sharjeelyunus/github-issues-dataset huggingface dataset:
Repository: material-ui
Issue: Rollup failed to resolve import "@mui/system/RtlProvider"
Labels: status: waiting for author

### Steps to reproduce

Steps:
1. just run npm install


### Current behavior

![Image](https://github.com/user-attachments/assets/8e2ea918-5afd-45f3-b7f5-862dad454653)

### Expected behavior

To succesfully install the package.

### Context

_No response_

### Your environment

<details>
  <summary><code>npx @mui/envinfo</code></summary>

```
  Don't forget to mention which browser you used.
  Output from `npx @mui/envinfo` goes here.
```
</details>



**Search keywords**: Rollup failed to resolve import "@mui/system/RtlProvider"

**Search keywords**:
Repository: deno
Issue: "Move to new file" quickfix does not work for `import * as ...`
Labels: lsp,tsc

Version: Deno 2.1.6

```ts
// main.ts
import * as a from 'data:application/json,{"a":1}' with { type: "json" };
const y = a;
```

When you try to execute the "Move to a new file" quick fix in VS Code in the `main.ts` file, the LSP fails to respond to the `codeAction/resolve` request.

It works if the file referenced from the import does not exist. It fails if it does exist (data url, local file, npm specifier all fail).
Repository: PowerToys
Issue: Make default log base in Run calculator a setting
Labels: Needs-Triage

### Description of the new feature / enhancement

Writing `log(5)` in the PowerToys Run calculator used to calculate the natural logarithm but this was changed following #14687 to instead use base 10. As discussed in that issue, the notation is inherently ambiguous and different users might have different, but very strong, expectations as to what should be the base. Anyone with a math/physics/programming background would surely expect the natural logarithm.

There are now also `log10`, `log2` and `ln`, so the question comes down to which one of these `log` should be an alias for. It would be great if this could be a setting, so users can choose themselves which convention to follow.

### Scenario when this would be used?

Logarithms are common and expectations for the standard base can be strong.

### Supporting information

- [Wikipedia](https://en.wikipedia.org/wiki/Logarithm#Particular_bases) lists `log` as an alias for bases 2, e and 10. (Though I haven't seen base 10 except for in handheld calculators and, by extensions, applications mimicking those.)
- In programming languages, `log` usually refers to the natural logarithm (e.g. [C++](https://cplusplus.com/reference/cmath/log/), [Python](https://docs.python.org/3/library/math.html#math.log)/[numpy](https://numpy.org/doc/stable/reference/generated/numpy.log.html), [JavaScript](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Math/log), [Matlab](https://www.mathworks.com/help/matlab/ref/double.log.html)).
- In those same languages, `log10` and `log2` are present to refer to logarithms of the other common bases, so the presence of those may lead users to expect the same convention to be followed.
- `ln` on the other hand is not usually present. (Its presence may lead users to expect the other ISO notations `lg` and `lb` to also exist, which they don't. Maybe adding those aliases is also worthwhile.)
Repository: react
Issue: Bug: eagerly adding `wheel` events to app root opts into changing input `type="number"` value on scroll
Labels: Status: Unconfirmed

<!--
  Please provide a clear and concise description of what the bug is. Include
  screenshots if needed. Please test using the latest version of the relevant
  React packages to make sure your issue has not already been fixed.
-->

React version: 17+

## Steps To Reproduce

1. Render `<input type="number" defaultValue={0} />`
2. Focus input
3. Scroll mouse wheel over input

<!--
  Your bug will get fixed much faster if we can run your code and it doesn't
  have dependencies other than React. Issues without reproduction steps or
  code examples may be immediately closed as not actionable.
-->

Link to code example: https://stackblitz.com/edit/react-wheel-event-number-input-mouse-wheel?file=src%2Fmain.tsx&terminal=dev

<!--
  Please provide a CodeSandbox (https://codesandbox.io/s/new), a link to a
  repository on GitHub, or provide a minimal code example that reproduces the
  problem. You may provide a screenshot of the application if you think it is
  relevant to your bug report. Here are some tips for providing a minimal
  example: https://stackoverflow.com/help/mcve.
-->

## The current behavior

The value of the input changes when you scroll the mouse wheel over the number input. This behavior is _only_ enabled in browsers if you add a `wheel` event to the input or an ancestor. React eagerly listens for a `wheel` event on the app's root, whether you use one in app code or not. 

Therefore React is forcibly opting you into behavior that is undesirable and error-prone. There is no way to opt out. You must instead add a clunky workaround (that may not even work correctly because the events are passive).

This codepen demonstrates how you get opted into the behavior outside of a React context: https://codepen.io/WickyNilliams/pen/xbKyVQE

## The expected behavior

The input's value should not change on mouse wheel, unless I have added an event listener explicitly. This aligns with actual browser behaviour outside of React
Repository: pytorch
Issue: distributed.new_group with backend GLOO hangs when distributed.split_group was called before
Labels: oncall: distributed

### 🐛 Describe the bug

A call to `distributed.new_group` with backend GLOO hangs if `distributed.split_group` was called before and not all ranks are part of a new ProcessGroup (whether in `new_group` and/or `split_group`).

Reproducer:
```python
#!/usr/bin/env python3
import os
import torch
import torch.distributed as dist

LOCAL_RANK = int(os.getenv("LOCAL_RANK"))
torch.distributed.init_process_group(backend='cpu:gloo,cuda:nccl', device_id=torch.device("cuda", LOCAL_RANK))
WORLD_SIZE = dist.get_world_size()

# hang in v2.5.1 and 2.7.0.dev20250120+cu126.
ranks_split = [ list(range(WORLD_SIZE-1)) ]
ranks_new = list(range(WORLD_SIZE))

# hang in v2.5.1, crash in tear down in 2.7.0.dev20250120+cu126.
# ranks_split = [ list(range(WORLD_SIZE)) ]
# ranks_new = list(range(WORLD_SIZE-1))

# hang in v2.5.1, crash in tear down in 2.7.0.dev20250120+cu126.
# ranks_split = [ list(range(WORLD_SIZE-1)) ]
# ranks_new = list(range(WORLD_SIZE-1))

# works
# ranks_split = [ list(range(WORLD_SIZE)) ]
# ranks_new = list(range(WORLD_SIZE))

dist.split_group(split_ranks=ranks_split)
print("new_group ...")
dist.new_group(ranks=ranks_new, backend=dist.Backend.GLOO) # hang occurs here
print("done")
dist.barrier()
```

Run with: `torchrun --nproc-per-node 2 ./torch-split-group-repro.py`

### Versions

Reproducible with PyTorch 2.5.1 and latest 2.7.0.dev20250120+cu126.

cc @H-Huang @awgu @kwen2501 @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @c-p-i-o
Repository: react-native
Issue: Memory Leak in Animated API
Labels: Issue: Author Provided Repro,API: Animated

### Description

A memory leak has been identified in the Animated API, specifically in the `_children` array within the AnimatedWithChildren class. The issue arises when rendering animated components using transforms and interpolation. Over time, the children array grows indefinitely, leading to increased memory usage and performance degradation. 

The memory leak only exists on web, ios and android don't seem to leak (see snack below). 


### Steps to reproduce

1. Implement a component that periodically renders Animated elements using transform and interpolate, as these trigger the issue more frequently.
2. Monitor performance degradation visually as animations run.
3. Use tools like Chrome DevTools to confirm memory growth over time, by taking heap snapshots.

### React Native Version

0.76.6

### Affected Platforms

Runtime - Web

### Output of `npx react-native info`

```text
info Fetching system and libraries information...
System:
  OS: macOS 15.1.1
  CPU: (10) arm64 Apple M1 Pro
  Memory: 128.17 MB / 16.00 GB
  Shell:
    version: "5.9"
    path: /bin/zsh
Binaries:
  Node:
    version: 18.20.3
    path: ~/.nvm/versions/node/v18.20.3/bin/node
  Yarn:
    version: 1.22.22
    path: ~/.nvm/versions/node/v18.20.3/bin/yarn
  npm:
    version: 10.7.0
    path: ~/.nvm/versions/node/v18.20.3/bin/npm
  Watchman: Not Found
Managers:
  CocoaPods:
    version: 1.16.2
    path: /Users/christophermiles/.asdf/shims/pod
SDKs:
  iOS SDK: Not Found
  Android SDK: Not Found
IDEs:
  Android Studio: Not Found
  Xcode:
    version: /undefined
    path: /usr/bin/xcodebuild
Languages:
  Java: Not Found
  Ruby:
    version: 2.7.2
    path: /Users/christophermiles/.asdf/shims/ruby
npmPackages:
  "@react-native-community/cli":
    installed: 15.1.3
    wanted: ^15.1.3
  react:
    installed: 18.3.1
    wanted: 18.3.1
  react-native:
    installed: 0.76.6
    wanted: 0.76.6
  react-native-macos: Not Found
npmGlobalPackages:
  "*react-native*": Not Found
Android:
  hermesEnabled: Not found
  newArchEnabled: Not found
iOS:
  hermesEnabled: Not found
  newArchEnabled: Not found

info React Native v0.77.0 is now available (your project is running on v0.76.6).
info Changelog: https://github.com/facebook/react-native/releases/tag/v0.77.0
info Diff: https://react-native-community.github.io/upgrade-helper/?from=0.76.6&to=0.77.0
info For more info, check out "https://reactnative.dev/docs/upgrading?os=macos".
```

### Stacktrace or Logs

```text
See memory and heap snapshots in screenshots below.
```

### Reproducer

https://snack.expo.dev/@miles121/smelly-blue-croissant

### Screenshots and Videos



<img width="600" alt="Image" src="https://github.com/user-attachments/assets/0031d466-6e6c-42cf-bc60-1a6af71e57ab" />

<br>

<img width="600" alt="Image" src="https://github.com/user-attachments/assets/07032ec0-a0ac-4e54-a5ae-da33e1ef970c" />
Repository: ui
Issue: [bug]: Error adding shadcn for Turborepo
Labels: bug

### Describe the bug

Unable to add shadcn using turborepo.

`npx shadcn@canary init`

 ✔ Preflight checks.
✖ Verifying framework.

We could not detect a supported framework at /app-name.
Visit https://ui.shadcn.com/docs/installation/manual to manually configure your project.
Once configured, you can use the cli to add components.

### Affected component/components

Not installing

### How to reproduce

1. Create monorepo using turborepo
2. Run shadcn/ui CLI to add for monorepo

### Codesandbox/StackBlitz link

_No response_

### Logs

```bash

```

### System Info

```bash
System, pnpm
```

### Before submitting

- [x] I've made research efforts and searched the documentation
- [x] I've searched for existing issues
Repository: electron
Issue: [Bug] unable to get `context-menu` event when using `-webkit-app-region: drag`
Labels: platform/linux,component/menu,bug :beetle:,has-repro-gist,32-x-y,33-x-y,34-x-y

### Preflight Checklist

- [x] I have read the [Contributing Guidelines](https://github.com/electron/electron/blob/main/CONTRIBUTING.md) for this project.
- [x] I agree to follow the [Code of Conduct](https://github.com/electron/electron/blob/main/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 bug report that matches the one I want to file, without success.

### Electron Version

32.2.7

### What operating system(s) are you using?

Linux

### Operating System Version

Ubuntu 22.0.4

### What arch are you using?

arm64 (including Apple Silicon)

### Last Known Working Electron version

Was probably never supported on Linux.

### Expected Behavior

An element with `-webkit-app-region: drag` should still receive context menu events.

### Actual Behavior

No `context-menu` event fires.

### Testcase Gist URL

https://gist.github.com/bpasero/b04271deaacf0e099b0a0fa2289e8d28

### Additional Information

//cc @codebytere @deepak1556
Repository: kubernetes
Issue: [Flaking Test][sig-node] Container Runtime blackbox test on terminated container should report termination message from file when pod succeeds and TerminationMessagePolicy FallbackToLogsOnError is set [NodeConformance] [Conformance]
Labels: sig/node,kind/flake,triage/accepted

### Which jobs are flaking?

master-blocking
- gce-ubuntu-master-containerd

### Which tests are flaking?

E2eNode Suite.[It] [sig-node] Container Runtime blackbox test on terminated container should report termination message from file when pod succeeds and TerminationMessagePolicy FallbackToLogsOnError is set [NodeConformance] [Conformance]

[Prow](https://prow.k8s.io/view/gs/kubernetes-ci-logs/logs/ci-crio-cgroupv1-node-e2e-conformance/1881671364948004864)
[Triage](https://storage.googleapis.com/k8s-triage/index.html?test=Container%20Runtime%20blackbox%20test%20on%20terminated%20container%20should%20report%20termination%20message%20from%20file%20when%20pod%20succeeds%20and%20TerminationMessagePolicy%20FallbackToLogsOnError%20is%20set)

### Since when has it been flaking?

[1/10/2025, 6:57:34 PM](https://prow.k8s.io/view/gs/kubernetes-ci-logs/logs/ci-crio-cgroupv1-node-e2e-conformance/1877882125122801664)
[1/21/2025, 5:54:07 AM](https://prow.k8s.io/view/gs/kubernetes-ci-logs/logs/ci-crio-cgroupv1-node-e2e-conformance/1881671364948004864)

### Testgrid link

https://testgrid.k8s.io/sig-release-master-blocking#ci-crio-cgroupv1-node-e2e-conformance

### Reason for failure (if possible)

```
{ failed [FAILED] Timed out after 300.001s.
Expected
    <v1.PodPhase>: Failed
to equal
    <v1.PodPhase>: Succeeded
In [It] at: k8s.io/kubernetes/test/e2e/common/node/runtime.go:157 @ 01/21/25 12:18:04.935
}
```

### Anything else we need to know?

N/A

### Relevant SIG(s)

/sig node
cc @kubernetes/release-team-release-signal
Repository: PowerToys
Issue: Enhanced Functionality of "Always on Top" with Transparency
Labels: Needs-Triage

### Description of the new feature / enhancement

Allow the user to apply opacity to a window that has the Always on top feature applied to. 
Customizable settings allowing specifc apps/windows to be effected differently or not at all. 


### Scenario when this would be used?

### Enhanced Functionality of "Always on Top" with Transparency

#### **Improved Multitasking Efficiency**
- **Reference Without Obstruction:** Overlay a window (e.g., calculator or reference document) while interacting with content underneath, ideal for single-display setups.  
- **Streamlined Workflows:** Designers, coders, and content creators can use transparent overlays to reference designs or follow guidelines without interrupting their workflow.  

#### **Space Optimization for Single-Display Setups**
- **Eliminates Resizing Hassles:** Maintain workspace layouts without rearranging or resizing windows.  
- **Facilitates Full-Screen Applications:** Overlay transparent windows on full-screen apps like video editing software, gaming dashboards, or virtual meeting platforms.  

#### **Better Accessibility for Cross-Referencing**
- **Educational Use Cases:** Keep tutorials or training videos visible while working in a secondary window.  
- **Live Monitoring:** Use overlays for live logs, error messages, or monitoring tools while maintaining primary workspace access.  

#### **Enhanced Visual Collaboration**
- **Design Adjustments:** Overlay grids, palettes, or guides directly on projects without obstructing the main canvas.  
- **Code and Debugging:** Debug efficiently with overlaid snippets or API documentation.  

#### **Improved Workflow for Content Creators**
- **Streaming and Recording:** Keep chat, analytics, or timers visible without obstructing broadcast content.  
- **Video Editing and Review:** Overlay subtitles or notes during playback for real-time adjustments.  

#### **Broader Accessibility for Niche Use Cases**
- **Data Entry and Forms:** Reference documents seamlessly during repetitive tasks like manual data entry.  
- **Medical and Technical Applications:** Overlay scans or schematics for cross-referencing while inputting notes or edits.  

#### **Customization and User Experience**
- **User-Controlled Transparency Levels:** Adjustable transparency allows users to balance visibility with unobstructed workflows.  
- **Consistency in UI/UX:** Aligns with modern design principles, offering flexibility for diverse workflows.  

#### **Potential Limitations Addressed**
- **Avoids Screen Clutter:** Transparency reduces clutter from overlapping opaque windows, ensuring an organized display.  
- **Minimizes Disruptions:** Keeps full-screen content visible and reduces window switching or resizing needs.



### Supporting information

_No response_
Repository: langchain
Issue: PERF: Langchain imports stat too many files causing 12 second import time
Labels: Ɑ:  core

### Checked other resources

- [x] I added a very descriptive title to this issue.
- [x] I searched the LangChain documentation with the integrated search.
- [x] I used the GitHub search to find a similar question and didn't find it.
- [x] I am sure that this is a bug in LangChain rather than my code.
- [x] The bug is not resolved by updating to the latest stable version of LangChain (or the specific integration package).

### Example Code

Here's the stats for a single import:

```python
import cProfile
import pstats
cProfile.run("from langchain_core.documents import Document", "langchainImport")
p = pstats.Stats("langchainImport")
```
output:
```
   ncalls  tottime  percall  cumtime  percall filename:lineno(function)
     2227    1.461    0.001    1.461    0.001 {built-in method posix.stat}
      520    0.624    0.001    0.624    0.001 {built-in method io.open_code}
      520    0.234    0.000    0.234    0.000 {method 'read' of '_io.BufferedReader' objects}
      549    0.183    0.000    0.183    0.000 {method '__exit__' of '_io._IOBase' objects}
    37/34    0.115    0.003    0.124    0.004 {built-in method _imp.create_dynamic}
```

As you can see this import calls `posix.stat` `2227` times causing the import to take 1.4 seconds to complete.

Other langchain imports have similarly egregious results revolving around `posix.stat`

What's causing all these file IO operations? Is there any way for them to be deferred or removed to improve performance?

### Error Message and Stack Trace (if applicable)

_No response_

### Description

I'm expecting imports to take under 100ms

### System Info

```
System Information
------------------
> OS:  Linux
> OS Version:  #1 SMP Thu Oct 5 21:02:42 UTC 2023
> Python Version:  3.10.12 | packaged by conda-forge | (main, Jun 23 2023, 22:40:32) [GCC 12.3.0]

Package Information
-------------------
> langchain_core: 0.3.31
> langchain: 0.3.15
> langchain_community: 0.3.15
> langsmith: 0.3.0
> langchain_openai: 0.3.1
> langchain_text_splitters: 0.3.5
> langchainhub: 0.1.21
> langgraph_sdk: 0.1.51

Optional packages not installed
-------------------------------
> langserve

Other Dependencies
------------------
> aiohttp: 3.11.11
> async-timeout: 4.0.3
> dataclasses-json: 0.6.7
> httpx: 0.28.1
> httpx-sse: 0.4.0
> jsonpatch: 1.33
> langsmith-pyo3: Installed. No version info available.
> numpy: 1.26.4
> openai: 1.60.0
> orjson: 3.10.14
> packaging: 24.2
> pydantic: 2.10.5
> pydantic-settings: 2.7.1
> pytest: 8.3.4
> PyYAML: 6.0.2
> requests: 2.32.3
> requests-toolbelt: 1.0.0
> rich: 13.9.4
> SQLAlchemy: 2.0.37
> tenacity: 9.0.0
> tiktoken: 0.8.0
> types-requests: 2.32.0.20241016
> typing-extensions: 4.12.2
> zstandard: 0.23.0
```
Repository: vscode
Issue: very many error
Labels: info-needed


Type: <b>Bug</b>

very many error

VS Code version: Code 1.96.4 (cd4ee3b1c348a13bafd8f9ad8060705f6d4b9cba, 2025-01-16T00:16:19.038Z)
OS version: Windows_NT x64 10.0.19045
Modes:

<details>
<summary>System Info</summary>

|Item|Value|
|---|---|
|CPUs|Intel(R) Core(TM) i5-7300U CPU @ 2.60GHz (4 x 2712)|
|GPU Status|2d_canvas: enabled<br>canvas_oop_rasterization: enabled_on<br>direct_rendering_display_compositor: disabled_off_ok<br>gpu_compositing: enabled<br>multiple_raster_threads: enabled_on<br>opengl: enabled_on<br>rasterization: enabled<br>raw_draw: disabled_off_ok<br>skia_graphite: disabled_off<br>video_decode: enabled<br>video_encode: enabled<br>vulkan: disabled_off<br>webgl: enabled<br>webgl2: enabled<br>webgpu: enabled<br>webnn: disabled_off|
|Load (avg)|undefined|
|Memory (System)|15.88GB (9.27GB free)|
|Process Argv|--crash-reporter-id 4391a7a7-6178-4b86-b201-49cde4eb170e|
|Screen Reader|no|
|VM|0%|
</details><details><summary>Extensions (4)</summary>

Extension|Author (truncated)|Version
---|---|---
copilot|Git|1.257.0
copilot-chat|Git|0.23.2
remote-wsl|ms-|0.88.5
powershell|ms-|2025.0.0


</details><details>
<summary>A/B Experiments</summary>

```
vsliv368:30146709
vspor879:30202332
vspor708:30202333
vspor363:30204092
vscod805:30301674
binariesv615:30325510
vsaa593cf:30376535
py29gd2263:31024239
c4g48928:30535728
azure-dev_surveyonecf:30548226
vscrp:30673768
a9j8j154:30646983
962ge761:30959799
pythonnoceb:30805159
pythonmypyd1:30879173
h48ei257:31000450
pythontbext0:30879054
cppperfnew:31000557
dsvsc020:30976470
pythonait:31006305
dsvsc021:30996838
dvdeprecation:31068756
dwnewjupyter:31046869
nativerepl2:31139839
pythonrstrctxt:31112756
nativeloc1:31192215
cf971741:31144450
iacca1:31171482
notype1cf:31157160
5fd0e150:31155592
dwcopilot:31170013
stablechunks:31184530
cf1a2727:31215809
6074i472:31201624
dwoutputs:31217127
9064b325:31222308
copilot_t_ci:31222730

```

</details>

<!-- generated by issue reporter -->
Repository: pytorch
Issue: torch.logit works incorrectly when input < eps after torch.compile
Labels: triaged,bug,oncall: pt2,module: decompositions,module: aotdispatch,module: pt2-dispatcher

### 🐛 Describe the bug

According to the doc https://pytorch.org/docs/stable/special.html#torch.special.logit, when input < eps, the actual computation is: `ln(eps/(1-eps))`. But this is not what `torch.compile` (with inductor backend) does.

```python
import torch

input = torch.tensor(0.3, dtype=torch.float64)
eps = torch.tensor(0.9, dtype=torch.float64)
compiled = torch.compile(torch.logit)
print(f"compiled: {compiled(input, eps)}")
print(f"expected: {torch.log(eps / (1 - eps))}")

```

```
compiled: -2.1972245773362196
expected: 2.1972245773362196
```

When using `aot_eager` to compile `torch.logit`, the compiled API's result is expected. So I think the issue lies in the inductor backend.

### Error logs

```
compiled: -2.1972245773362196
expected: 2.1972245773362196
```


### Versions

[pip3] numpy==1.26.2
[pip3] nvidia-cublas-cu12==12.4.5.8
[pip3] nvidia-cuda-cupti-cu12==12.4.127
[pip3] nvidia-cuda-nvrtc-cu12==12.4.127
[pip3] nvidia-cuda-runtime-cu12==12.4.127
[pip3] nvidia-cudnn-cu12==9.1.0.70
[pip3] nvidia-cufft-cu12==11.2.1.3
[pip3] nvidia-curand-cu12==10.3.5.147
[pip3] nvidia-cusolver-cu12==11.6.1.9
[pip3] nvidia-cusparse-cu12==12.3.1.170
[pip3] nvidia-nccl-cu12==2.21.5
[pip3] nvidia-nvjitlink-cu12==12.4.127
[pip3] nvidia-nvtx-cu12==12.4.127
[pip3] optree==0.13.1
[pip3] torch==2.5.1
[pip3] triton==3.1.0
[conda] numpy 1.26.2 pypi_0 pypi
[conda] nvidia-cublas-cu12 12.4.5.8 pypi_0 pypi
[conda] nvidia-cuda-cupti-cu12 12.4.127 pypi_0 pypi
[conda] nvidia-cuda-nvrtc-cu12 12.4.127 pypi_0 pypi
[conda] nvidia-cuda-runtime-cu12 12.4.127 pypi_0 pypi
[conda] nvidia-cudnn-cu12 9.1.0.70 pypi_0 pypi
[conda] nvidia-cufft-cu12 11.2.1.3 pypi_0 pypi
[conda] nvidia-curand-cu12 10.3.5.147 pypi_0 pypi
[conda] nvidia-cusolver-cu12 11.6.1.9 pypi_0 pypi
[conda] nvidia-cusparse-cu12 12.3.1.170 pypi_0 pypi
[conda] nvidia-nccl-cu12 2.21.5 pypi_0 pypi
[conda] nvidia-nvjitlink-cu12 12.4.127 pypi_0 pypi
[conda] nvidia-nvtx-cu12 12.4.127 pypi_0 pypi
[conda] optree 0.13.1 pypi_0 pypi
[conda] torch 2.5.1 pypi_0 pypi
[conda] triton 3.1.0 pypi_0 pypi

cc @chauhang @penguinwu @SherlockNoMad @zou3519 @bdhirsh @yf225
Repository: kubernetes
Issue: prober_probe_total stability
Labels: sig/instrumentation,triage/accepted

The `prober_probe_total` has been marked as Alpha since 3a5091779523a02278ad1ea334df7119ab4b2e5f (part of 1.16). Is it intended to be promoted or removed?