sharjeelyunus/github-issues-dataset huggingface dataset:
Repository: pytorch
Issue: CuDNN convolution on some CUDA devices will not preserve NaN weights (upstream bug)
Labels: module: dependency bug,module: cudnn,low priority,triaged

## 🐛 Bug

<!-- A clear and concise description of what the bug is. -->
`Conv1d` with nan weights outputs non-nan values during traing. But after saving and reloading the weights, it outputs nan values. It should output nan value not only after reloading but also during training if the weights are nan. And I don't know why the weights become nan.

These lines in my repo are example. It prints only `weight has nan` after hundreds iterations.

https://github.com/dhgrs/pytorch-UniWaveNet/blob/484efb51a48586f9b1189a60ce35c6408310d744/net.py#L58-L70

## To Reproduce

Steps to reproduce the behavior:

1. Clone this [repo](https://github.com/dhgrs/pytorch-UniWaveNet).
1. Download [LJSpeech](https://keithito.com/LJ-Speech-Dataset/) and set the path in `params.py`.
1. Install librosa and tqdm.
1. `Python train.py`

## Expected behavior

`Conv1d` outputs nan value or `Conv1d`'s weights are not  nan values.

<!-- A clear and concise description of what you expected to happen. -->

## Environment
PyTorch version: 0.5.0a0+a24163a
Is debug build: No
CUDA used to build PyTorch: 9.1.85

OS: Ubuntu 16.04.5 LTS
GCC version: (Ubuntu 5.4.0-6ubuntu1~16.04.10) 5.4.0 20160609
CMake version: version 3.5.1

Python version: 3.6
Is CUDA available: Yes
CUDA runtime version: 9.1.85
GPU models and configuration: GPU 0: GeForce GTX 1080 Ti
Nvidia driver version: 390.87
cuDNN version: Probably one of the following:
/usr/lib/x86_64-linux-gnu/libcudnn.so.7.1.2
/usr/lib/x86_64-linux-gnu/libcudnn_static_v7.a
/usr/local/lib/python3.6/site-packages/cupy/_lib/libcudnn.so.7

Versions of relevant libraries:
[pip3] msgpack-numpy (0.4.3.1)
[pip3] numpy (1.15.1)
[pip3] torch (0.5.0a0+a24163a)
[pip3] torchtext (0.2.3)
[pip3] torchvision (0.2.1)
[conda] Could not collect
Repository: opencv
Issue: cv::cuda::norm works only for single channel images.
Labels: category: gpu/cuda (contrib)

https://github.com/opencv/opencv/blob/808ba552c532408bddd5fe51784cf4209296448a/modules/cudaarithm/src/cuda/norm.cu#L104

There does not seem to be any such constraint for the cpu version. Does removing this constraint have any side effects?
Repository: flutter
Issue: Flutter Tester binaries should be optimized with debug assertions enabled
Labels: a: tests,engine,P2,team-engine,triaged-engine

The current binaries distributed to cloud buckets by the buildbots are from the host_debug_unopt variant. This was done so that all debug assertions would hold and the binaries would contain debug symbols to boot. We should update the buildroot to enable optimized builds with debug assertions as well as symbols. Unoptimized binaries are significantly slower.
Repository: create-react-app
Issue: mini-css-extract-plugin throws "Conflicting order" errors during build
Labels: contributions: up for grabs!,tag: documentation,difficulty: starter

(react-scripts 2.0.4)
Same as in [this issue](https://github.com/webpack-contrib/mini-css-extract-plugin/issues/250) I am getting a lot of errors from the mini-css-extract-plugin when doing a CI build - which fails since no warnings are allowed.
Since CRA does not allow customizing the WebPack plugin config, I cannot use the [warningsFilters](https://github.com/webpack-contrib/mini-css-extract-plugin/issues/250#issuecomment-415345126) and the [question about CRA also already popped up](https://github.com/webpack-contrib/mini-css-extract-plugin/issues/250#issuecomment-425287049).

I am not sure what the CRA team can do about this - but maybe just keep an eye on it (or have it documented as a Known Issue) until WebPack somehow solves it.

PS: for now I am running "set CI=&&react-scripts build" to disable the CI build warnings limit.
Repository: vscode
Issue: Git - support HEAD <> working tree changes in gutter
Labels: help wanted,feature-request,git

Issue Type: <b>Feature Request</b>

I'd like to see staged changes as well as unstaged changes in the gutter. Currently, VS Code only shows unstaged changes, at least when using Git.

Unstaged changes: 
<img width="131" alt="fikcx" src="https://user-images.githubusercontent.com/103690/46696912-635e3a80-cbe1-11e8-97d4-287bc37bcfcd.png">

Staged changes:
<img width="128" alt="b6y38" src="https://user-images.githubusercontent.com/103690/46696925-68bb8500-cbe1-11e8-96bb-cd074c8648ea.png">

See https://stackoverflow.com/questions/48881124/can-i-make-visual-studio-code-highlight-staged-changes as well as https://github.com/eamodio/vscode-gitlens/issues/396 .

VS Code version: Code 1.28.0 (431ef9da3cf88a7e164f9d33bf62695e07c6c2a9, 2018-10-04T16:40:40.180Z)
OS version: Darwin x64 16.7.0


<!-- generated by issue reporter -->
Repository: pytorch
Issue: Support calculating grad for dense in sparse @ dense 
Labels: module: sparse,triaged

## 🐛 Bug

I get an error when I try to backprop through `torch.matmul` where the first matrix is a sparse matrix and the second matrix (dense) requires gradient. I am getting the following error:

```
RuntimeError: Expected object of type torch.FloatTensor but found type torch.sparse.FloatTensor for argument #2 'mat2'
```

Note that the sparse matrix does not require gradient in my case.

More specifically backpropagating through `torch.matmul(A, x)` works fine, but it doesn't work for `torch.matmul(A, x.transpose(0,1))`. It works fine when doing `torch.matmul(A, x.transpose(0,1).clone())`

## To Reproduce

Steps to reproduce the behavior:

Run the following script

```
import torch
x = torch.ones(3, 3, requires_grad=True)
i = torch.LongTensor([ [0, 1, 2], [0, 1, 2] ])
v = torch.FloatTensor([1,1,1])
A = torch.sparse.FloatTensor(i, v, (3,3))
y = torch.matmul(A, x.transpose(0,1))
loss = y.mean()
loss.backward()
```

## Expected behavior

Backprop normally through this operation.

## Environment

I am using **pytorch/pytorch:0.4.1-cuda9-cudnn7-runtime**

```
PyTorch version: 0.4.1
Is debug build: No
CUDA used to build PyTorch: 9.0.176

OS: Ubuntu 16.04.5 LTS
GCC version: (Ubuntu 5.4.0-6ubuntu1~16.04.10) 5.4.0 20160609
CMake version: Could not collect

Python version: 3.6
Is CUDA available: Yes
CUDA runtime version: Could not collect
GPU models and configuration: GPU 0: GeForce GTX TITAN Z
Nvidia driver version: 384.130
cuDNN version: Could not collect

Versions of relevant libraries:
[pip] numpy (1.14.5)
[pip] torch (0.4.1)
[pip] torchvision (0.2.1)
[conda] cuda90                    1.0                  h6433d27_0    pytorch
[conda] pytorch                   0.4.1           py36_cuda9.0.176_cudnn7.1.2_1    pytorch
[conda] torchvision               0.2.1                    py36_1    pytorch
```
Repository: pytorch
Issue: C++: Calling Workspace::RunNet for a prediction on a different thread each time causes a GPU memory leak
Labels: caffe2

## 🐛 Bug
Hi, 
I am trying to obtain a model prediction (on GPU) while running another piece of code in parallel (on CPU). Since I am streaming data, I instantiate a separate std::thread (or std::async) every time to call Workspace::RunNet, this causes a GPU memory leak which is not noticeable unless you are streaming data. However, if the thread used is maintained (a worker thread with the same thread_id), the leak does not occur.
Thank you,
<!-- A clear and concise description of what the bug is. -->

## To Reproduce
Steps to reproduce the behavior:
1. Given a pre-trained model, please use the following sample code to reproduce the issue:
<!-- If you have a code sample, error messages, stack traces, please provide it here as well -->
```
// Network setup

caffe2::NetDef init_net;
caffe2::NetDef predict_net;
ReadProtoFromFile(init_file, &init_net);
ReadProtoFromFile(predict_file, &predict_net);
auto  workspace = std::make_unique<caffe2::Workspace>();
const auto cuda_device = caffe2::TypeToProto(caffe2::CUDA);
predict_net.mutable_device_option()->set_device_type(cuda_device);
init_net.mutable_device_option()->set_device_type(cuda_device);
workspace->CreateBlob(predict_net_.external_input(0));
workspace->RunNetOnce(init_net);
workspace->CreateNet(predict_net);

// Tensors setup

auto input_host_tensor = std::make_unique<caffe2::TensorCPU>(dims, caffe2::CPU);
input_host_tensor->ShareExternalPointer(some_buffer);  // some_buffer will be filled with the input data
auto input_device_tensor = std::make_unique<caffe2::TensorCUDA>(dims, caffe2::CUDA);
workspace->GetBlob(predict_net_.external_input(0))->Reset(input_device_tensor.get());
 
// Prediction

while(true) {
   FetchData(some_buffer);
   input_device_tensor->CopyFrom(*input_host_tensor);

  // This is where the leak occurs
   std::thread my_thread(&caffe2::Workspace::RunNet, workspace.get(), predict_net.name());

  //
  // some host code
  //

  my_thread.join();
}

```

## Expected behavior
Not expecting a memory leak when executing on threads with different thread ids.
<!-- A clear and concise description of what you expected to happen. -->

## Environment
```
Linux=Ubuntu 16.04.4 LTS
cmake 3.5.1
gcc 5.4.0
NVIDIA CUDA 8.0
NVIDIA cuDNN v6.0
Pytorch built from source (version to date is v1.0rc1)
```
## Additional context

<!-- Add any other context about the problem here. -->
Repository: material-ui
Issue: [Accessibility] Some of the components are not visible or rendered properly in Windows High Contrast Mode
Labels: accessibility

While testing our application in Windows High Contrast Mode (Both ie11 and Edge), could see that some of the material-ui/core components are not visible or rendered properly. Reproduced the issues while accessing the Demo Components in material-ui page (https://material-ui.com/)

<!-- Checked checkbox should look like this: [x] -->
- [x] This is not a v0.x issue. <!-- (v0.x is no longer maintained) -->
- [x] I have searched the [issues](https://github.com/mui-org/material-ui/issues) of this repository and believe that this is not a duplicate.

## Expected Behavior
In Windows High Contrast Mode, all elements should be visible and user friendly. 

## Current Behavior
In Windows High Contrast Mode, the below components are not behaving as expected
 - Switches are not visible.
 - User cannot distinguish between enabled and disabled Selection Controls like Radio button and Checkbox.
 - The first character in Text Field (if not intended) is cropped.
 - The first character in some of the Select (if not intended) is cropped.
 - In Menus, user is not able to distinguish between selected and de-selected MenuItem.

## Steps to Reproduce
1. In Windows 10, open High Contrast setting and select a High contrast theme (High Contrast#1 or High Contrast#2)
2. Open ie11 and Edge browsers.
3. Go to https://material-ui.com/demos/ and validate Switches, Text Field, Menus, Select etc
4. Verify the issues.

## Context
Our application is used by many users who have visual problems and need to make sure it's accessible to all users across platforms.

## Your Environment

| Tech         | Version |
|--------------|---------|
| Material-UI/core  | v3.0.0  |
| React        | v16.4.1        |
| Browser      | ie11, Edge        |
Repository: TypeScript
Issue: Automatic typings install does not trigger project refresh
Labels: Bug

From https://github.com/Microsoft/vscode/issues/59436

<!-- Please try to reproduce the issue with `typescript@next`. It may have already been fixed. -->
**TypeScript Version:**  3.2.0-dev.20181009

<!-- Search terms you tried before logging this (so others can find this issue more easily) -->
**Search Terms:**
- ATA, automatic typings acquisition

**Code**
Tested on macos with npm 6.4.1.

1. Clear the typings cache.
1. For a new JS project with contents:

`package.json`

```
{
    "dependencies": {
        "express": "4.16.3"
    }
}
```

`main.js`

```js
import * as express from "express"
 
let a = express()
```

1. Open the project in vscode
1. Run `npm install`
1. Open `main.js`

1. Notice the `...` suggestion on the import stating `could not find a declaration file for module 'express'`

1. Check ATA directory and see that express typings have been installed

**Bug**
The `...` suggestion is never removed and we fail to get proper typings for express. After reloading the javascript project we do start seeing the correct suggestions
Repository: kubernetes
Issue: Add tests using storage framework for the default storageclass
Labels: sig/storage,kind/feature,area/conformance,lifecycle/frozen

<!-- This form is for bug reports and feature requests ONLY!

If you're looking for help check [Stack Overflow](https://stackoverflow.com/questions/tagged/kubernetes) and the [troubleshooting guide](https://kubernetes.io/docs/tasks/debug-application-cluster/troubleshooting/).

If the matter is security related, please disclose it privately via https://kubernetes.io/security/.
-->

**Is this a BUG REPORT or FEATURE REQUEST?**:
@kubernetes/sig-storage-feature-requests 

**What happened**:
We can consider these tests as a future conformance profile candidate.  See https://github.com/kubernetes/kubernetes/issues/65155#issuecomment-411486293
Repository: pytorch
Issue: The text design (color, type) makes it hard to read
Labels: todo,triaged

The text color and type is hard to read, contrast is too low and text too thin,
even playing with the browser zoom does not make it much better.

I actually wrote small bookmarklet for myself to just color the text black and different font to temporarily fixed it. code here for those interested -
javascript:function changeFontColor() {var all = document.getElementsByTagName("*"); for (var i=0, max=all.length; i < max; i++) { all[i].style.color = "black"; all[i].style.fontFamily = 'Arial'; }}; changeFontColor();
Repository: go
Issue: runtime: segfault during test using -coverpkg and -race
Labels: RaceDetector,NeedsInvestigation

### What version of Go are you using (`go version`)?
go1.11.1

### Does this issue reproduce with the latest release?
Yes

### What operating system and processor architecture are you using (`go env`)?
Linux amd64

### What did you do?
`go test -c -o aTestBinary -coverpkg package1,package2,package3 -covermode atomic -race -ldflags '-w -s -extldflags "-static -Wl,--no-export-dynamic"'`
`./aTestBinary -test.v -test.run . -test.coverprofile coverout`

### What did you expect to see?
Success

### What did you see instead?
```
unexpected fault address 0x19600
fatal error: fault
[signal SIGSEGV: segmentation violation code=0x1 addr=0x19600 pc=0x12a0389]

goroutine 63887 [running]:
runtime: unexpected return pc for runtime.throw called from 0x5
stack: frame={sp:0x7f0386ffca70, fp:0x7f0386ffcaa0} stack=[0xc0021f4000,0xc0021f6000)

runtime.throw(0x5, 0x7f0386ffcae0)
	/usr/local/go/src/runtime/panic.go:608 +0x72 fp=0x7f0386ffcaa0 sp=0x7f0386ffca70 pc=0x497d42
created by ...

goroutine 1 [chan receive]:
testing.tRunner.func1(0xc000112100)
	/usr/local/go/src/testing/testing.go:803 +0x2e4
testing.tRunner(0xc000112100, 0xc00011bc98)
	/usr/local/go/src/testing/testing.go:831 +0x17f
testing.runTests(0xc0000c4060, 0x410d5c0, 0xa5, 0xa5, 0xc0000bc000)
	/usr/local/go/src/testing/testing.go:1117 +0x4ef
testing.(*M).Run(0xc000232200, 0x0)
	/usr/local/go/src/testing/testing.go:1034 +0x2ef
.../....TestMain(0xc000232200)
	/go/src/....go:36 +0x123
main.main()
	_testmain.go:962 +0x33f

goroutine 50 [chan receive]:
testing.(*testContext).waitParallel(0xc0000ad1d0)
	/usr/local/go/src/testing/testing.go:926 +0x15c
testing.(*T).Parallel(0xc000112200)
	/usr/local/go/src/testing/testing.go:733 +0x3e5
...
```

Probably related #23882?
Repository: pytorch
Issue: how to use mask-rcnn in caffe2 c++ gpu
Labels: caffe2

I changed the pkl model to pb model use  convert_pkl_to_pb.py , but only detection net will be converted even in Mask R-CNN which has mask net

If anyone could share an example working code with GPU in C++, that'd be amazing.
Repository: vscode
Issue: [html] proper support of XHTML
Labels: feature-request,html

XHTML is parsed as HTML rather than as XML, which causes various issues:

- Self closing tags are not allowed, except for elements which in HTML are void elements.
- Elements which in HTML are void elements are allowed to be unclosed, and are unclosed by default.
- Elements which in HTML are void elements are not allowed to have a separate close tag.
- Attribute values are allowed to be omitted or unquoted.
Repository: rust
Issue: Subslice search
Labels: T-libs-api,C-feature-request

As enhancement, I think stdlib should contain functions that search a subslice inside a given slice:

```
fn contains_subslice<T: PartialEq>(data: &[T], needle: &[T]) -> bool {
    data
    .windows(needle.len())
    .any(|w| w == needle)
}

fn position_subslice<T: PartialEq>(data: &[T], needle: &[T]) -> Option<usize> {
    data
    .windows(needle.len())
    .enumerate()
    .find(|&(_, w)| w == needle)
    .map(|(i, _)| i)
}

fn main() {
    println!("{}", contains_subslice(b"hello", b"ll"));
    println!("{:?}", position_subslice(b"hello", b"ll"));
}
```

For the common case of T:Copy items the true stdlib functions should specialize using a smarter algorithm, like:
https://en.wikipedia.org/wiki/Knuth%E2%80%93Morris%E2%80%93Pratt_algorithm

(Similar functions are useful for iterators too).
Repository: go
Issue: net: clarify documentation on net.ListenConfig.Listen and related calls w.r.t. context
Labels: Documentation,help wanted,NeedsFix

### What version of Go are you using (`go version`)?
go version go1.11.1 linux/amd64

### Does this issue reproduce with the latest release?
Yes

### What operating system and processor architecture are you using (`go env`)?
GOARCH="amd64"
GOOS="linux"

### What did you do?
I created a net.ListenConfig.Listen(cancelableCtx, "unix", "/path/to/socket") to create a Unix socket, and called Accept on said listener.

### What did you expect to see?
I expected canceling the context to cancel the Accept.

### What did you see instead?
The Accept was not canceled.

---

So maybe my expectation was wrong.  I reasoned "_Why else_ would there be a context there if not to cancel (or time out) the Accept calls?".  But clearly not.

I asked on the #general channel in the Gophers Slack and was reminded that Dial, for example, specifically says that once Dial completes, the context it's given doesn't affect the connection, and that probably Listen & Accept were similar.  That does appear to be the case.

So, for folks like me that are not terribly familiar with network or socket programming, would it be possible to note in the Listen & Accept docs that the given context doesn't affect the later Accept?  And maybe even what the Listen context actually does; it wasn't 100% clear to me.

Thanks.
Repository: go
Issue: x/tools/go/packages: support for loading files/syntax irrespective of build tags
Labels: modules,Tools

### What version of Go are you using (`go version`)?

```
go version go1.11.1 linux/amd64
go/packages commit 29f11e2b93f4d66f7c335bd7b2892836d4944f5c
```

### Does this issue reproduce with the latest release?

Yes, per above

### What operating system and processor architecture are you using (`go env`)?

```
GOARCH="amd64"
GOBIN=""
GOCACHE="/home/myitcv/.cache/go-build"
GOEXE=""
GOFLAGS=""
GOHOSTARCH="amd64"
GOHOSTOS="linux"
GOOS="linux"
GOPATH="/home/myitcv/gostuff"
GOPROXY=""
GORACE=""
GOROOT="/home/myitcv/gos"
GOTMPDIR=""
GOTOOLDIR="/home/myitcv/gos/pkg/tool/linux_amd64"
GCCGO="gccgo"
CC="gcc"
CXX="g++"
CGO_ENABLED="1"
GOMOD=""
CGO_CFLAGS="-g -O2"
CGO_CPPFLAGS=""
CGO_CXXFLAGS="-g -O2"
CGO_FFLAGS="-g -O2"
CGO_LDFLAGS="-g -O2"
PKG_CONFIG="pkg-config"
GOGCCFLAGS="-fPIC -m64 -pthread -fmessage-length=0 -fdebug-prefix-map=/tmp/go-build137760326=/tmp/go-build -gno-record-gcc-switches"
```

Picking up on the discussion from the [2018-10-09 golang-tools catch up](https://docs.google.com/document/d/1oEknhf60Cdg9p_i17ESIm3zjTuVK7Adr-lTw78D0Qrc/edit#)

In the pre-modules world, `go/build` and `go/parser` could be used in combination to get file and syntax information for packages and their dependencies _irrespective_ of `GOOS`, `GOARCH` and build tags via the `UseAllFiles` [`go/build.Context`](https://godoc.org/go/build#Context) field. 

This use case is important for tools like [`govers`](https://github.com/rogpeppe/govers) and [`gogrep`](https://github.com/mvdan/gogrep). 

`go/packages` is driven by [`Config`](https://godoc.org/golang.org/x/tools/go/packages#Config) which includes `GOOS`, `GOARCH` and build tags and hence its response is specific to the provided config. `go/packages` cannot, therefore, be used in these use cases.

This issue is a placeholder to continue discussion about how best to support loading of files, imports and syntax in a `GOOS`, `GOARCH` and build tags-agnostic way.

cc @ianthehat @matloob @alandonovan @bcmills @rogpeppe @mvdan
Repository: react
Issue: JAWS reads non-interactive elements as Clickable
Labels: Type: Bug

**Do you want to request a *feature* or report a *bug*?**
Bug

**What is the current behavior?**
1. I create an app using [create-react-app](https://github.com/facebook/create-react-app)
2. I use JAWS Professional Edition Version 2018 (build 1710.42 ILM) and Internet Explorer 11 on Windows 7
3. I use arrow keys to navigate to paragraph "Edit src/App.js and save to reload."
4. Jaws announces "Edit src/App.js and save to reload. **clickable**"

**What is the expected behavior?**
This paragraph is non interactive, it should not be announced as clickable.

**Which versions of React, and which browser / OS are affected by this issue? Did this work in previous versions of React?**
- JAWS Professional Edition Version 2018 (build 1710.42 ILM) 
- Internet Explorer 11
- Windows 7
- create-react-app 2.0.3

**suspected cause**
Using Chrome Event Listener Breakpoints I observed there's a function called `trapClickOnNonInteractiveElement` which is the onclick handler for non interactive elements. This noop function is causing JAWS to think this is an interactive element

**possible solution**
In [trapClickOnNonInteractiveElement](https://github.com/facebook/react/blob/8a8d973d3cc5623676a84f87af66ef9259c3937c/packages/react-dom/src/client/ReactDOMComponent.js#L245) there is a comment which reads 
```
// TODO: Only do this for the relevant Safaris maybe?
```
I think that this would fix this issue.
Repository: pytorch
Issue: Provide better documentation for torch.Size
Labels: module: docs,triaged

## 📚 Documentation

<!-- A clear and concise description of what content in https://pytorch.org/docs is an issue. If this has to do with the general https://pytorch.org website, please file an issue at https://github.com/pytorch/pytorch.github.io/issues/new/choose instead. If this has to do with https://pytorch.org/tutorials, please file an issue at https://github.com/pytorch/tutorials/issues/new -->
Current documentation doesn't have an entry for torch.Size, in particular it is not clear how to convert torch.Tensor to torch.Size or the other way around.