sharjeelyunus/github-issues-dataset huggingface dataset:
Repository: material-ui
Issue: [Select] NVDA does not announce helper text
Labels: accessibility,component: select

This may be captured more broadly by issue #15597
When focus is brought to a (non native) select widget, NVDA announces the label and the value but not the helper text.

NVDA announces native select widgets as expected (value, label, and helper text).

- [x] The issue is present in the latest release.
- [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.

## Steps to Reproduce 🕹

The code sandbox is taken from the Material-UI [docs](https://material-ui.com/components/text-fields/)
https://lu6rp.csb.app/

Steps:
1. Using NVDA, bring focus to the "Select". The label and value is announced but not the helper text.
2. Then bring focus to the "Native Select". The label, value, and helper text is announced - illustrating the expected behaviour
Repository: go
Issue: x/pkgsite: automate fetching of new versions of Go standard library
Labels: NeedsInvestigation,FeatureRequest,pkgsite

This issue is related to #37002, but limited in scope to just the Go standard library.

When a new version of Go is released, it takes a manual action to add it to pkg.go.dev. This can and should be automated, so that it happens as soon as a new Go version is released.

/cc @julieqiu @jba @cagedmantis @toothrot @FiloSottile
Repository: flutter
Issue: Update flutter docs for LiveTestWidgetsFlutterBinding
Labels: a: tests,framework,d: api docs,P2,team-framework,triaged-framework

Right now `LiveTestWidgetsFlutterBinding` looks like it's a solution for app developers, but it's primarily for use in testing the Flutter framework itself. We should update the documentation to push Flutter app and plugin authors to use appropriate alternatives.
Repository: godot
Issue: propagate_notification method is inconsistent: not calling _enter_tree, but calling _ready
Labels: bug,topic:core

**Godot version:**
3.2 stable

**OS/device including version:**
Win 10

**Issue description:**
The issue is that calling `propagate_notification` method does not call `_enter_tree`, but it does call `_ready`. However, the `_notification` virtual method does receive all these notifications, it's just that the `_enter_tree` method is not called. The issue seems to be the same on tool and game side.

Note that the `propagate_call` method works perfectly, but by design it doesn't alarm any notifications and only calls the last extended (overridden) methods - not those of the inherited classes. Similarly if you explicitly call `_enter_tree` on a Node, it will only call the last method - unlike the `_notification` call that does go through the whole chain of inheritance.

The net result of all this, is that there seems to be no general way of calling `_enter_tree` on a Node, so that it would also call it on the inherited classes. However the whole chain does get called "normally" when a node enters the tree and becomes ready, and you can do this for `_ready` (even using the convenient `propagate_notification`), so there really should be a way to do this - to avoid hacky scripting.

**Update**:
Sorry, the earlier confusion about switching scene tabs - a crucial typo while debugging.

**Steps to reproduce:**
- See the minimal reproduction project. 
- See what happens when opening up the project (everything is correct). 
- See what happens when clicking the different "Test" properties on the inspector on the root node: The `_enter_tree` method never gets called on the Kid.gd (only on the KidExtended.gd).

**Minimal reproduction project:**
[PropagationProblem.zip](https://github.com/godotengine/godot/files/4269248/PropagationProblem.zip)
Repository: TypeScript
Issue: Object intellisense doesn't work properly when parameter is unioned with a non-object
Labels: Bug,Domain: Completion Lists

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<!--
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This is also the 'Nightly' version in the playground: http://www.typescriptlang.org/play/?ts=Nightly
-->
**TypeScript Version:**  3.8.2

<!-- Search terms you tried before logging this (so others can find this issue more easily) -->
**Search Terms:**

**Code**

```ts
declare function expectsConfig1(a: { x?: string }): void;
declare function expectsConfig2(a: { x?: string } | undefined): void;
expectsConfig1({});
expectsConfig2({});
```

![ig9JlMMIFn](https://user-images.githubusercontent.com/15217173/75591798-52b49b80-5a46-11ea-99ad-cbf8198fff87.gif)

**Expected behavior:** both should prompt you with `x` as a key
**Actual behavior:** only the first does
**Playground Link:** <!-- A link to a TypeScript Playground "Share" link which demonstrates this behavior --> n/a, playground doesn't support this intellisense at all. [Here it is anyway, though.](https://www.typescriptlang.org/play/?ts=3.9.0-dev.20200227#code/CYUwxgNghgTiAEAzArgOzAFwJYHtXxAA8AHcDAZwGE9EsBzARgAooAueAb3kIH53yMMLKjrwAvgEp2ANxxZgAbgBQoSLAQp02PARJkqNegCYW7Lr36DhosfAA+8NKFqoQwKfFnzlRUpgOotIxMHJI+ev7UgcYhYUA)
**Related Issues:** <!-- Did you find other bugs that looked similar? -->
Repository: storybook
Issue: Embed MDX Docs into Gatsby
Labels: feature request,addon: docs,mdx

**Is your feature request related to a problem? Please describe.**
So I noticed in this blog post [here](https://medium.com/storybookjs/rich-docs-with-storybook-mdx-61bc145ae7bc#78bb) that it mentions being able to embed the new mdx docs into gatsby at some point. But I went looking for some reference to that here in github that I could try to subscribe to and keep an eye on and didn't see anything. Is it still on the radar at all?

**Describe the solution you'd like**
Being able to embed the MDX docs into gatsby.

**Describe alternatives you've considered**
We've been playing with embedding the storybook iframe setup into gatsby already with some success, but if there's a built-in way to do something similar with the storybook MDX docs that would be really useful.

**Are you able to assist bring the feature to reality?**
Probably not.
Repository: pytorch
Issue: TensorPipes RPC Agent CUDA Support
Labels: module: cuda,triaged,module: rpc

## 🚀 Feature
CUDA support would require the following items:

- Support memory allocation and communication for GPUs. 
- Update RPC API to support args placement and result placement on CUDA devices. 
- Update `RRef.to_here()` to accept device placement arguments


cc @ngimel @pietern @mrshenli @pritamdamania87 @zhaojuanmao @satgera @gqchen @aazzolini @rohan-varma @xush6528 @jjlilley @osalpekar
Repository: go
Issue: runtime: ensuring support of debug.asyncpreemptoff
Labels: NeedsInvestigation,compiler/runtime

This came up during a routinely scheduled meeting between the Delve team and folks from the Go team and it was suggested by @heschik to open an issue about this to ensure it stays on folks minds.

Delve leverages the `debug.asyncpreemptoff` in order to disable the functionality on Windows [[0]] (where it won't play well with debuggers) and may use it on other platforms as well to disable the functionality when run under Delve [[1]] [[2]].

This issue is mostly to get feedback and assurance that we can rely on this feature for the foreseeable future.

[0]: https://github.com/golang/go/issues/36494
[1]: https://github.com/golang/go/issues/37528
[2]: https://github.com/go-delve/delve/issues/1905
Repository: pytorch
Issue: Initialize TensorPipe RPC Agent Transport
Labels: triaged,module: rpc

## 🚀 Feature
Allow the Tensorpipes RPC Agent to be initialized with any underlying transport (shm, libuv, thrift, TLS, etc.) This may need to be added as an option to the RPC Backend Options to initialize from Python.

cc @pietern @mrshenli @pritamdamania87 @zhaojuanmao @satgera @gqchen @aazzolini @rohan-varma @xush6528 @jjlilley @osalpekar
Repository: pytorch
Issue: TensorPipes RPC Agent Listener shortcut
Labels: triaged,module: rpc

## 🚀 Feature
Support an optimization in the TensorPipes RPC Agent listener when sending a message to yourself. This is similar to an optimization in the ProcessGroupAgent `listenLoopInternal`.


cc @pietern @mrshenli @pritamdamania87 @zhaojuanmao @satgera @gqchen @aazzolini @rohan-varma @xush6528 @jjlilley @osalpekar
Repository: node
Issue: ConsumeHTTP2Data Assertion error
Labels: http2

v10.16.3
OS X Catalina 10.15.3 (Darwin imac2019.lan 19.3.0 Darwin Kernel Version 19.3.0: Thu Jan  9 20:58:23 PST 2020; root:xnu-6153.81.5~1/RELEASE_X86_64 x86_64)

My app will run for an hour before it dies with the error below.  What does it mean please?

```
.nvm/versions/node/v10.16.3/bin/node[84392]: ../src/node_http2.cc:893:ssize_t node::http2::Http2Session::ConsumeHTTP2Data(): Assertion `(flags_ & SESSION_STATE_READING_STOPPED) != (0)' failed.
 1: 0x10003d035 node::Abort() [/Users/user/.nvm/versions/node/v10.16.3/bin/node]
 2: 0x10003c057 node::AddEnvironmentCleanupHook(v8::Isolate*, void (*)(void*), void*) [/Users/user/.nvm/versions/node/v10.16.3/bin/node]
 3: 0x100081b34 node::http2::Http2Session::ConsumeHTTP2Data() [/Users/user/.nvm/versions/node/v10.16.3/bin/node]
 4: 0x10008484e node::http2::Http2Session::OnStreamRead(long, uv_buf_t const&) [/Users/user/.nvm/versions/node/v10.16.3/bin/node]
 5: 0x10013a258 node::TLSWrap::ClearOut() [/Users/user/.nvm/versions/node/v10.16.3/bin/node]
 6: 0x10013b86e node::TLSWrap::OnStreamRead(long, uv_buf_t const&) [/Users/user/.nvm/versions/node/v10.16.3/bin/node]
 7: 0x1000efaca node::LibuvStreamWrap::OnUvRead(long, uv_buf_t const*) [/Users/user/.nvm/versions/node/v10.16.3/bin/node]
 8: 0x1009be83f uv__stream_io [/Users/user/.nvm/versions/node/v10.16.3/bin/node]
 9: 0x1009c60fb uv__io_poll [/Users/user/.nvm/versions/node/v10.16.3/bin/node]
10: 0x1009b6139 uv_run [/Users/user/.nvm/versions/node/v10.16.3/bin/node]
11: 0x100044831 node::Start(v8::Isolate*, node::IsolateData*, std::__1::vector<std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char> >, std::__1::allocator<std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char> > > > const&, std::__1::vector<std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char> >, std::__1::allocator<std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char> > > > const&) [/Users/user/.nvm/versions/node/v10.16.3/bin/node]
12: 0x100043d3c node::Start(uv_loop_s*, std::__1::vector<std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char> >, std::__1::allocator<std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char> > > > const&, std::__1::vector<std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char> >, std::__1::allocator<std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char> > > > const&) [/Users/user/.nvm/versions/node/v10.16.3/bin/node]
13: 0x100043886 node::Start(int, char**) [/Users/user/.nvm/versions/node/v10.16.3/bin/node]
15: 0x2 
```
Repository: pytorch
Issue: TensorPipes RPC Agent Message Acknowledgements
Labels: triaged,module: rpc

## 🚀 Feature
Since TensorPipes RPC Agent will support a `result_placement` argument, which allows the receiver to send the computed result to a worker that's not necessarily the sender, we must ensure that the sender receives confirmation of message success/failure. 

For example, if CPU0 sends a message to CPU1, and indicates that the result should be sent to GPU0, then GPU0 must indicate to CPU0 that the message was received. This would likely require that we have longer timeouts for such messages. 

Furthermore if the result must be placed on multiple devices, the original sender must ensure each of the machines receiving the result confirms successful message completion.


cc @pietern @mrshenli @pritamdamania87 @zhaojuanmao @satgera @gqchen @aazzolini @rohan-varma @xush6528 @jjlilley @osalpekar
Repository: TypeScript
Issue: Typecheck multiple module formats at once
Labels: Suggestion,Awaiting More Feedback

(The other side of #15833)

## Search Terms

typecheck multiple module formats

## Suggestion

For projects that compile to multiple output formats - e.g. different `module` outputs - it would be useful to have typechecking able to emit errors for multiple formats at once.

The reason that duplicate typechecking is needed is that typechecking is slightly different based on the module - e.g. for commonjs / AMD, `export =` and `import foo = require(...)` are both legal, whereas in ESNext they are not; ESNext has `import.meta` and in some cases, top level `await`, that AMD/Commonjs don't support.  So no single `module` target has the strictest typechecking.

The benefits are:
- save CPU time
- no need for running typecheck multiple times and get most errors duplicated between them

On it's own, I'm not sure it'll make a ton of sense - e.g. in `compilerOptions` the `module` field could take an array of modules, or we could use a new field for this; though together with emit for multiple module types (#15833) we could keep the invariant that tsc typechecks with the same module(s) that it emits.

## Use Cases

If I compile my code to both AMD and ESNext, typechecking only as AMD or only as ESNext, does not guarantee my code is valid for the other module format - an `export =` will fail ESNext typechecking, whereas an `import.meta` will fail AMD typechecking; so there's no single strictest typecheck mode; as is to guarantee correctness, I need to typecheck against all the module formats we emit, and then any type errors in e.g. function bodies would get repeated in both typechecks.  Deduping these errors would be the main benefit.
Repository: flutter
Issue: Document how to run profile/release from Xcode
Labels: platform-ios,tool,d: api docs,a: build,P3,team-ios,triaged-ios

In order to get Xcode use the correct debug/profile/release mode, the Generated.xcconfig file should include `FLUTTER_BUILD_MODE=xxx`.

A correct one would like like:
```
// This is a generated file; do not edit or check into version control.
FLUTTER_ROOT=/Users/liyuqian/flutter/flutter
FLUTTER_APPLICATION_PATH=/Users/liyuqian/flutter/test/webp
FLUTTER_TARGET=/Users/liyuqian/flutter/test/webp/lib/main.dart
FLUTTER_BUILD_DIR=build
SYMROOT=${SOURCE_ROOT}/../build/ios
FLUTTER_FRAMEWORK_DIR=/Users/liyuqian/flutter/flutter/bin/cache/artifacts/engine/ios-profile
FLUTTER_BUILD_NAME=1.0.0
FLUTTER_BUILD_NUMBER=1
TRACK_WIDGET_CREATION=true
FLUTTER_BUILD_MODE=profile
```

However, currently the Flutter tools are generating
```
// This is a generated file; do not edit or check into version control.
FLUTTER_ROOT=/Users/liyuqian/flutter/flutter
FLUTTER_APPLICATION_PATH=/Users/liyuqian/flutter/test/webp
FLUTTER_TARGET=/Users/liyuqian/flutter/test/webp/lib/main.dart
FLUTTER_BUILD_DIR=build
SYMROOT=${SOURCE_ROOT}/../build/ios
FLUTTER_FRAMEWORK_DIR=/Users/liyuqian/flutter/flutter/bin/cache/artifacts/engine/ios-profile
FLUTTER_BUILD_NAME=1.0.0
FLUTTER_BUILD_NUMBER=1
TRACK_WIDGET_CREATION=true
```
Repository: pytorch
Issue: TensorPipes RPC Agent Multiple Placement Retries
Labels: triaged,module: rpc

## 🚀 Feature
Since multiple machines can receive the result of a remote operation, it is possible that only some of these replies fail. We have 2 options for dealing with message failures:

- We mark the original future as complete only if all the recipients received the result. We can maintain a list on the sender of the recipients that received the result, and only retry those that failed.
- We have separate futures for each recipient, and each of these futures can be polled individually on whether that recipient successfully received the result.



cc @pietern @mrshenli @pritamdamania87 @zhaojuanmao @satgera @gqchen @aazzolini @rohan-varma @xush6528 @jjlilley @osalpekar
Repository: pytorch
Issue: TensorPipes RPC Agent Default Args/Result Device Mapping
Labels: triaged,module: rpc

## 🚀 Feature
The planned RPC change to accommodate TensorPipes involves adding arguments to specify machines for results and arguments placement. We should give users the option to supply a default mapping which we can default to when an explicit mapping is not given, or if a partial mapping is given. 

This mapping would include 2 items:
- a results placement dictionary to specify which machines each sub-field from the result should be placed on
- an args placement tuple of dictionaries, where each dictionary corresponds to the machine mapping for the sub-fields of one arg


cc @pietern @mrshenli @pritamdamania87 @zhaojuanmao @satgera @gqchen @aazzolini @rohan-varma @xush6528 @jjlilley @osalpekar
Repository: pytorch
Issue: ModuleList doesn't support slicing in TorchScript
Labels: oncall: jit

## 🐛 Bug

Slicing a ModuleList works in eager mode, but fails to script.

## To Reproduce

```
class MyModule(torch.nn.Module):
    def __init__(self):
        super().__init__()
        self.mods = torch.nn.ModuleList([
            torch.nn.Identity(),
            torch.nn.Identity(),
        ])
        
    def forward(self, arg):
        for good_mod in self.mods[:-1]:
            arg = good_mod(arg)
        return arg
    
m = MyModule()
print(m(0))
torch.jit.script(m)

0

---------------------------------------------------------------------------
RuntimeError                              Traceback (most recent call last)
<ipython-input-94-45a56232649d> in <module>
     14 m = MyModule()
     15 print(m(0))
---> 16 torch.jit.script(m)

[...]

RuntimeError: 
Arguments for call are not valid.
The following variants are available:
  
  aten::slice.Tensor(Tensor(a) self, int dim=0, int start=0, int end=9223372036854775807, int step=1) -> (Tensor(a)):
  Expected a value of type 'Tensor' for argument 'self' but instead found type '__torch__.torch.nn.modules.container.___torch_mangle_26.ModuleList'.
  
[...]

The original call is:
  File "<ipython-input-94-45a56232649d>", line 10
    def forward(self, arg):
        for good_mod in self.mods[:-1]:
                        ~~~~~~~~~~~~~ <--- HERE
            arg = good_mod(arg)
        return arg
```

## Environment

```
Collecting environment information...
PyTorch version: 1.5.0.dev20200226+cpu
Is debug build: No
CUDA used to build PyTorch: None

OS: Fedora release 30 (Thirty)
GCC version: (GCC) 9.1.1 20190503 (Red Hat 9.1.1-1)
CMake version: version 3.14.4

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:
[pip3] numpy==1.17.0
[pip3] pytorch-pretrained-bert==0.6.2
[pip3] torch==1.2.0
[pip3] torchtext==0.4.0
[conda] Could not collect
```

## Additional context

Look, folks.  I don't write these models.  I just need to get them running on mobile.

I'm currently working around this by tracing the model because it has no data-dependent control flow.


cc @suo
Repository: godot
Issue: move_child() does not correctly refresh Texturebutton overlap priority when they are children of Node2Ds
Labels: bug,topic:gui

**Godot version:** v3.2.stable.official

**OS/device including version:** PC, Microsoft Windows 10 Home 10.0.1.18362

**Issue description:** When using Nodes containing TextureButtons with overlapping areas, the first button to receive input should be determined by which is lowest in the tree. When reordering these nodes (for instance, to account for changed positions along the y axis), move_child is not sufficient to make Godot recalculate overlapping priority -- it will place the nodes into the correct hierarchy and draw them correctly, but overlapping buttons will behave inconsistently. If this sorting step is completed as part of the _ready() method it will correctly behave, but at any time following that it is necessary to remove and re-add the texturebutton with remove_child and add_child to make it function correctly. This makes me think it's something to do with an update function or tree entering signal that add_child has but move_child lacks. It just seems weird to me that re-adding a node is the way to fix this, there must be some other solution for updating the node hierarchy.

**Steps to reproduce:**

Create a scene with a main node and several child nodes that each contain a TextureButton that overlaps with at least one other Texturebutton.
Sort the nodes by y position and reorder them accordingly at any point **after** _ready() has been called.
Click on overlapped portions of buttons. Some buttons 'beneath' others (higher in the tree) will receive the signal instead of the visually intended button.

**Minimal reproduction project:**
[ProblemReproduction1.zip](https://github.com/godotengine/godot/files/4269744/ProblemReproduction1.zip)

Open and run the project. Press 'R' to shuffle and sort the nodes by height. Clicking on overlapped portions will behave contrary to the expected results provided by the tree output in the console, i.e the click priority will always be Blue , Green , Red. 

Uncomment the refreshNode() call in sortNodes() in the SortingNode.

Repeat the process, noting how now the overlapping is correct and the physically lowest node is always the 'top' button and gets any clicks, even when overlapping.
Repository: godot
Issue: Input.set_use_accumulated_input(false) broken?
Labels: bug,platform:windows,topic:input

**Godot version:**
v3.2.stable.official

**OS/device including version:**
Linux Mint Cinnamon 19.3
also tested on: Windows 10 some new build

**Issue description:**
Input is only sent once per frame by _input(event), but i want to use the input in the moment it is triggered, without having to wait to the next frame.
So I tried "Input.set_use_accumulated_input(false)", but _input(event) is still called once per frame.

Is this a bug or is set_use_accumulated_input supposed to do something else?
There is not much in the documentation about this method.

**Steps to reproduce:**
The minimal project is set to use vsync and count the time in micro-seconds from the start of the last frame to the delivery of the input event. The measurement is displayed at the top lefthand side of the window.
The event is set to InputEventMouseButton but can also be changed.
Input.set_use_accumulated_input() is set to false.
You can set vsync off, but with vsync on it's easier to see, that the time is roughly the same with every mouse-button pressed, instead of evenly distributed from 0 to the frametime in µseconds.
If it's the same all the time, that means _input(event) is only called once per frame.
On a 60Hz display, vsync enabled, the measured time is, but shouldn't be all the time, about 16667µs.

**Minimal reproduction project:**
[inputLatency.zip](https://github.com/godotengine/godot/files/4269822/inputLatency.zip)