sharjeelyunus/github-issues-dataset huggingface dataset:
Repository: rust
Issue: Suggestion for a typoed crate or module results in compile error
Labels: A-diagnostics,T-compiler,A-suggestion-diagnostics,D-papercut,D-invalid-suggestion

This issue is 

I implemented a suggestion for typoed crate or module in #89347. However there are still some edge cases.

Given the following code: <!-- Please provide a link to play.rust-lang.org -->

https://play.rust-lang.org/?version=nightly&mode=debug&edition=2018&gist=36133bfa20fc000bce25b7b1ea075df9

The current output is:

```
error[E0433]: failed to resolve: use of undeclared crate or module `my_cor`
  --> $DIR/extern-prelude-from-opaque-fail.rs:10:5
   |
LL |     my_cor::mem::drop(0);
   |     ^^^^^^ use of undeclared crate or module `my_cor`
   |
help: there is a crate or module with a similar name
   |
LL |     my_core::mem::drop(0);
   |     ~~~~~~~

error: aborting due to previous error

For more information about this error, try `rustc --explain E0433`.
```
However if you apply this suggestion, you get a compiler error like the following.

```
error[E0433]: failed to resolve: use of undeclared crate or module `my_core`
  --> $DIR/extern-prelude-from-opaque-fail.rs:10:5
   |
LL |     my_core::mem::drop(0);
   |     ^^^^^^^ use of undeclared crate or module `my_core`

error: aborting due to previous error

For more information about this error, try `rustc --explain E0433`.
```

<!-- The following is not always necessary. -->
Ideally the output should look like:

The compiler shouldn't suggest a crate or module name which you can't use.

```
error[E0433]: failed to resolve: use of undeclared crate or module `my_cor`
  --> $DIR/extern-prelude-from-opaque-fail.rs:10:5
   |
LL |     my_cor::mem::drop(0);
   |     ^^^^^^ use of undeclared crate or module `my_cor`
   |

error: aborting due to previous error

For more information about this error, try `rustc --explain E0433`.
```

<!--
If the problem is not self-explanatory, please provide a rationale for the
change.
-->

<!--
If dramatically different output is caused by small changes, consider also
adding them here.

If you're using the stable version of the compiler, you should also check if the
bug also exists in the beta or nightly versions. The output might also be
different depending on the Edition.
-->

https://github.com/rust-lang/rust/pull/89347#issuecomment-932277226 might help you.

Other things to do: https://github.com/rust-lang/rust/pull/89347#discussion_r721353137
Repository: go
Issue: proposal: testing: custom mutator support for fuzzing
Labels: Proposal,NeedsInvestigation,FeatureRequest,fuzz

As the official fuzzer implementation provided by golang, the native fuzzer should be well suited for various usage scenarios. However, currently native fuzzers only support general mutation algorithms for built-in types. Therefore, in many cases, the native fuzzer cannot efficiently generate test inputs. For example, when testing a DSL parser, the mutator will generate a large amount of output that cannot pass the syntax or semantic check. A possible solution is to provide support for custom mutators, so that users can implement custom mutators for various fuzz targets and reuse other parts of the native fuzzer.

I tried on the existing code and designed the following interface:
```
 type CustomMutator interface {
     Marshal() ([]byte, error)
     Unmarshal([]byte) error
     Mutate() error
 }
```
The object that implements the above interface can be passed as an argument to the `testing.F.Fuzz` method, and it will call the `Mutate` method to use the custom mutation algorithm. The `Marshal` and `Unmarshal` methods ensure that it can be imported/exported to a corpus file.

I think supporting custom mutator will bring the following benefits:
- the usage scenarios of native fuzzer are expanded
- it is more convenient for the community to test and optimize mutation algorithms
- the interface of custom mutator is very similar to the struct mutation interface mentioned in the [draft proposal](https://go.googlesource.com/proposal/+/master/design/draft-fuzzing.md#fuzz-target), so implementing a custom mutator may be a way to support struct mutation

In addition, custom mutator will also bring some side effects, such as the custom mutator code will be instrumented, which may affect performance and the accuracy of coverage statistics.

/cc @jayconrod
Repository: node
Issue: Assertion `(write_req_.result) >= (0)' failed
Labels: linux

### Version

v16.10.0

### Platform

Linux af87af56-9877-4f08-60c5-f271 5.4.0-84-generic #94~18.04.1-Ubuntu SMP Thu Aug 26 23:17:46 UTC 2021 x86_64 x86_64 x86_64 GNU/Linux

### Subsystem

_No response_

### What steps will reproduce the bug?

Running our server app with `node --trace-event-categories v8,node,node.async_hooks,node.promises.rejections` flags.  

### How often does it reproduce? Is there a required condition?

When `node.promises.rejections` enabled, server crashes at least once per hour with this error.

### What is the expected behavior?

Printing promise rejection trace, when rejection occurs.

### What do you see instead?

Node crashes

```
node[137]: ../src/tracing/node_trace_writer.cc:196:void node::tracing::NodeTraceWriter::AfterWrite(): Assertion `(write_req_.result) >= (0)' failed.
1: 0x5578c3cff280 node::Abort() [node]
2: 0x5578c3cff314  [node]
3: 0x5578c3e1a654  [node]
4: 0x5578c487db64  [node]
5: 0x5578c48834f6  [node]
6: 0x5578c489749d  [node]
7: 0x5578c4883e2a uv_run [node]
8: 0x7fe3b1e9f6db  [/lib/x86_64-linux-gnu/libpthread.so.0]
9: 0x7fe3b1bc871f clone [/lib/x86_64-linux-gnu/libc.so.6]
Aborted
```

### Additional information

_No response_
Repository: pytorch
Issue: Specifying USE_VULKAN=0 in launching build_android.sh does not disable Vulkan
Labels: module: build,triaged,module: vulkan

## 🐛 Bug

<!-- A clear and concise description of what the bug is. -->
First mentioned here: https://discuss.pytorch.org/t/about-build-android-sh-lite-and-nnapi/133581
It is not possible to disable vulkan when using the build_android.sh script. The code only allow to activate the flag, but the flag is not activated for ANDROID builds cmake activate it automatically if not set to zero.

## To Reproduce

Steps to reproduce the behavior:
1. Launch USE_VULKAN=0 ANDROID_ABI=arm64-v8a ANDROID_NDK=<path_to_ndk> scripts/build_android.sh
2. Interrupt the build process after cmake configuration is complete, USE_VULKAN is set true in the cmake cache

<!-- If you have a code sample, error messages, stack traces, please provide it here as well -->

## Expected behavior

Vulkan should be disabled
I have a fix ready, but I have not be able to put up a pull request (remote: Permission to pytorch/pytorch.git denied to caraffi.)
```
diff --git a/scripts/build_android.sh b/scripts/build_android.sh
index daad46e8fb..4dcb00becb 100755
--- a/scripts/build_android.sh
+++ b/scripts/build_android.sh
@@ -147,7 +147,7 @@ if [ "${ANDROID_DEBUG_SYMBOLS:-}" == '1' ]; then
 fi
 
 if [ -n "${USE_VULKAN}" ]; then
-  CMAKE_ARGS+=("-DUSE_VULKAN=ON")
+  CMAKE_ARGS+=("-DUSE_VULKAN=${USE_VULKAN}")
 fi
 
 # Use-specified CMake arguments go last to allow overridding defaults
```
## 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).

The error can be reproduced for 1.9.0, 1.9.1, 1.10.0-rc2 and master

Collecting environment information...
PyTorch version: N/A
Is debug build: N/A
CUDA used to build PyTorch: N/A
ROCM used to build PyTorch: N/A

OS: Ubuntu 20.04.3 LTS (x86_64)
GCC version: (Ubuntu 9.3.0-17ubuntu1~20.04) 9.3.0
Clang version: Could not collect
CMake version: version 3.21.3
Libc version: glibc-2.31

Python version: 3.8.10 (default, Sep 28 2021, 16:10:42)  [GCC 9.3.0] (64-bit runtime)
Python platform: Linux-5.11.0-37-generic-x86_64-with-glibc2.29
Is CUDA available: N/A
CUDA runtime version: Could not collect
GPU models and configuration: Could not collect
Nvidia driver version: Could not collect
cuDNN version: Could not collect
HIP runtime version: N/A
MIOpen runtime version: N/A

Versions of relevant libraries:
[pip3] numpydoc==0.7.0
[conda] Could not collect


## Additional context

<!-- Add any other context about the problem here. -->


cc @malfet @seemethere
Repository: pytorch
Issue: `torch.fx.replace_pattern` doesn't work with untraceable wrapped functions
Labels: triaged,module: fx

## 🐛 Bug

`torch.fx.replace_pattern` doesn't seem to work when we have untraceable functions that are wrapped with `torch.fx.wrap`.

It looks like while doing `torch.fx.replace_pattern`, the functions that have been wrapped are not passed-through and are instead re-traced fully.

I'm running on PyTorch `1.11.0.dev20210930` (from last week)

## To Reproduce

```python
import torch
import torch.fx

# untraceable function
@torch.fx.wrap
def my_func(x):
    a = torch.empty(x.shape)  # not FX-traceable
    a.bernoulli_(0.5)
    return x


def my_func_2(x):
    return x * 2


# my model
def m(x):
     return x + my_func(x)

# we can properly trace it
mm = torch.fx.symbolic_trace(m)
# and we can also run it properly
mm(torch.rand(2))

print(mm.code)

# but this fails
torch.fx.replace_pattern(mm, my_func, my_func_2)

print("After replacement")
print(mm.code)
```
This is the output of the snippet, which fails at `replace_pattern`

```python
torch.fx._symbolic_trace.wrap("__main___my_func")

def forward(self, x):
    my_func = __main___my_func(x)
    add = x + my_func;  x = my_func = None
    return add

Traceback (most recent call last):
  File "testing.py", line 25, in <module>
    torch.fx.replace_pattern(mm, my_func, identity)
  File "/Users/fmassa/anaconda3/lib/python3.8/site-packages/torch/fx/subgraph_rewriter.py", line 251, in replace_pattern
    pattern_graph = symbolic_trace(pattern).graph
  File "/Users/fmassa/anaconda3/lib/python3.8/site-packages/torch/fx/_symbolic_trace.py", line 907, in symbolic_trace
    graph = tracer.trace(root, concrete_args)
  File "/Users/fmassa/anaconda3/lib/python3.8/site-packages/torch/fx/_symbolic_trace.py", line 615, in trace
    self.create_node('output', 'output', (self.create_arg(fn(*args)),), {},
  File "testing.py", line 7, in my_func
    a = torch.empty(x.shape)
TypeError: empty(): argument 'size' (position 1) must be tuple of ints, not Attribute
```

which is the same type of error we would get if we tried to symbolically trace `my_func` without wrapping it first.

Originally reported by @datumbox 

cc @ezyang @SherlockNoMad
Repository: yt-dlp
Issue: [Feature Request] Provide type of URL in JSON output
Labels: enhancement

## Checklist
- [x] I'm reporting a feature request
- [x] I've verified that I'm running yt-dlp version **2021.09.25**
- [x] I've searched the bugtracker for similar feature requests including closed ones


## Description

I'm using the following command to query video/playlist information:
python -m yt_dlp -J --flat-playlist URL

In case the URL  refers to a video and a playlist, it returns JSON for playlist. I would like this JSON to contain information indicating if the URL refers to a video also. 

For now as a workaround I have to make a second request with the following command:
python -m yt_dlp -J --flat-playlist --no-playlist URL

If it returns the same JSON - it's playlist only URL. Otherwise, it's a video also.
Repository: flutter
Issue: Cannot Scroll `PageView` while long press is active in a `GestureDetector`
Labels: framework,f: gestures,has reproducible steps,P2,found in release: 2.5,found in release: 2.6,team-framework,triaged-framework


## Steps to Reproduce
1. Create a app with pageview and gesture detector in child pages
2. try onLongPress callback in gesturedetector 
3. on long pressing the child widget, if u move the hand in the screen it wont react to pageview swipe to next page

**Expected results:** <!-- what did you want to see? -->
both the gesture detector and pageview should react 
**Actual results:** <!-- what did you see? -->
only gesture detector detecting onlongpress and pageview refuse to swipe page.


**Reproducible Code:**
````dart
import 'dart:developer';

import 'package:flutter/material.dart';

void main() {
  runApp(const MyApp());
}

class MyApp extends StatelessWidget {
  const MyApp({Key? key}) : super(key: key);

  @override
  Widget build(BuildContext context) {
    return MaterialApp(
      title: 'Flutter Demo',
      theme: ThemeData(
        primarySwatch: Colors.blue,
      ),
      home: const MyHomePage(),
    );
  }
}

class MyHomePage extends StatefulWidget {
  const MyHomePage({Key? key}) : super(key: key);

  @override
  _MyHomePageState createState() => _MyHomePageState();
}

class _MyHomePageState extends State<MyHomePage> {
  @override
  Widget build(BuildContext context) {
    return Scaffold(
      body: PageView(
        scrollDirection: Axis.vertical,
        children: [
          Container(
            color: Colors.blue,
            child: const CustomBox(),
          ),
          Container(
            color: Colors.red,
            child: const CustomBox(),
          ),
          Container(
            color: Colors.green,
            child: const CustomBox(),
          ),
          Container(
            color: Colors.yellow,
            child: const CustomBox(),
          ),
        ],
      ),
    );
  }
}

class CustomBox extends StatelessWidget {
  const CustomBox({Key? key}) : super(key: key);

  @override
  Widget build(BuildContext context) {
    return Center(
      child: GestureDetector(
        onLongPress: () {
          log('Long Pressed this');
        },
        child: Container(
          height: MediaQuery.of(context).size.width / 2,
          width: MediaQuery.of(context).size.width / 2,
          color: Colors.white,
        ),
      ),
    );
  }
}
````
Repository: pytorch
Issue: Move the `queue_callback()` API out of `Variable._execution_engine` and into a public API
Labels: module: autograd,triaged,better-engineering,actionable

As per title.

I think the `autograd.graph` namespace is a good place to put it?

cc @ezyang @albanD @zou3519 @gqchen @pearu @nikitaved @soulitzer @Lezcano @Varal7
Repository: godot
Issue: Ruler does not display radians for angles.
Labels: discussion,topic:editor

### Godot version

3.0+

### System information

N/A

### Issue description

The ruler tool displays pixels, units and degrees. It does not display radians. This seems like a bit of an odd shortcoming seeing as a lot Godot's functions related to angles use radians.

![53477_demonstrator](https://user-images.githubusercontent.com/324679/136224228-c3a3ba5c-87ca-43ff-8598-281763ce5b93.png)

### Steps to reproduce

Use the ruler tool.

### Minimal reproduction project

N/A
Repository: youtube-dl
Issue: freesportsplayer.tv
Labels: site-support-request

## Checklist

- [x] I'm reporting a new site support request
- [x] I've verified that I'm running youtube-dl version **2021.06.06**
- [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

- Single video: https://www.freesportsplayer.tv/ondemand/1015154-kotv-classics
- Single video: https://www.freesportsplayer.tv/ondemand/1015156-new-york-fc-v-nashville

## Description

Requires a login; free to register. Would be great to have support for this site for offline viewing. Any questions, let me know, and thanks!
Repository: PowerToys
Issue: PowerToys Run Hint with starting a keyword
Labels: Idea-Enhancement,Product-PowerToys Run,Run-Plugin,Needs-Team-Response

### Description of the new feature / enhancement

lets say we type ? and will show us  ?file searching mode etc
![image](https://user-images.githubusercontent.com/2059694/136234055-48c2ca08-5cf3-4dac-8714-09f5c3348b0b.png)

I think this hint will make fresh user knowing more what they are doing

### Scenario when this would be used?

any scenario, in particular for new user

### Supporting information

_No response_
Repository: go
Issue: testing: minimization takes longer than expected for very large []byte/string
Labels: NeedsFix,fuzz

To reproduce, fuzz the following target with `go test -fuzz Fuzz`
```
func FuzzFoo(f *testing.F) {
	f.Fuzz(func(t *testing.T, b []byte) {
		if len(b) > 10000 {
			panic("bad")
		}
	})
}
```

The following output will occur:
```
fuzz: elapsed: 0s, gathering baseline coverage: 0/1 completed
fuzz: elapsed: 0s, gathering baseline coverage: 1/1 completed, now fuzzing with 8 workers
fuzz: minimizing 34995-byte crash input...
fuzz: elapsed: 3s, execs: 13821 (4604/sec), new interesting: 0 (total: 1)
fuzz: elapsed: 6s, execs: 13821 (2303/sec), new interesting: 0 (total: 1)
fuzz: elapsed: 9s, execs: 13821 (1535/sec), new interesting: 0 (total: 1)
```

Notice that it found a crash and indicated that it would minimize it, but ~~then just proceeded with fuzzing anyway~~ (Correction: It didn't keep fuzzing, it just kept updating the log. It looks like the worker hung). If you press Ctrl^C, it exits and writes the crasher:
```
fuzz: elapsed: 0s, gathering baseline coverage: 0/1 completed
fuzz: elapsed: 0s, gathering baseline coverage: 1/1 completed, now fuzzing with 8 workers
fuzz: minimizing 34995-byte crash input...
fuzz: elapsed: 3s, execs: 13821 (4604/sec), new interesting: 0 (total: 1)
fuzz: elapsed: 6s, execs: 13821 (2303/sec), new interesting: 0 (total: 1)
fuzz: elapsed: 9s, execs: 13821 (1535/sec), new interesting: 0 (total: 1)
fuzz: elapsed: 12s, execs: 13821 (1152/sec), new interesting: 0 (total: 1)
^Cfuzz: elapsed: 14s, execs: 13821 (994/sec), new interesting: 0 (total: 1)
--- FAIL: FuzzAdd (13.90s)
        --- FAIL: FuzzAdd (0.00s)
            testing.go:1299: panic: bad
                goroutine 1506 [running]:
                runtime/debug.Stack()
                        /Users/katiehockman/godev/src/runtime/debug/stack.go:24 +0x90
                testing.tRunner.func1()
                        /Users/katiehockman/godev/src/testing/testing.go:1299 +0x5a5
                ...
                
    
    Crash written to testdata/fuzz/FuzzAdd/618b91bbfb35dd0736e9c6c90ed38973a2e1f5ebb7edf50714c31ae21b18d419
    To re-run:
    go test foo -run=FuzzAdd/618b91bbfb35dd0736e9c6c90ed38973a2e1f5ebb7edf50714c31ae21b18d419
FAIL
exit status 1
FAIL    foo     18.072s
```

Turning off minimization fixes this (e.g. `go test -fuzz Fuzz -fuzzminimizetime=0x`)

This also only seems to happen once the fuzzing engine has already run baseline coverage or found a new interesting value. If the target is changed to panic for every input, this bug won't occur and it'll crash as expected. e.g.
```
func FuzzAdd(f *testing.F) {
	f.Fuzz(func(t *testing.T, b []byte) {
		panic("bad")
	})
}
```

This also shows a hole in our testing. Most of our tests use `-fuzztime` in order to ensure they don't run for too long. However, using `-fuzztime` ends fuzzing after a certain number of iterations. That means we aren't testing that the fuzzing process will complete successfully if a crash occurs without help from `-fuzztime`.

/cc @golang/fuzzing
Repository: pytorch
Issue: Add LTC-TS support for ops used in SGD optimizer
Labels: triaged,module: lazy

The script below uses SGD optimizer and the LTC trace doesn't capture the SGD step.  We need to add the ops necessary to enable tracing it.

```
import math
import torch
import lazy_tensor_core
import lazy_tensor_core.core.lazy_model as ltm
lazy_tensor_core._LAZYC._ltc_init_ts_backend()

torch.manual_seed(42)

device = 'lazy'
dtype = torch.float32


class Polynomial3(torch.nn.Module):
    def __init__(self):
        super().__init__()
        self.a = torch.nn.Parameter(torch.randn(()))
        self.b = torch.nn.Parameter(torch.randn(()))
        self.c = torch.nn.Parameter(torch.randn(()))
        self.d = torch.nn.Parameter(torch.randn(()))

    def forward(self, x):
        return self.a + self.b * x + self.c * x ** 2 + self.d * x ** 3

    def string(self):
        return f'y = {self.a.item()} + {self.b.item()} x + {self.c.item()} x^2 + {self.d.item()} x^3'


x = torch.linspace(-math.pi, math.pi, 20).to(device)
y = torch.sin(x)

model = Polynomial3()

criterion = torch.nn.MSELoss(reduction='sum')
optimizer = torch.optim.SGD(model.parameters(), lr=1e-2)
for t in range(5):
    # Forward pass: Compute predicted y by passing x to the model
    y_pred = model(x)

    # Compute and print loss
    loss = criterion(y_pred, y)
    print(t, loss.item())

    # Zero gradients, perform a backward pass, and update the weights.
    optimizer.zero_grad()
    loss.backward()
    optimizer.step()
    ltm.mark_step()

print(f'Result: {model.string()}')
```
Repository: kubernetes
Issue: APF: client should retry with exponential backoff and some jitter in default configuration
Labels: kind/bug,sig/api-machinery,lifecycle/frozen,triage/accepted

#### What happened:

When Priority and Fairness rejects a request, it sets `Retry-After: 1`  in the response header. client-go recognizes `Retry-After` header and automatically retries the request. 
The default configuration of client-go uses the `NoBackoff` implementation for the underlying `BackoffManager`.  `NoBackoff` will sleep exactly `N` seconds as the header suggested (`1s` in this case) - there is no built-in exponential back-off with jitter.

Today the client has to set a couple of env variables to use `URLBackoff` -https://github.com/kubernetes/kubernetes/blob/master/staging/src/k8s.io/client-go/rest/client.go#L145-L153


#### What you expected to happen:

- We expect client-go to exercise exponential backoff with some jitter in default configuration.
- The server can also randomize `N` in `Retry-After` header to de-synchronize the client a bit.

#### How to reproduce it (as minimally and precisely as possible):

#### Anything else we need to know?:

#### Environment:
- Kubernetes version (use `kubectl version`):
- Cloud provider or hardware configuration:
- OS (e.g: `cat /etc/os-release`):
- Kernel (e.g. `uname -a`):
- Install tools:
- Network plugin and version (if this is a network-related bug):
- Others: