sharjeelyunus/github-issues-dataset huggingface dataset:
Repository: pytorch
Issue: libpytorch_jni is not provided in conda builds
Labels: module: build,triaged

## 🐛 Bug

<!-- A clear and concise description of what the bug is. -->

## To Reproduce

Steps to reproduce the behavior:

1. `conda create -n tmp -y python=3.6`
1. `conda install -c pytorch pytorch -y`
1. `find "$CONDA_PREFIX" -name "libpytorch_jni.*"`

## Expected behavior

The conda artifact should include `libpytorch_jni`.

## Environment

Please copy and paste the output from our
[environment collection script](https://raw.githubusercontent.com/pytorch/pytorch/master/torch/utils/collect_env.py)
(or fill out the checklist below manually).

You can get the script and run it with:
```
wget https://raw.githubusercontent.com/pytorch/pytorch/master/torch/utils/collect_env.py
# For security purposes, please check the contents of collect_env.py before running it.
python collect_env.py
```

PyTorch version: 1.6.0
Is debug build: No
CUDA used to build PyTorch: None

OS: Mac OSX 10.15.6
GCC version: Could not collect
CMake version: version 3.14.0

Python version: 3.6
Is CUDA available: No
CUDA runtime version: No CUDA
GPU models and configuration: No CUDA
Nvidia driver version: No CUDA
cuDNN version: No CUDA

Versions of relevant libraries:
[pip3] numpy==1.18.5
[pip3] torch==1.6.0
[conda] blas                      1.0                         mkl
[conda] mkl                       2019.4                      233
[conda] mkl-service               2.3.0            py36hfbe908c_0
[conda] mkl_fft                   1.1.0            py36hc64f4ea_0
[conda] mkl_random                1.1.1            py36h959d312_0
[conda] numpy                     1.18.5           py36h55a193a_0
[conda] numpy-base                1.18.5           py36h3304bdc_0
[conda] pytorch                   1.6.0                   py3.6_0    pytorch

## Additional context

`libpytorch_jni` is available through download of libtorch from pytorch.org, but the documentation is wrong for some platforms (e.g., at least OS X).

cc @malfet
Repository: pytorch
Issue: Stop implementing JIT stack as a std::vector
Labels: oncall: jit,triaged,weeks

@zou3519 in https://github.com/pytorch/pytorch/pull/41943 reported an unexpected interaction, where references to value on the stack (which had not been popped) because invalidated when he pushed further arguments on the stack. The reason for this is, of course, that when pushing new arguments onto the stack, it triggered a reallocation, which forced ALL of the elements on the stack to get moved.

std::vector is a bad data structure for implementing a "stack" in the PL sense:

* You can't safely take reference to live arguments on the stack, because they might get moved when you push more arguments on the stack
* The capacity of a vector never decreases (unless you call, e.g, `resize_to_fit`) which means that you'll always use up as much space as the high watermark of memory usage

A different data structure, e.g., a linked list of stack chunks, would probably be better and safer to work with.

cc @suo @gmagogsfm
Repository: pytorch
Issue: RFC: torch.vmap
Labels: triaged,module: vmap

TL;DR: We’re implementing a prototype torch.vmap (inspired by jax.vmap) for PyTorch and are looking for early adopters! Please go to https://github.com/pytorch/functorch and follow installation instructions there.

JAX provides jax.vmap, a program transformation that automatically “vectorizes” a function. What this means is that it parallelizes a function over some dimension of the inputs. jax.vmap can potentially do the following:

* Automatically batch certain models (#830). vmap can help users forget about the batch dimension, enabling a simpler model authoring experience.
* Efficiently compute batched gradients (#8304, #23475). vmap can speed up things like full Jacobian/Hessian matrix computation.
* Efficiently compute per-sample-gradients (#7786).
* And more (see [jax’s README](https://github.com/google/jax#auto-vectorization-with-vmap))

Given the popularity of JAX, we’re implementing a prototype of vmap in PyTorch to see how well it applies to PyTorch use cases. Because the torch.vmap project is in early stages and requires some investment, we’d love to hear from and work directly with early adopters to shape the initial direction.

[UPDATE 11/12/21]
Are you running PyTorch 1.10 and want to use this? See installation instructions at https://github.com/pytorch/functorch

[UPDATE 5/5/21]
 We have a working prototype of this (JAX-like composable vmap + grad for PyTorch) and it currently lives out-of-tree at https://github.com/pytorch/functorch.

We’re very interested in supporting your use cases to build out and validate the prototype! If you’re not already in contact with us, please open an issue at https://github.com/facebookresearch/functorch if you’re interested in using the prototype. You can also try it out via pip install --user "git+https://github.com/pytorch/functorch.git"

Alternatively, please:
- post in the [channel for functorch users](https://app.slack.com/client/T2077MDKQ/C02DVE5MAFR) if you're on the PyTorch slack
- or reach out directly to me, on the PyTorch Slack channel or via email (my github username @gmail.com) if you’d be interested in using torch.vmap for your project.
Repository: go
Issue: x/tools/gopls: story for custom codelens providers
Labels: FeatureRequest,gopls,Tools

`gopls` started to offer [test/benchmark codelenses](https://github.com/golang/go/issues/36787)
for test and benchmark functions that work with the `testing` package.

The VS Code Go extension that has offered this feature for a while in its own way received multiple
feature requests to support various testing frameworks (e.g. `gocheck`, `ginkgo`, `testify`, ...)
and we expect to get more as more custom testing frameworks show up.

Current VS Code Go's plan is to export necessary symbol information to other extensions, so
these feature requests can be implemented as separate extensions. 

However, I think it is more desirable for long term if this type of feature extension works more closely
with `gopls`. That will allow other editors to benefit from the work, and also more go developers
can contribute.

This is also related to the question of how to support various linters, custom diagnostics providers.
(I couldn't find an open issue about custom linter support yet)
Repository: PowerToys
Issue: [Colour Picker] Allow to zoom with touchpad two finger gesture
Labels: Idea-Enhancement,Product-Color Picker

## 📝 Provide a description of the new feature

It's not possible to use two finger gesture on touchpad to zoom in colour picker.
Please add this feature.

---

If you'd like to see this feature implemented, add a 👍 reaction to this post.
Repository: kubernetes
Issue: test/integration/master package tests are slow, package times out
Labels: kind/bug,priority/important-soon,kind/flake,sig/auth,help wanted,lifecycle/frozen,needs-triage

**Which jobs are flaking**:

pull-kubernetes-integration

**Which test(s) are flaking**:

test/integration/master

**Testgrid link**:

**Reason for failure**:

There are ~5 tests that average more than 30 seconds each.

https://testgrid.k8s.io/presubmits-kubernetes-blocking#pull-kubernetes-integration&graph-metrics=test-duration-minutes&include-filter-by-regex=k8s.io/kubernetes/test/integration/master&exclude-filter-by-regex=%5C%5B1%5C%5D

This is an umbrella issue tracking speeding up these five tests:

- [x] k8s.io/kubernetes/test/integration/master.TestReconcilerMasterLease{MultiMoreMasters,MultiCombined,Combined} - @gitlawr - https://github.com/kubernetes/kubernetes/pull/93721
- [x] k8s.io/kubernetes/test/integration/master.TestAudit - @vareti - https://github.com/kubernetes/kubernetes/pull/94054 
    * suggestion/starting point: rather than setting up a new server and webhook for each iteration, we can set up a single server with a policy that logs differently named configmaps at different verbosity levels (using the resourceNames portion of the audit policy), and a webhook that only intercepts specifically labeled configmaps (using the objectSelector portion of the webhook).
    * Then all the iterations in the table test can run against the same server and webhook, selecting a different configmap name depending on what verbosity we want to exercise, and setting different labels on the configmap depending on whether we want the mutating webhook to intercept it or not.
- [ ] k8s.io/kubernetes/test/integration/master.TestKMSHealthz - needs an owner

**Anything else we need to know**:

https://storage.googleapis.com/k8s-gubernator/triage/index.html?pr=1&text=FAIL%09k8s.io%2Fkubernetes%2Ftest%2Fintegration%2Fmaster

/sig api-machinery
/priority important-soon
Repository: go
Issue: runtime: merge workarounds to false deadlocks
Labels: NeedsFix,compiler/runtime

In #40368, I avoided false deadlocks from `startm` in `sysmon` by reserving M ids in advance to make it look like the new M is already running to `checkdead`.

Later, I discovered that @dvyukov fixed a nearly identical issue in #6070 by temporarily decrementing the number of idle locked M's, to make checkdead see an extra M. Slightly different approach, but same end result.

We should merge these two approaches back to one just to keep things simpler and easier to understand.

cc @aclements @mknyszek @ianlancetaylor
Repository: PowerToys
Issue: Animated GIF thumbnails/icons in windows explorer.
Labels: Idea-New PowerToy,Product-File Explorer

With a toggleable option, GIFs that normally show up as an image preview in explorer would be animated.

A nice touch would be to specify the quality of the preview, the framerate, and an option to only animate it if it is selected in windows explorer.

This would not be in the preview area, this would be the actual icon or thumbnail of the icon that is animated.
Repository: rust
Issue: Tracking Issue for slice::array_chunks
Labels: T-libs-api,C-tracking-issue,A-const-generics,A-slice,Libs-Tracked,F-generic_const_exprs,A-array

The feature gate for the issue is `#![feature(array_chunks)]`.

Also tracks `as_(r)chunks(_mut)` in `#![feature(slice_as_chunks)]`.

### About tracking issues

Tracking issues are used to record the overall progress of implementation.
They are also uses as hubs connecting to other relevant issues, e.g., bugs or open design questions.
A tracking issue is however *not* meant for large scale discussion, questions, or bug reports about a feature.
Instead, open a dedicated issue for the specific matter and add the relevant feature gate label.

### Steps

- [ ] ~~Restrict `N` to values greater than 0 at compile time instead of using a runtime panic.~~ https://github.com/rust-lang/rust/pull/99471
- [ ] Support calls where `N == 0` is unreachable due to conditionals https://github.com/rust-lang/rust/issues/74985#issuecomment-2087722186
- [ ] Adjust documentation ([see instructions on rustc-dev-guide][doc-guide])
- [ ] Stabilization PR ([see instructions on rustc-dev-guide][stabilization-guide])

[stabilization-guide]: https://rustc-dev-guide.rust-lang.org/stabilization_guide.html#stabilization-pr
[doc-guide]: https://rustc-dev-guide.rust-lang.org/stabilization_guide.html#documentation-prs

### Unresolved Questions

- [ ] Iterator vs slices, https://github.com/rust-lang/rust/issues/76354

### Implementation history

- implemented in #74373
- mut version in #75021
- `as_chunks{_mut}` in #76635
- `as_rchunks{_mut}` and unchecked versions in #78818
- const `as_(r)chunk` in #111453
Repository: pytorch
Issue: TensorBoard Summaries Written with `SummaryWriter.add_scalars()` are not Purged 
Labels: module: tensorboard,oncall: visualization

## 🐛 Bug

When writing TensorBoard summaries, `SummaryWriter` does not purge summaries written with `SummaryWritter.add_scalars()`. However, summaries written with `SummaryWriter.add_scalar()` are purged correctly.

## To Reproduce

Steps to reproduce the behavior:

1. Save metrics using `SummaryWriter.add_scalars()`.
1. Save metrics using `SummaryWriter.add_scalar()`.
1. Create a new `SummaryWriter` with the same `log_dir` and set `purge_step` to a step lower than the last written `global_step`.
1. Observe that summaries written with `SummaryWriter.add_scalars()` are not purged correctly but those written with `SummaryWriter.add_scalar()` are.

## Expected behavior

All summaries should be purged.

## Environment

Collecting environment information...
PyTorch version: 1.5.1
Is debug build: No
CUDA used to build PyTorch: None

OS: Mac OSX 10.15.5
GCC version: Could not collect
CMake version: Could not collect

Python version: 3.7
Is CUDA available: No
CUDA runtime version: No CUDA
GPU models and configuration: No CUDA
Nvidia driver version: No CUDA
cuDNN version: No CUDA

Versions of relevant libraries:
[pip] 20.1.1
[conda] Could not collect

## Additional context

<!-- Add any other context about the problem here. -->
Repository: PowerToys
Issue: [Run] Touchpad scrolling is too sensitive
Labels: Issue-Bug,Product-PowerToys Run,External Dependency,Area-User Interface,Status-Blocked

<!--
**Important: When reporting BSODs or security issues, DO NOT attach memory dumps, logs, or traces to Github issues**.
Instead, send dumps/traces to secure@microsoft.com, referencing this GitHub issue.
-->

## ℹ Computer information

- Windows build number: 19042.421
- PowerToys version: 0.20.0
- PowerToy module: Run

## 📝 Provide detailed reproduction steps (if any)

1. open pt run on a laptop
2. input a character to show a big list
3. scroll with the touchpad
### ✔️ Expected result

smooth scrolling that obeys windows scrolling speed settings

### ❌ Actual result

way too sensitive scrolling (can scroll to the bottom of the list with just a few millimeters of movement on the touch pad)

## 📷 Screenshots
Repository: flutter
Issue: adding textDirection property to ThemeData class
Labels: c: new feature,framework,f: material design,a: typography,team-design,triaged-design

shouldn't `textDirection` be added to `ThemeData` so we can just change it once and not in every single `Text` widget, i know about the [Directionality](https://api.flutter.dev/flutter/widgets/Directionality-class.html) widget but it doesn't work like `textDirection` property inside the `Text` widget.
Repository: go
Issue: x/tools/gopls: unexpected line/character calculations in certain diagnostics
Labels: gopls,Tools,gopls/parsing

#### What did you do?

I've run into a situation where gopls was consistently returning a diagnostic with range data that was inconsistent with the editor state. Critically, it was producing a range with a character that was past the end of the line.

While I uncovered the issue interacting with gopls via the LSP interface, it appears to exhibit the behavior on the command line as well. Here's the code that reproduces the issue for me:

```
package main

func testFunc() error {
	releases := []int{1, 2, 3}

	for _, _ := range releases {
		if ;
	}

	return nil
}

func main() {
	testFunc()
}
```

#### What did you expect to see?

The line at issue, which has an intentional error, is the `if ;`. When running gopls from the command line, I get the following (expected) output:

`file.go:8:2: expected operand, found '}'`

*However* if I exchange that offending semi-colon for an `r` character, I get the following unexpected, and possibly incorrect, output:

`file.m:7:7: expected operand, found '}'`

Not only is the line change surprising, the character offset is past the end of the line.

#### What did you see instead?

I would have expected the line/character output to be unchanged, *or* changed, but still consistent with the length of the line in question.

#### Build info

```
golang.org/x/tools/gopls 0.4.3
    golang.org/x/tools/gopls@v0.4.3 h1:irz7Q+XdHNECamFKbNWKvMV2Ak6zBbwdwbZndG4545I=
    github.com/BurntSushi/toml@v0.3.1 h1:WXkYYl6Yr3qBf1K79EBnL4mak0OimBfB0XUf9Vl28OQ=
    github.com/sergi/go-diff@v1.1.0 h1:we8PVUC3FE2uYfodKH/nBHMSetSfHDR6scGdBi+erh0=
    golang.org/x/mod@v0.2.0 h1:KU7oHjnv3XNWfa5COkzUifxZmxp1TyI7ImMXqFxLwvQ=
    golang.org/x/sync@v0.0.0-20190911185100-cd5d95a43a6e h1:vcxGaoTs7kV8m5Np9uUNQin4BrLOthgV7252N8V+FwY=
    golang.org/x/tools@v0.0.0-20200708181441-6004c8539734 h1:Vc0Vx98oU/O3+qPQ36fnTT5UduS55KLh2uSGbL7mqEo=
    golang.org/x/xerrors@v0.0.0-20191204190536-9bdfabe68543 h1:E7g+9GITq07hpfrRu66IVDexMakfv52eLZ2CXBWiKr4=
    honnef.co/go/tools@v0.0.1-2020.1.4 h1:UoveltGrhghAA7ePc+e+QYDHXrBps2PqFZiHkGR/xK8=
    mvdan.cc/xurls/v2@v2.2.0 h1:NSZPykBXJFCetGZykLAxaL6SIpvbVy/UFEniIfHAa8A=
```

#### Go info

```
go version go1.13.8 darwin/amd64

```
Repository: PowerToys
Issue: [KBM] Automatically deactivate warning tone (Caps Lock Windows setting)
Labels: Idea-Enhancement,Product-Keyboard Shortcut Manager

Hello everyone 👋

I like to use the Keyboard Manager.
This makes reassign _Caps Lock_ to _Shift left_ easy for me.
In order not to accidentally activate Caps Lock, I activated the warning tone in the Windows settings.
(This sound is still present although key reassigned.)

It would be great if this warning tone was automatically deactivated if desired.
Or you can add a link to the Keyboard Manager to go directly to the corresponding Windows settings dialog.

Best wishes

Christian

---

If you'd like to see this feature implemented, add a 👍 reaction to this post.
Repository: pytorch
Issue: Reading data speed slower than tensorflow
Labels: module: performance,module: dataloader,triaged

I tried two version code for iterating MNIST data to compare the elapsed time.

Pytorch version
```
import os
os.environ["CUDA_VISIBLE_DEVICES"] = "0"
import torch
from torchvision import datasets, transforms
import matplotlib.pyplot as plt
import time
train_loader = torch.utils.data.DataLoader(
    datasets.MNIST('~/data', train=True, download=True,
                   transform=transforms.Compose([
                       transforms.ToTensor(),
                       # transforms.Normalize((0.1307,), (0.3081,))
                   ])),
    batch_size=30000, shuffle=True,pin_memory=True,num_workers=4)
tic = time.time()
for epoch in range(0, 5):
    for batch_idx, (data, target) in enumerate(train_loader):
        continue
toc=time.time()
print('elapsed time:',toc-tic)
```
**Tensorflow 2.x version**
```
import os
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
os.environ["CUDA_VISIBLE_DEVICES"] = "0"
import tensorflow as tf
from tensorflow.keras import datasets
import time
(xs, ys), (xs_, ys_) = datasets.mnist.load_data()
# print('datasets:', xs.shape, ys.shape, xs.min(), xs.max())
xs = tf.convert_to_tensor(xs, dtype=tf.float32) / 255.
db = tf.data.Dataset.from_tensor_slices((xs, ys))
db = db.batch(30000)
tic = time.time()
for epoch in range(5):
    for step, (x, y) in enumerate(db):
        continue
toc = time.time()
print('elapsed time:', toc - tic)
```

And the result are TF elapsed 2s and Pytorch elapsed 15s. So, why Pytorch is slower than Tensorflow in reading data? 
Am I setting it wrong? 
Thanks!

cc @SsnL @VitalyFedyunin @ngimel @ppwwyyxx
Repository: PowerToys
Issue: [Shortcut Guide] Remove "Open Dictation Bar" for unsupported Languages 
Labels: Idea-Enhancement,Product-Shortcut Guide

Not every Language in Windows supports the dictation bar. When you press then win + h nothing happen. So it could be removed for non supported languages. 

---

If you'd like to see this feature implemented, add a 👍 reaction to this post.
Repository: pytorch
Issue: slow data loading in VisionDataset  - need to allow batch loading.
Labels: module: performance,feature,module: dataloader,triaged,module: vision

## 🚀 Feature
VisionDataset  is slow in loading large batches. This happens because of data being loaded and transformed by single item in regular Python cycle. 

## Motivation
I have a bit of frustration when seeing slower Pytorch code vs TF in data loading functions. 

## Pitch
1) fix `__getitem__()` for `VisionDataset()` class so it allows loading and transforming batches at once
2) allow `auto_collation = False` in [_MapDatasetFetcher ](https://github.com/pytorch/pytorch/blob/master/torch/utils/data/_utils/fetch.py)

## Alternatives
There may be ideas based on how TF does it - works much faster in such situations

## Additional context
see question and answer at SO [here](https://stackoverflow.com/questions/63202478/why-pytorch-is-slower-than-tensorflow-in-read-data/63204186#63204186).



cc @SsnL @VitalyFedyunin @fmassa @vfdev-5 @ngimel
Repository: pytorch
Issue: torch.distributions.multinomial.Multinomial cannot be used in batch
Labels: module: distributions,feature,triaged

torch.distributions.multinomial.Multinomial(total_count=1, probs=None, logits=None, validate_args=None)

the total_count is must be int, but not tensor, so I can't use this function in a batch scenario.  It's quite inconvenient.
![image](https://user-images.githubusercontent.com/30493522/89102992-f7e1fe80-d440-11ea-971b-e111e3cb94c4.png)


cc @vincentqb @fritzo @neerajprad @alicanb @vishwakftw
Repository: godot
Issue: Material transparency bug over far blured environnement
Labels: topic:rendering,confirmed,documentation,topic:3d

**Godot version:** Observed since 3.2.2 (not tested earlier) -> 3.2.3RC3


**OS/device including version:**
Tested in Linux / MacOs and Windows environnements


**Issue description:**
When far blur is activated in environnement,
Transparent material meshes don't deal correctly (i think) with depth.

Either the mesh is sharp but the background inside the mesh isn't blurred anymore
This is the case when depth draw mode is set to Always in the material setting

Either the mesh over the blur background is also blurred even if it's not enough far from the camera to be blurred by far blur.
This is the case for all other depth draw mode (Opaque only, opaque prepass or never)

**Steps to reproduce:**
Configure a far blur environnement.
Add a semi transparent mesh

![bug](https://user-images.githubusercontent.com/3649998/89105865-3ff32800-d425-11ea-8160-d0681415f779.jpg)


**Minimal reproduction project:**
[TransparencyBug.zip](https://github.com/godotengine/godot/files/5010916/TransparencyBug.zip)
Repository: PowerToys
Issue: [Run][New Plugin] Quick Reminder notifications
Labels: Idea-Enhancement,Product-PowerToys Run,Run-Plugin

## 📝 Add quick reminds with Windows notifications.

![image](https://user-images.githubusercontent.com/228802/89106021-6f129500-d437-11ea-9dc2-2a3d20bfbddc.png)

Type reminder command in specific language like on screenshot, and then show Windows notifications on time.

Purpose is to not forget to do important stuff in short period of time.

---

If you'd like to see this feature implemented, add a 👍 reaction to this post.
Repository: godot
Issue: Script button in remove mode on custom class nodes
Labels: bug,topic:editor

**Godot version:**
3.2.2.stable.official

**OS/device including version:**
Windows 10, AMD 2600X (x86_64), Nvidia GTX 1660TI

**Issue description:**
When using `add_custom_type()`, and selecting a custom node that has been added to the scene, the "add/remove script" button at the top of the scenetree pane is in remove mode, and clicking it does nothing as the class script is not removable. 
Expected behavior: this button should either be "add script" or "extend script" when a custom node is selected.

**Steps to reproduce:**
1. Use `add_custom_type()` to register a new node type
2. Add an instance of the registered class to a scene
3. Select the instance

**Minimal reproduction project:**
[customnode_bug.zip](https://github.com/godotengine/godot/files/5011013/customnode_bug.zip)