensorflow.python.framework import dtypes
from tensorflow.python.ops import array_ops

GRADIENT_TESTS_DTYPES = (dtypes.bfloat16, dtypes.float16, dtypes.float32, dtypes.float64)

def scatter_nd(indices, updates, shape):
    return array_ops.scatter_nd(indices, updates, shape)

def testExtraIndicesDimensions():
    indices = array_ops.zeros((1, 1, 2), dtypes.int32)
    updates = array_ops.zeros([1], dtypes.int32)
    shape = np.array((2, 2))
    scatter = scatter_nd(indices, updates, shape)

testExtraIndicesDimensions()
```

> 2024-08-31 12:17:41.010855: F tensorflow/core/framework/tensor_shape.cc:357] Check failed: d < dims() (1 vs. 1)
> Aborted (core dumped)

### Standalone code to reproduce the issue

```shell
import numpy as np
from tensorflow.python.framework import dtypes
from tensorflow.python.ops import array_ops

GRADIENT_TESTS_DTYPES = (dtypes.bfloat16, dtypes.float16, dtypes.float32, dtypes.float64)

def scatter_nd(indices, updates, shape):
    return array_ops.scatter_nd(indices, updates, shape)

def testExtraIndicesDimensions():
    indices = array_ops.zeros((1, 1, 2), dtypes.int32)
    updates = array_ops.zeros([1], dtypes.int32)
    shape = np.array((2, 2))
    scatter = scatter_nd(indices, updates, shape)

testExtraIndicesDimensions()
```


### Relevant log output

```shell
2024-08-31 12:17:41.010855: F tensorflow/core/framework/tensor_shape.cc:357] Check failed: d < dims() (1 vs. 1)
Aborted (core dumped)
```
I have confirmed that above code would crash on `tf-nightly 2.18.0.dev20240817` (nightly-build)
Repository: tensorflow
Issue: tensorflow.python.ops.state_ops.scatter_nd_update can cause a crash
Labels: stat:awaiting tensorflower,type:support,comp:ops,2.17

### Issue type

Bug

### Have you reproduced the bug with TensorFlow Nightly?

Yes

### Source

source

### TensorFlow version

tf-nightly 2.18.0.dev20240817

### Custom code

Yes

### OS platform and distribution

_No response_

### Mobile device

_No response_

### Python version

_No response_

### Bazel version

_No response_

### GCC/compiler version

_No response_

### CUDA/cuDNN version

_No response_

### GPU model and memory

_No response_

### Current behavior?

I encountered a `Segmentation fault` in TensorFlow when I used API `state_ops.scatter_nd_update`  with empty indices.
I have confirmed that the code would crash on `tf-nightly 2.18.0.dev20240817` (nightly-build)

### Standalone code to reproduce the issue

```shell
import numpy as np

from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.ops import resource_variable_ops
from tensorflow.python.ops import state_ops


def testSimpleResource():
    indices = constant_op.constant([], dtype=dtypes.int32)
    for dtype in (dtypes.int32, dtypes.bfloat16):
        updates = constant_op.constant([], dtype=dtype)
        ref = resource_variable_ops.ResourceVariable((0, 0, 0, 0, 0, 0, 0, 0), dtype=dtype)
        scatter = state_ops.scatter_nd_update(ref, indices, updates)

testSimpleResource()
```


### Relevant log output

```shell
> Segmentation fault (core dumped)
```
Repository: PowerToys
Issue: Rename File Locksmith to File & Folder Locksmith
Labels: Needs-Triage

### Description of the new feature / enhancement

Rename File Locksmith to File & Folder Locksmith.

### Scenario when this would be used?

This would be used to tell that File Locksmith can also unlock folders.

### Supporting information

_No response_
Repository: tensorflow
Issue: tensorflow.python.ops.gen_math_ops.sparse_bincount can cause a crash
Labels: stat:awaiting tensorflower,type:bug,comp:ops,2.17

### Issue type

Bug

### Have you reproduced the bug with TensorFlow Nightly?

Yes

### Source

source

### TensorFlow version

tf-nightly 2.18.0.dev20240817

### Custom code

Yes

### OS platform and distribution

_No response_

### Mobile device

_No response_

### Python version

_No response_

### Bazel version

_No response_

### GCC/compiler version

_No response_

### CUDA/cuDNN version

_No response_

### GPU model and memory

_No response_

### Current behavior?

I encountered a `Segmentation fault ` issue in TensorFlow when using the `gen_math_ops.sparse_bincount` API. I have confirmed that the code would crash on `tf-nightly 2.18.0.dev20240817` (nightly-build)

### Standalone code to reproduce the issue

```shell
from tensorflow.python.ops import gen_math_ops

values = [0, 1, 2, 2]
binary = False
indices = [[], [], [990, 2], [2, 349]]
dense_shape = []
gen_math_ops.sparse_bincount(indices=indices, values=values, dense_shape=dense_shape, size=3, weights=[],binary_output=binary)
```


### Relevant log output

```shell
Segmentation fault (core dumped)
```
Repository: go
Issue: net/http: TestTransportMaxConnsPerHostDialCancellation/h1 failures
Labels: NeedsInvestigation

```
#!watchflakes
default <- pkg == "net/http" && test == "TestTransportMaxConnsPerHostDialCancellation/h1"
```

Issue created automatically to collect these failures.

Example ([log](https://ci.chromium.org/b/8738119239626546913)):

    === RUN   TestTransportMaxConnsPerHostDialCancellation/h1
        transport_test.go:767: expected error context canceled, got <nil>
    --- FAIL: TestTransportMaxConnsPerHostDialCancellation/h1 (0.00s)


— [watchflakes](https://go.dev/wiki/Watchflakes)