sharjeelyunus/github-issues-dataset huggingface dataset:
Repository: pytorch
Issue: gdb core dump when enable DEBUG mode to compile cpu torch in centos!!!
Labels: needs reproduction,triaged

### 🐛 Describe the bug

try to compile pytorch 2.0 from source with DEBUG mode in centos, 
```
DEBUG=ON USE_CUDA=OFF python3 setup.py build
python3 setup.py bdist_wheel -d build_pip
pip3 install build_pip/torch-2.0.0a0+gitf33faa7-cp38-cp38-linux_x86_64.whl
```

write a test_import.py only to execute "import torch",

test_import.py:
`
import torch
`
execute on gdb terminal,
```
$ gdb python3
GNU gdb (GDB) Red Hat Enterprise Linux 7.6.1-120.el7
Copyright (C) 2013 Free Software Foundation, Inc.
License GPLv3+: GNU GPL version 3 or later <http://gnu.org/licenses/gpl.html>
This is free software: you are free to change and redistribute it.
There is NO WARRANTY, to the extent permitted by law.  Type "show copying"
and "show warranty" for details.
This GDB was configured as "x86_64-redhat-linux-gnu".
For bug reporting instructions, please see:
<http://www.gnu.org/software/gdb/bugs/>...
Reading symbols from /usr/local/bin/python3.8...done.
(gdb) r test_import.py
Starting program: /usr/local/bin/python3 test_import.py
[Thread debugging using libthread_db enabled]
Using host libthread_db library "/lib64/libthread_db.so.1".
[Detaching after fork from child process 59264]
Segmentation fault (core dumped)
```
the only info of gdb core dump file is:
```
$ gdb core-gdb.36373.software-h3c-r5300-g5-012.1696993149
GNU gdb (GDB) Red Hat Enterprise Linux 7.6.1-120.el7
Copyright (C) 2013 Free Software Foundation, Inc.
License GPLv3+: GNU GPL version 3 or later <http://gnu.org/licenses/gpl.html>
This is free software: you are free to change and redistribute it.
There is NO WARRANTY, to the extent permitted by law.  Type "show copying"
and "show warranty" for details.
This GDB was configured as "x86_64-redhat-linux-gnu".
For bug reporting instructions, please see:
<http://www.gnu.org/software/gdb/bugs/>...
[New LWP 36373]
Missing separate debuginfo for the main executable file
Try: yum --enablerepo='*debug*' install /usr/lib/debug/.build-id/c1/2d5af5d51fcc6bf42dbae84c5c14631fc28025
Core was generated by `gdb python3'.
Program terminated with signal 11, Segmentation fault.
#0  0x000000000079c820 in ?? ()
"./core-gdb.36373.software-h3c-r5300-g5-012.1696993149" is a core file.
Please specify an executable to debug.
(gdb) bt
Python Exception <class 'gdb.MemoryError'> Cannot access memory at address 0x7fffff7fef20:
(gdb)

```
Noted:
if compile on ubuntu image, it is ok;

### Versions

pytorch v2.1.0 tag
docker: nvidia/cuda:11.2.0-cudnn8-devel-centos7
Repository: pytorch
Issue: RuntimeError: out_ptr == out_accessor[thread_count_nonzero[tid + 1]].data() INTERNAL ASSERT FAILED
Labels: needs reproduction,triaged,module: advanced indexing

### 🐛 Describe the bug

Running a python script from within a SLURM job. Running the same SLURM job multiple times will have inconsistent results with jobs sometimes completing and sometimes failing with this error message.

### Error logs

```
Traceback (most recent call last):
  File "/<myprojectpath>/src/SLURM/pythonScript.py", line 45, in <module>
    dot_detect_deconv(fl, spot_dir, support_dir, th_fit = 80, delta=2, delta_fit=4, sigmaZ=2.5, sigmaXY=1.85)
  File "/<myprojectpath>/src/SLURM/pythonScript.py", line 33, in dot_detect_deconv
    Xh = get_local_maxfast_tensor(imDn,th_fit=th_fit,im_raw=im_,dic_psf=None,delta=delta,delta_fit=delta_fit,sigmaZ=sigmaZ,sigmaXY=sigmaXY)
         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/<myprojectpath>/src/SLURM/../ioMicro_Schier_v5.py", line 2768, in get_local_maxfast_tensor
    z_ = get_ind(im_centers0,zmax)
         ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/<myprojectpath>/src/SLURM/../ioMicro_Schier_v5.py", line 2741, in get_ind
    x_[bad]=-x_[bad]
             ~~^^^^^
RuntimeError: out_ptr == out_accessor[thread_count_nonzero[tid + 1]].data() INTERNAL ASSERT FAILED at "/opt/conda/conda-bld/pytorch_1682343970094/work/aten/src/ATen/native/TensorAdvancedIndexing.cpp":2232, please report a bug to PyTorch. 
```

### Minified repro

_No response_

### Versions

```
Collecting environment information...
Traceback (most recent call last):
  File "collect_env.py", line 612, in <module>
    main()
  File "collect_env.py", line 595, in main
    output = get_pretty_env_info()
  File "collect_env.py", line 590, in get_pretty_env_info
    return pretty_str(get_env_info())
  File "collect_env.py", line 428, in get_env_info
    pip_version, pip_list_output = get_pip_packages(run_lambda)
  File "collect_env.py", line 400, in get_pip_packages
    out = run_with_pip([sys.executable, '-mpip'])
  File "collect_env.py", line 384, in run_with_pip
    for line in out.splitlines()
AttributeError: 'NoneType' object has no attribute 'splitlines'
```
sorry I guess this is not what you were expecting... 

cc @ezyang @msaroufim @wconstab @bdhirsh @anijain2305
Repository: stable-diffusion-webui
Issue: [Bug]: queue status not visible 
Labels: bug-report

### Is there an existing issue for this?

- [X] I have searched the existing issues and checked the recent builds/commits

### What happened?

When sharing the UI over web multiple jobs at the same time will be queued.
However the current queue status seems not to be visible in the UI.
(My guess is that is uses the same layout as the progress bar which starts all the way to the left and only becomes visible when progressing.)

### Steps to reproduce the problem

1. Use --share when launching
2. Have user start image generation while current generation not finished

### What should have happened?

The current queue status of the users job should be clearly visible

### Sysinfo

Ubuntu 22.04

### What browsers do you use to access the UI ?

Mozilla Firefox, Google Chrome, Apple Safari

### Console logs

```Shell
--
```


### Additional information

_No response_
Repository: kubernetes
Issue: [csi-translation-lib] Topology keys not translated for azure_disk
Labels: kind/bug,sig/storage,triage/accepted

### What happened?

When translating an `azure_disk` in-tree pv using `csi-translation-lib`, the topology keys are not translated when using [TranslateInTreePVToCSI](https://github.com/kubernetes/csi-translation-lib/blob/master/plugins/azure_disk.go#L143)

### What did you expect to happen?

I would expect the topology keys to be translated as they are for [aws_ebs](https://github.com/kubernetes/csi-translation-lib/blob/master/plugins/aws_ebs.go#L193-L195) or [gce_pd](https://github.com/kubernetes/csi-translation-lib/blob/master/plugins/gce_pd.go#L257-L259).
Is there a reason why this is not done?

### How can we reproduce it (as minimally and precisely as possible)?

- In a kube cluster <=v1.26 with `CSIMigrationAzureDisk` flag disabled on the control plane.
- Create an in-tree storage class using topology keys like `failure-domain.beta.kubernetes.io/region` 
- Create a PV using the storage class 
- Translate the PV using the csi-translation-lib

### Anything else we need to know?

I can create a PR to fix this if the topology keys should be translated

### Kubernetes version

<details>
latest lib version

</details>


### Cloud provider

<details>
azure
</details>


### OS version

<details>
</details>


### Install tools

<details>

</details>


### Container runtime (CRI) and version (if applicable)

<details>

</details>


### Related plugins (CNI, CSI, ...) and versions (if applicable)

<details>

</details>
Repository: vscode
Issue: File Nesting setting is ignored
Labels: bug,settings-editor,confirmation-pending

<!-- ⚠️⚠️ Do Not Delete This! bug_report_template ⚠️⚠️ -->
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<!-- 💡 Instead of creating your report here, use 'Report Issue' from the 'Help' menu in VS Code to pre-fill useful information. -->
<!-- 🔧 Launch with `code --disable-extensions` to check. -->
Does this issue occur when all extensions are disabled?: Yes

<!-- 🪓 If you answered No above, use 'Help: Start Extension Bisect' from Command Palette to try to identify the cause. -->
<!-- 📣 Issues caused by an extension need to be reported directly to the extension publisher. The 'Help > Report Issue' dialog can assist with this. -->
- VS Code Version: 1.82.2
- OS Version: Win10

`explorer.fileNesting.enabled`
![image](https://github.com/microsoft/vscode/assets/13949704/1d33e13e-ff20-4811-9ee5-579571d776f9)
Repository: TypeScript
Issue: Double slash comment `//` will be wrongly removed in the trailing position of the object attribute
Labels: Help Wanted,Possible Improvement

### 🔎 Search Terms

- comment removal
- removeComments

### 🕗 Version & Regression Information

- This is the behavior in every version I tried.


### ⏯ Playground Link

https://www.typescriptlang.org/play?ts=5.2.2#code/KYDwDg9gTgLgBAYwgOwM7wGYQnAvHAbwCg5S4sIAuOAcgpoBo4B6ZuGACwEtVEIBbfsGTwA7lwA2EuACNgcKMH4QAbsAAmAOhJkZAQyjUa+qDRZtOPPoOFjJ0uXADWwMDCYyArmI4BPbQC+QA

### 💻 Code

```ts
export const foo = {
    foo: 'foo', // this comment will be removed, however this should be kept
    bar: 'bar' // this comment will be kept, works well
}
```


### 🙁 Actual behavior

```ts
export const foo = {
    foo: 'foo',
    bar: 'bar' // this comment will be kept, works well
}
```

### 🙂 Expected behavior

```ts
export const foo = {
    foo: 'foo', // this comment will be removed, however this should be kept
    bar: 'bar' // this comment will be kept, works well
}
```


### Additional information about the issue

_No response_
Repository: godot
Issue: Reverting is broken for GDExtension types with Resource properties with non-null default values
Labels: bug,topic:editor,topic:gdextension

### Godot version

4.1.1

### System information

Ubuntu 22.04.3

### Issue description

See also  #36372 and https://github.com/godot-rust/gdext/issues/440

Creating a GDExtension type with an exported `Resource` property that defaults to something other than null causes the Godot editor to use a specific, static instance of that type as the default value to revert that property.

That means it's possible to modify the default, so that reverting behaves in unexpected ways. Same behavior as #36372.

In particular, this makes it very tricky to implement non-null properties in GDExtension types. For example, a custom transform type that has a useful default value and is cheap to construct. Or something like Path2D from #36372 but instead of reverting to null it reverts to an empty path. For the Rust GDExtension bindings in particular this would be very nice to avoid null checks all over the code base.

### Steps to reproduce

1. Create a GDExtension type with an exported `Curve2D` property that defaults to `Curve2D.new()` in `init`
2. Follow the repro steps in #36372 :

> 3. Draw your curve.
> 4. Now press the reset button. Curve disappears, but when you now draw a new curve, the reset button is also gone.
> 5. If you select "New Curve2D" from the dropdown, and then reset, it will default to the previous curve you had drawn.

Example video with the attached repro project:

[godot-obj-nonnull-repro.webm](https://github.com/godotengine/godot/assets/3664988/c76cafee-0d31-4460-97a9-764a7f15c453)




### Minimal reproduction project

[obj-nonnull-repro.zip](https://github.com/godotengine/godot/files/12858498/obj-nonnull-repro.zip)


To build the GDExtension lib:
```
cd rust/
cargo build
```
Repository: material-ui
Issue: [joy-ui] Add Kbd component
Labels: new feature,waiting for 👍,package: joy-ui

### Duplicates

- [X] I have searched the existing issues

### Latest version

- [X] I have tested the latest version

### Summary 💡

The Kbd component simplifies the display of keyboard inputs, making it easy to showcase shortcuts and user interactions involving the keyboard. It enhances user understanding and interaction in applications ensuring a seamless and user-friendly experience.

### Examples 🌈

https://mantine.dev/core/kbd/
https://chakra-ui.com/docs/components/kbd/usage

### Motivation 🔦

_No response_
Repository: pytorch
Issue: Enable more flake8-pyi ruff checks
Labels: good first issue,module: lint,triaged,actionable

### 🚀 The feature, motivation and pitch

https://github.com/pytorch/pytorch/pull/110830 enabled a bunch of use flake8-PYI checks to improve the quality of type hints on the PyTorch codebase. While this was a good first pass, many rules need to removed from the ignore list in the pyproject.toml. Fixing these rules an enabling the lints would be a good starter task.

For other rules to enable, see this starter task: https://github.com/pytorch/pytorch/issues/106571

### Alternatives

_No response_

### Additional context

_No response_
Repository: vscode
Issue: Running extensions editor does not wrap content properly
Labels: bug,extensions-editor



![Image](https://github.com/microsoft/vscode/assets/2193314/44719d74-ff0a-46a7-893a-07f8fc40efb4)



![Image](https://github.com/microsoft/vscode/assets/2193314/67b6a8fe-7106-438d-aa59-ae02b1742497)
Repository: deno
Issue: Accept http/2 only
Labels: feat,ext/http

How can I built a server that accept only http/2 connection in Deno?
Repository: vscode
Issue: Diff Editor: Confusing Line Endings
Labels: bug,diff-editor


![Image](https://github.com/microsoft/vscode/assets/2931520/c25e0852-0a09-462f-8849-b6782f8b565c)



## Playground Example

[Monaco Editor Playground Repro](https://microsoft.github.io/monaco-editor/playground.html?source=v0.45.0-dev-20231010#XQAAAALYBAAAAAAAAABBqQkHQ5NjdMeMm-jY7SIQ9S7DNlzs5W-mwj0fe1ZCDRFc9ws9XQE0SJE1jc2VKxhaLFIw9vEWdz-byd211kSnigQsJWN0ZLn8ssc1omO-gmDsEXZGzSI2XkagwyWmNzGAgaQLuAE3x4YRhDvqk2czXgMVnV3CjL1H_Tff3JMlfgCl1SdH_Br9zIqoiljbpQvmVU5aApti4AxS_OaML3Wdf1iQzgBya_5aoMRiErb7SULMQoC8aocQxJKpxXrmCfNJa1lCfQhrw3u2zA0qM_kF2UttjaTXEVUxm2rO6VJfPi0lgzsUMnX-yemPeSfjvkRFnL6nKyqcO_Y-ly8RYUlzH3wyCmj0JQ33ccdvL2L1T2F3NzYAyVAymw-9m4b2ipzoaBog1yMZWMSkuHoWKx9uZWq0ZvPd6eJr-yCpcW9ZtuFax1cSY-b67hSaMUuqlHehJK3iK-BY5WnczXLEv-fh6yd0dRFWUKmbW6LYBtYJ3cQ5OshfRNzMFsNOkdrR7nhwVJkeyacGVEZvRHsXj33r7vI6qjAmiEcq011gQJIK5jg3mwxSdSLLv4SYSQi79u5XL4wKF8b-OVb-a0gppmR7yEZ-uiQp6yrQx59T0gKIE-bdU5bht99SEN3oLFNE0zK3kNYdH6P6F_JWn4vqJk3CK4GVL1nnB1vdbJn5YQ0LaFQVd-qogZwc3XFNeNEohLlgu1-y3FojqQXs4Ho9NMorKtMlAwnhyqEz7DBDCkVLjyduFfTMN-J0AMz1Lx-6hkb8X9JdDQ3jf5C6aLS3_B-PQFAN--fkI7d6kL_eNT7iIdDG5KObz4Em5__nsLP-) (click on "use latest dev" to verify a future bug-fix)
Repository: pytorch
Issue: kBackendDefaultTimeout is causing a timeout exception when rank 0 process exceeds 30 minutes preparing a dataset.
Labels: oncall: distributed

### 🐛 Describe the bug

If rank 0 process takes more than 30 minutes to process a training dataset, processes of rank > 0 assume it is dead and throw an exception, therefore killing the distributed training program.

Attempts to change default_pg_timeout within deepspeed's code failed to work, implying that value is either ignored or being overridden by the value in  ~/pytorch/torch/csrc/distributed/c10d/Backend.hpp

____________________________________________________________________________________________________________

#pragma once

#include <condition_variable>
#include <memory>
#include <mutex>
#include <stdexcept>
#include <unordered_map>
#include <utility>
#include <vector>

#include <ATen/ATen.h>
#include <c10/macros/Macros.h>

#include <torch/csrc/distributed/c10d/Work.hpp>
#include <torch/csrc/distributed/c10d/Types.hpp>
#include <torch/csrc/distributed/c10d/Utils.hpp>
#include <torch/csrc/distributed/c10d/debug.h>
#include <torch/csrc/distributed/c10d/sequence_num.hpp>


constexpr auto kBackendDefaultTimeout = // This default of 30 minutes for a timeout is causing problems for long running 
                                                                      // training data prep with multiple GPU setups.
    std::chrono::milliseconds(30 * 60 * 1000);

namespace c10d {

class TORCH_API Backend : public torch::CustomClassHolder {
 public:

  // Backend Options is a base struct that defines the basic options
  // when constructing a Backend. Each Backend subclass should
  // extend this struct and define its options if it wants to provide more
  // config options (beyond basic ones defined here) to end user.
  struct TORCH_API Options : torch::CustomClassHolder {
    explicit Options(
        std::string backend,
        std::chrono::milliseconds timeout = kBackendDefaultTimeout)
        : timeout(timeout), backend(std::move(backend)) {}
    ~Options() override = default;


### Versions

.

cc @mrshenli @pritamdamania87 @zhaojuanmao @satgera @rohan-varma @gqchen @aazzolini @osalpekar @jiayisuse @H-Huang @kwen2501 @awgu @penguinwu
Repository: PowerToys
Issue: Powertoys doesn't show Timezone
Labels: Idea-Enhancement,Product-PowerToys Run,Severity-Regression,Needs-Triage,Run-Plugin

### Microsoft PowerToys version

0.74.1

### Installation method

WinGet

### Running as admin

Yes

### Area(s) with issue?

PowerToys Run

### Steps to reproduce

1. Launch powertoys run
2. use the command `) Eastern Time` or ` ) ETC`

### ✔️ Expected Behavior

Show the time zone for Eastern Time

### ❌ Actual Behavior

Doesn't display any data. 

### Other Software

_No response_
Repository: godot
Issue: AutoLoad fails to load in an unintuitive way
Labels: topic:core

### Godot version

4.1.1 and 4.1.2 (v4.1.2.stable.official [399c9dc39])

### System information

Windows 10 (Compatibility)

### Issue description

I was trying to figure out why, at random intervals, my game started crashing and complaining about one of my AutoLoad not inheriting from a Node. after a day and a half of trial and error (I could not find someone with the same problem online) I managed to get it to work by just shuffling the AutoLoad order. It did not make any sense as one of the AutoLoad that was giving me an error was quite literally empty and could not possibly depend on other singletons. Then, i realized it wasn't random, the fix was specifically to move the AutoLoads that were causing the crash before my scene manager, which preloads every scene in the game and that's when it clicked. changing preload to load fixed the problem regardless of the order.

Conclusion: When an AutoLoad preloads scenes that use other singletons that haven't been loaded yet, it causes a crash and gives you some error message about the AutoLoad not inheriting from Node. If this cannot be fixed, changing the error message would be nice.

### Steps to reproduce

- Create a project.
- Add two AutoLoad.
- Create a scene that calls a function from AutoLoad2.
- Preload the scene in AutoLoad1.
- You should get an error that AutoLoad2 doesn't inherit Node and the program will crash when the function is called as AutoLoad2 is nil.

Note that you won't get a crash if you only refer to the AutoLoad, you have to call a method or refer to a variable as if it were a null pointer.


### Minimal reproduction project

[ErrorReport.zip](https://github.com/godotengine/godot/files/12860596/ErrorReport.zip)
Repository: pytorch
Issue: `torch.is_autocast_enabled()` always False on CPU
Labels: triaged,module: amp (automated mixed precision)

### 🐛 Describe the bug

`torch.is_autocast_enabled()` seems to always returns `False` on CPU. For example:

```python
import torch

device = torch.device("cpu")
with torch.autocast(device.type, torch.bfloat16, enabled=True):
    assert torch.is_autocast_enabled()
```

### Versions

Collecting environment information...
PyTorch version: 2.1.0
Is debug build: False
CUDA used to build PyTorch: None
ROCM used to build PyTorch: N/A

OS: macOS 13.2.1 (arm64)
GCC version: Could not collect
Clang version: 14.0.0 (clang-1400.0.29.202)
CMake version: version 3.26.2
Libc version: N/A

Python version: 3.10.10 (main, Feb 16 2023, 02:46:59) [Clang 14.0.0 (clang-1400.0.29.202)] (64-bit runtime)
Python platform: macOS-13.2.1-arm64-arm-64bit
Is CUDA available: False
CUDA runtime version: No CUDA
CUDA_MODULE_LOADING set to: N/A
GPU models and configuration: No CUDA
Nvidia driver version: No CUDA
cuDNN version: No CUDA
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True

CPU:
Apple M1 Max

Versions of relevant libraries:
[pip3] flake8==6.0.0
[pip3] mypy==1.2.0
[pip3] mypy-extensions==1.0.0
[pip3] numpy==1.22.4
[pip3] pytorch-ranger==0.1.1
[pip3] torch==2.1.0
[pip3] torch-optimizer==0.3.0
[pip3] torchaudio==2.1.0
[pip3] torchmetrics==0.11.4
[pip3] torchvision==0.16.0
[conda] Could not collect

cc @ezyang @gchanan @zou3519 @kadeng @mcarilli @ptrblck @leslie-fang-intel @jgong5
Repository: PowerToys
Issue: Keeps forgeting the fancy zone settings for each desktop
Labels: Issue-Bug,Product-FancyZones

### Microsoft PowerToys version

0.74.1

### Installation method

GitHub, PowerToys auto-update

### Running as admin

Yes

### Area(s) with issue?

FancyZones, FancyZones Editor

### Steps to reproduce

I configure all desktops with differents zones and if I restart the pc all gets messy and some config repeated on some screens and some in other and they are not set for the actual screen they was configured for.

### ✔️ Expected Behavior

Desktop should gets its configured fancy zones 

### ❌ Actual Behavior

desktops gets random fancy zone configurations 

### Other Software

_No response_
Repository: go
Issue: gccgo: "error: esc already decorated call" on valid program
Labels: NeedsInvestigation

```
$ gccgo --version
gccgo (Debian 13.2.0-4) 13.2.0
```
```
package main

func f(s string) int {
	return len([]byte(s))
}

func main() {
	for _, e := range make([]int, f("abc")) {
		println(e)
	}
}
```
```
$ gccgo crash.go 
go1: error: esc already decorated call f("abc")
```

Compiles and runs fine on gc.
Repository: flutter
Issue: [flutter_tools] NPE in HotRunner._updateDevFS
Labels: c: crash,P2,team-tool,triaged-tool

Version: `beta/3.15.0-15.2.pre`
Command: `flutter run --machine --start-paused -d emulator-5554 --devtools-server-address http://127.0.0.1:9100/ --target /path/to/app/lib/main.dart`

```
_TypeError: Null check operator used on a null value
at HotRunner._updateDevFS(run_hot.dart:466)
at <asynchronous gap>(async)
at HotRunner.attach(run_hot.dart:282)
at <asynchronous gap>(async)
at AppDomain.launch.<anonymous closure>(daemon.dart:655)
at <asynchronous gap>(async)
at AppDomain.launch(daemon.dart:653)
at <asynchronous gap>(async)
at RunCommand.runCommand(run.dart:645)
at <asynchronous gap>(async)
at FlutterCommand.run.<anonymous closure>(flutter_command.dart:1323)
at <asynchronous gap>(async)
at AppContext.run.<anonymous closure>(context.dart:150)
at <asynchronous gap>(async)
at CommandRunner.runCommand(command_runner.dart:212)
at <asynchronous gap>(async)
at FlutterCommandRunner.runCommand.<anonymous closure>(flutter_command_runner.dart:348)
at <asynchronous gap>(async)
at AppContext.run.<anonymous closure>(context.dart:150)
at <asynchronous gap>(async)
at FlutterCommandRunner.runCommand(flutter_command_runner.dart:294)
at <asynchronous gap>(async)
at run.<anonymous closure>.<anonymous closure>(runner.dart:113)
at <asynchronous gap>(async)
at AppContext.run.<anonymous closure>(context.dart:150)
at <asynchronous gap>(async)
at main(executable.dart:90)
at <asynchronous gap>(async)
```

Code looks like:

```dart
      for (final FlutterDevice? device in flutterDevices)
        await device!.setupDevFS(
          fsName,
          globals.fs.directory(projectRootPath),
        ),
```

However, the static type of flutterDevices is `List<FlutterDevice> flutterDevices` so I'm not sure how this is possible.