sharjeelyunus/github-issues-dataset huggingface dataset:
Repository: kubernetes
Issue: Allow exposing status.containerStatuses[*].imageID through Downward API
Labels: sig/node,kind/feature,priority/important-longterm,lifecycle/frozen,needs-triage

**What would you like to be added**:

It would be great if `status.containerStatuses[0].imageID` and `status.containerStatuses[0].image` could be exposed through Downward API and passed as an environment variable. That would allow the container to obtain information about which exactly digest of the image it is running, which can then be useful for any logging from that container.

**Why is this needed**:

It is useful for the container to know which exactly version of the image it is running. By allowing passing the image and digest/ID to the container, this is achievable.
Repository: pytorch
Issue: The speed of `torch.einsum` and `torch.matmul` when using `fp16` is slow
Labels: module: performance,module: cuda,triaged,module: linear algebra

## 🐛 Bug

I found that the speed of `torch.einsum` when using fp16 is much slower than using fp32.

when the shapes of inputs are (a,b,c) and (a,c,d), `matmul` became much slower as well.

## To Reproduce
```python
import os
os.environ['CUDA_VISIBLE_DEVICES']='0'
import torch
from time import time

a = torch.empty(24,32,40,48, dtype=torch.float32).to('cuda')
b = torch.empty(64,32,40,48, dtype=torch.float32).to('cuda')
c = torch.empty(40,80,24, dtype=torch.float32).to('cuda')
d = torch.empty(40,24,16, dtype=torch.float32).to('cuda')

st = time()
for _ in range(1000):
    c.matmul(d)
print(time()-st)

st = time()
for _ in range(1000):
    torch.einsum('ibnd,jbnd->ijbn', a, b)
print(time()-st)

a = torch.empty(24,32,40,48, dtype=torch.float16).to('cuda')
b = torch.empty(64,32,40,48, dtype=torch.float16).to('cuda')
c = torch.empty(40,80,24, dtype=torch.float16).to('cuda')
d = torch.empty(40,24,16, dtype=torch.float16).to('cuda')

st = time()
for _ in range(1000):
    torch.matmul(c,d)
print(time()-st)

st = time()
for _ in range(1000):
    torch.einsum('ibnd,jbnd->ijbn', a, b)
print(time()-st)
```
Steps to reproduce the behavior:

just run it


## Expected behavior

the speed of fp16 is much much slower than fp32.
```shell
~# python debug_fp32.py
0.027073144912719727
0.04812788963317871
~# python debug_fp16.py
0.3655080795288086
10.85773253440857
```
## Environment

v100, cuda 10.1, pytorch 1.1



cc @ngimel @vincentqb @vishwakftw @jianyuh @nikitaved @pearu @VitalyFedyunin
Repository: vue-element-admin
Issue: 有咩有谁在这个项目当中引用过el-image？我引入el-image会报组件注册不正确的错误
Labels: feature

## Question（提问）
有咩有谁在这个项目当中引用过el-image？我引入el-image会报组件注册不正确的错误
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#### Other relevant information（格外信息）
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Repository: flutter
Issue: Refactor logs to operate on functionality instead of log level
Labels: team,framework,P3,team-framework,triaged-framework

Refactor logs to operate on functionality instead of log level, e.g.,

`Log.debugPrintSystemChannels();`
`Log.debugPrintLifecycle();`
etc.
Repository: pytorch
Issue: creation of a tensor from a numba.cuda array
Labels: feature,low priority,triaged,module: numba

## 🚀 Feature
<!-- A clear and concise description of the feature proposal -->
Having `torch.from_numba(cuda_arr)` can be useful in many cases.  
## Motivation
With the easy to use APIs in numba, I would like to do the preprocessing on gpu and then pass resultant gpu arrays to pytorch model. But currently, we have to convert these gpu arrays to numpy and then use the `torch.from_numpy()` API. 
<!-- Please outline the motivation for the proposal. Is your feature request related to a problem? e.g., I'm always frustrated when [...]. If this is related to another GitHub issue, please link here too -->

## Pitch

<!-- A clear and concise description of what you want to happen. -->

## Alternatives

<!-- A clear and concise description of any alternative solutions or features you've considered, if any. -->

## Additional context
```Python
import numba 
import torch
cuda_arr = numba.cuda.device_array(shape=(5,4))
# here, we need to perform this unnecessary conversion from gpu->cpu
numpy_arr = cuda_arr.copy_to_host()
gpu_tensor = torch.from_numpy(numpy_arr)
```
<!-- Add any other context or screenshots about the feature request here. -->
Repository: create-react-app
Issue: create-react-app freezes at extracting "rxjs"
Labels: issue: bug

![image](https://user-images.githubusercontent.com/44221538/61531295-0b901200-aa44-11e9-8b04-3b4683a23c52.png)

#ITS NOW SHOWING TWO LOADERS CAN U PLEASE HELP ME WITH IT ????
![image](https://user-images.githubusercontent.com/44221538/61531396-4eea8080-aa44-11e9-8669-e37064327db3.png)


##ITS NOW 2 DAYS BUT THIS ISSUE IS COMING UP AGAIN AND AGAIN . 
Please help ...
Repository: ant-design
Issue: TreeSelect的节点提供连接线以及目录树
Labels: help wanted,Inactive

- [ ] I have searched the [issues](https://github.com/ant-design/ant-design/issues) of this repository and believe that this is not a duplicate.

### What problem does this feature solve?
目前的TreeSelect展开的树形列表虽然功能上已经基本完善，但是在某些情况下用户体验并不是很好，比如在节点数量比较多，节点层数比较复杂的情况下只用△的展示方式并不友好，所以希望提供像Tree组件的showLine以及DirectoryTree的可选方式展示。

### What does the proposed API look like?
<TreeSelect    showLine />    
参数：showLine	    
说明：是否展示连接线	    
类型：boolean	
默认值：false

const {  DirectoryTreeSelect } = TreeSelect;      
<DirectoryTreeSelect />


<!-- generated by ant-design-issue-helper. DO NOT REMOVE -->
Repository: TypeScript
Issue: checkJs should recognize properties assigned with lodash
Labels: Suggestion,Awaiting More Feedback

<!-- 🚨 STOP 🚨 𝗦𝗧𝗢𝗣 🚨 𝑺𝑻𝑶𝑷 🚨

Half of all issues filed here are duplicates, answered in the FAQ, or not appropriate for the bug tracker. Please read the FAQ first, especially the "Common Feature Requests" section.

-->

## Search Terms

<!-- List of keywords you searched for before creating this issue. Write them down here so that others can find this suggestion more easily -->
js, lodash, properties

## Suggestion

<!-- A summary of what you'd like to see added or changed -->
Recognize properties of some object when using lodash assign  method

## Use Cases

<!--
What do you want to use this for?
What shortcomings exist with current approaches?
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Any initalization of an object using:
``` js
_.assign(obj, { ...someProps });

// Instead of
this.oneProp = oneProp;
this.anotherProp = anotherProp;
```


## Examples

<!-- Show how this would be used and what the behavior would be -->
![image](https://user-images.githubusercontent.com/31735779/61537520-c0f3a300-aa0d-11e9-9588-7f7e6c55dad6.png)


## Checklist

My suggestion meets these guidelines:

* [x] This wouldn't be a breaking change in existing TypeScript/JavaScript code
* [x] This wouldn't change the runtime behavior of existing JavaScript code
* [ ] This could be implemented without emitting different JS based on the types of the expressions
* [ ] This isn't a runtime feature (e.g. library functionality, non-ECMAScript syntax with JavaScript output, etc.)
* [x] This feature would agree with the rest of [TypeScript's Design Goals](https://github.com/Microsoft/TypeScript/wiki/TypeScript-Design-Goals).
Repository: pytorch
Issue: Inconsistent axis argument names in torch.diagonal and torch.transpose
Labels: module: docs,low priority,triaged

`torch.diagonal` uses `dim1` and `dim2` while `torch.transpose` uses `dim0` and `dim1`.
Repository: go
Issue: cmd/compile: malformed DWARF ranges (child not contained in parent)
Labels: NeedsFix,Debugging

<!-- Please answer these questions before submitting your issue. Thanks! -->

### What version of Go are you using (`go version`)?

<pre>
$ go version
go version devel +79bb1a3653 Thu Jul 18 10:16:59 2019 -0400 linux/amd64
</pre>

### Does this issue reproduce with the latest release?

Yes

### What operating system and processor architecture are you using (`go env`)?

<details><summary><code>go env</code> Output</summary><br><pre>
$ go env
linux/amd64
</pre></details>

### What did you do?

Build this program:

<pre>
package main

import "C"
import "log"

func main() {
	log.Printf("foo")
}
</pre>

in the usual way, e.g. "go build main.go". Then run

<pre>
llvm-dwarfdump -verify -verbose main
</pre>

to check the resulting dwarf.

### What did you expect to see?

Clean run

### What did you see instead?

A number of errors of the form:  "error: DIE address ranges are not contained in its parent's ranges:"

Here is one instance:

```
0x00006511: DW_TAG_inlined_subroutine
              DW_AT_abstract_origin	(0x00000000000014b8 "runtime.add")
              DW_AT_ranges	(0x00001370
                 [0x0000000000004984, 0x0000000000004988)
                 [0x00000000000049f9, 0x00000000000049fe))
              DW_AT_call_file	("/ssd2/go/src/runtime/chan.go")
              DW_AT_call_line	(121)
```
which is contained in this DIE:

```
0x000064e4: DW_TAG_inlined_subroutine
              DW_AT_abstract_origin	(0x0000000000001696 "runtime.chanbuf")
              DW_AT_low_pc	(0x000000000000497c)
              DW_AT_high_pc	(0x0000000000004984)
              DW_AT_call_file	("/ssd2/go/src/runtime/chan.go")
              DW_AT_call_line	(484)
```
so definitely an inconsistency. Note that the top-level parent is:

```
0x0000640e: DW_TAG_subprogram
              DW_AT_name	("runtime.chanrecv")
              DW_AT_low_pc	(0x00000000000048a0)
              DW_AT_high_pc	(0x0000000000004f52)
              DW_AT_frame_base	(DW_OP_call_frame_cfa)
              DW_AT_decl_file	("/ssd2/go/src/runtime/chan.go")
              DW_AT_external	(0x01)
```

There is nothing in the DWARF spec as far as I know that mandates this sort of address range nesting consistency, but I think it would probably be nice if a given inlined subroutines ranges were completely nested inside the parent DIE.
Repository: pytorch
Issue: update docs that sorting is not needed in 
Labels: module: docs,module: rnn,triaged

## 📚 Documentation

based on dicussion here:

https://discuss.pytorch.org/t/why-lengths-should-be-given-in-sorted-order-in-pack-padded-sequence/3540/10

`pack_padded_sequence`

does not need sorting anymore, so perhaps the fact the docs mention sorting at all should be deleted. 

> For unsorted sequences, use enforce_sorted = False. If enforce_sorted is True, the sequences should be sorted by length in a decreasing order, i.e. input[:,0] should be the longest sequence, and input[:,B-1] the shortest one. enforce_sorted = True is only necessary for ONNX export.
Repository: youtube-dl
Issue: [ARD Radio] Audiothek Site support request
Labels: site-support-request

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## Checklist

<!--
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- Make sure that all provided video/audio/playlist URLs (if any) are alive and playable in a browser.
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- Finally, put x into all relevant boxes (like this [x])
-->

- [x] I'm reporting a new site support request
- [x] I've verified that I'm running youtube-dl version **2019.07.16**
- [x] I've checked that all provided URLs are alive and playable in a browser
- [x] I've checked that none of provided URLs violate any copyrights
- [x] I've searched the bugtracker for similar site support requests including closed ones


## Example URLs

<!--
Provide all kinds of example URLs support for which should be included. Replace following example URLs by yours.
-->

- Single audio: https://www.ardaudiothek.de/lesungen/manfred-krug-liest-die-kuh-im-propeller-von-michail-soschtschenko/64767418


## Description

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Provide any additional information.
If work on your issue requires account credentials please provide them or explain how one can obtain them.
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Can you please add support for ARD Audiothek (ARD Radio)?
Repository: go
Issue: cmd/vet: reject flag.Parse during func init
Labels: help wanted,NeedsFix,early-in-cycle,Analysis

In #31859, @cespare suggested rejecting flag.Parse during func init, which is always incorrect (other packages not yet initialized may want to define flags). 

We could add a special runtime hook of some kind to allow flag to see whether main.main has started, but that would be unfortunate.
There also may be lots of code in the wild that does parse flags during init and kind of works out OK, and if it's working well enough we don't want to break it unnecessarily.

A vet check, on by default during go test, seems like the perfect compromise to me.
Repository: flutter
Issue: Expose hot restart to flutter_driver
Labels: c: new feature,tool,t: flutter driver,P3,team-tool,triaged-tool

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## Use case

Writing e2e tests could be more automated, and less time consuming, if we could wipe app state at the end of any given test. Often, we don't want the state from the previous test to carry over to a new test or workflow that we're testing.

## Proposal

Expose a method on `FlutterDriver` that performs a hot restart on the app that's running for the driver. (i.e. FlutterDriver.restartApp`), or add a flag to the driver that can configure it to restart at the end of every test. (i.e. `FlutterDriver.restartAfterEachTest = true`).

### more context

My team is re-writting our company's app in Flutter from iOS. The QAEs are attempting to port the E2E tests from our current app with Flutter Driver. Currently, they're written using cucumber. 

There actually is a cucumber port on Pub that offers this feature. It accomplishes this by writing an "R" to stdin to the vm running the app while driver is running. That library isn't great for our use case, I'm just pointing it out for context
Repository: flutter
Issue: Initial image load is slow when AssetManifest.json is larger than 10KB
Labels: framework,c: performance,a: assets,customer: google,a: images,a: build,P2,team-framework,triaged-framework

When AssetManifest.json is larger than 10KB, [AssetBundle.loadString](https://github.com/flutter/flutter/blob/master/packages/flutter/lib/src/services/asset_bundle.dart#L70) will spawn a new isolate to perform utf8 decoding, and that is taking 1.5 - 3 seconds on my test device (Pixel 2) in debug mode.

Release mode is much better, takes only ~150ms.

This is affecting our internal customers because the slow image load makes the scuba tests flaky.
Repository: TypeScript
Issue: `this` and `typeof` are not type keywords in completions
Labels: Bug,Help Wanted,Domain: Completion Lists

In services/utilities.ts:1213, `this` and `typeof` are not in

```ts
    export const typeKeywords: ReadonlyArray<SyntaxKind> = [
        SyntaxKind.AnyKeyword,
        SyntaxKind.BigIntKeyword,
        SyntaxKind.BooleanKeyword,
        SyntaxKind.FalseKeyword,
        SyntaxKind.KeyOfKeyword,
        SyntaxKind.NeverKeyword,
        SyntaxKind.NullKeyword,
        SyntaxKind.NumberKeyword,
        SyntaxKind.ObjectKeyword,
        SyntaxKind.ReadonlyKeyword,
        SyntaxKind.StringKeyword,
        SyntaxKind.SymbolKeyword,
        SyntaxKind.TrueKeyword,
        SyntaxKind.VoidKeyword,
        SyntaxKind.UndefinedKeyword,
        SyntaxKind.UniqueKeyword,
        SyntaxKind.UnknownKeyword,
    ];
```

even though they are type keywords. Unfortunately, adding them breaks some tests to do with find-all-refs with global this -- patterns like `function f(this) { this }` start identifying the `this` inside the function as the global `this`.
Repository: pytorch
Issue: Versioning for libtorch nightlies
Labels: module: binaries,module: build,triaged,better-engineering

## 🚀 Feature
<!-- A clear and concise description of the feature proposal -->

Currently, all the nightly builds have the same `CAFFE2_VERSION` even though there may be major changes between them.

For example, both `1.2.0.dev20190601` and `1.2.0.dev20190717` list the version as `10200`, but there are many breaking changes between the two:
- `torch::jit::load` returned a shared pointer in the past and no longer does
- Getting a schema requires `method.function().getSchema()` instead of `method.getSchema()`
- A `ClassType` argument is added as the first input to every model
- Lots of changes in `List`/`GenericList` and `Dict`/`GenericDict`

## Motivation

<!-- Please outline the motivation for the proposal. Is your feature request related to a problem? e.g., I'm always frustrated when [...]. If this is related to another GitHub issue, please link here too -->

Since torch development is moving pretty quickly, it's important to be able to support one or two nightlies between major releases. This is difficult because there doesn't appear to be a good way to differentiate between versions.

## Pitch

<!-- A clear and concise description of what you want to happen. -->

Can the nightly builds define an additional version? Maybe something like this:

```
#define CAFFE2_NIGHTLY_VERSION 20190717
```

## Additional context

<!-- Add any other context or screenshots about the feature request here. -->

There's a comment that mentions a versioning strategy. Is this still correct?

https://github.com/pytorch/pytorch/blob/693871ded3d3c643d7d57b990fc415198392b5f0/caffe2/core/macros.h.in#L8-L9
Repository: pytorch
Issue: Test utility for non-contiguous tensors
Labels: module: tests,triaged,enhancement

Currently in tests, non-contiguous tensors are mostly created in a homebrewed way, e.g., via transpose. This may work for now but it seems relying too much on the underlying implementation which guarantees nothing about contiguity. It would be nice if there is a utility that consistently produces non-contiguous tensors for testing purposes.
Repository: TypeScript
Issue: Optionally provide path/link to file with transpilation error
Labels: Suggestion,Awaiting More Feedback

I see this in my terminal:

<kbd>
<img width="975" alt="Screen Shot 2019-07-19 at 1 04 27 PM" src="https://user-images.githubusercontent.com/11139560/61562857-18523d00-aa27-11e9-8a2b-67025d2dab95.png">
</kbd>

-----

I have two feature requests:

1. for us hard of seeing people, it's _really_ hard to read the cyan and yellow color in a light terminal.
Is there some way to turn on darker colors - by passing a dark/light option to pretty?

2. It would be awesome if the transpiler could include the path to the file in the terminal. My editor is cool and if I click the file path in the terminal it will open the file.


My tsconfig.json is:

```

    {
      "compilerOptions": {
        "outDir": "dist",
        "allowJs": false,
        "pretty": true,   // << makes it pretty, but I can't read in a light-colored terminal
        "resolveJsonModule": true,
        "sourceMap": false,
        "skipLibCheck": true,
        "rootDir": "src",
        "declaration": false,
        "baseUrl": ".",
        "target": "es2018",
        "module": "commonjs",
        "noImplicitAny": true,
        "removeComments": true,
        "allowUnreachableCode": true,
        "lib": [
          "es2017",
          "es2018"
        ]
      },
      "compileOnSave": false,
      "include": [
        "src"
      ]
    }
```




  [1]: https://i.stack.imgur.com/bssEZ.png
Repository: godot
Issue: Can't change color space of vertex colors in GLES2 using a SpatialMaterial
Labels: bug,topic:rendering,confirmed,topic:3d

**Godot version:**
3.1 stable


**OS/device including version:**
GNU/Linux x64


**Issue description:**
Vertex colors look very different in GLES2 and the "Is Srgb" toggle in the material doesn't do anything

Note: the "Is Srgb" toggle does make a difference in GLES3, but the colors look right when it's off.

Edit: This happens when I export the model in the gltf2 format, when I export it in .dae with the default collada exporter it looks bad in gles3 without "Is Srgb" turned on so I guess the issue is that you can't change the color space of vertex colors in GLES2.

Comparisons:

Blender
![image](https://user-images.githubusercontent.com/18746022/61571797-3a1de500-aa64-11e9-87cd-a79e1a18c186.png)

Godot(GLES2)
![image](https://user-images.githubusercontent.com/18746022/61571846-c203ef00-aa64-11e9-85bc-baac40db2092.png)

Godot(GLES3)
![image](https://user-images.githubusercontent.com/18746022/61571909-448cae80-aa65-11e9-8098-d30729be6d5b.png)