sharjeelyunus/github-issues-dataset huggingface dataset:
Repository: godot
Issue: Keep Screen On not working on Fedora 39 (KDE Plasma)
Labels: bug,platform:linuxbsd,topic:porting

### Tested versions

Reproduced in v4.2.1.stable.mono.official [b09f793f5] and v4.3.dev5.official [c9c17d6ca] in both x11 and wayland and in all rendering methods.

### System information

Godot v4.2.1.stable.mono - Fedora Linux 39 (KDE Plasma) - X11 - Vulkan (Forward+) - dedicated NVIDIA GeForce GTX 1650 (nvidia; 550.54.14) - Intel(R) Core(TM) i3-10100F CPU @ 3.60GHz (8 Threads)

### Issue description

Screen turns off after normal time despite a project running with keep_screen_on enabled.

### Steps to reproduce

Create a project, save a scene with anything in it, then run it and wait for the screen to turn off.

### Minimal reproduction project (MRP)

N/A
Repository: tensorflow
Issue: Aborted (core dumped) with `tf.raw_ops.CombinedNonMaxSuppression`
Labels: stat:awaiting tensorflower,type:bug,comp:ops,TF 2.16

### Issue type

Bug

### Have you reproduced the bug with TensorFlow Nightly?

Yes

### Source

source

### TensorFlow version

tf 2.16.1

### Custom code

Yes

### OS platform and distribution

Ubuntu 20.04

### Mobile device

_No response_

### Python version

3.11

### Bazel version

_No response_

### GCC/compiler version

_No response_

### CUDA/cuDNN version

_No response_

### GPU model and memory

_No response_

### Current behavior?

If `max_total_size` is too large , `tf.raw_ops.CombinedNonMaxSuppression` encounters "Aborted (core dumped)".

### Standalone code to reproduce the issue

```shell
import tensorflow as tf

pad_per_class = True
clip_boxes = False
boxes = tf.constant(3.5e+35, shape=[], dtype=tf.float32)
scores = tf.constant(0, shape=[], dtype=tf.float32)
max_output_size_per_class = tf.constant(8, shape=[], dtype=tf.int32)
max_total_size = tf.constant(1879048192, shape=[], dtype=tf.int32)
iou_threshold = tf.constant(0.5, shape=[], dtype=tf.float32)
score_threshold = tf.constant(0.5, shape=[], dtype=tf.float32)
tf.raw_ops.CombinedNonMaxSuppression(boxes=boxes, scores=scores, max_output_size_per_class=max_output_size_per_class, max_total_size=max_total_size, iou_threshold=iou_threshold, score_threshold=score_threshold, pad_per_class=pad_per_class, clip_boxes=clip_boxes)
```


### Relevant log output

```shell
2024-05-01 02:52:31.372751: W tensorflow/core/kernels/image/non_max_suppression_op.cc:998] Detected a large value for `max_total_size`. This may cause OOM error. (max_total_size: 1879048192)
2024-05-01 02:52:31.372808: F tensorflow/core/framework/tensor_shape.cc:357] Check failed: d < dims() (2 vs. 0)
Aborted (core dumped)
```
Repository: tensorflow
Issue: Aborted (core dumped) with `tf.raw_ops.Dilation2DBackpropFilter`
Labels: stat:awaiting tensorflower,type:bug,comp:ops,TF 2.16

### Issue type

Bug

### Have you reproduced the bug with TensorFlow Nightly?

Yes

### Source

source

### TensorFlow version

tf 2.16.1

### Custom code

Yes

### OS platform and distribution

Ubuntu 20.04

### Mobile device

_No response_

### Python version

3.11

### Bazel version

_No response_

### GCC/compiler version

_No response_

### CUDA/cuDNN version

_No response_

### GPU model and memory

_No response_

### Current behavior?

Under specific input, `tf.raw_ops.Dilation2DBackpropFilter` encounters "Aborted (core dumped)".

### Standalone code to reproduce the issue

```shell
import tensorflow as tf

strides = [1, 1, 1, 1]
rates = [1, 1, 1, 1]
padding = "VALID"
input = tf.constant([], shape=[0,0,0,0], dtype=tf.float32)
filter = tf.constant([], shape=[0,0,0], dtype=tf.float32)
out_backprop = tf.constant([], shape=[0], dtype=tf.float32)
tf.raw_ops.Dilation2DBackpropFilter(input=input, filter=filter, out_backprop=out_backprop, strides=strides, rates=rates, padding=padding)
```


### Relevant log output

```shell
2024-05-01 03:00:39.549898: F tensorflow/core/framework/tensor_shape.cc:357] Check failed: d < dims() (1 vs. 1)
Aborted (core dumped)
```
Repository: pytorch
Issue: Need a C++ way to convert PyTorch model to TorchScript model
Labels: oncall: jit

### 🚀 The feature, motivation and pitch

I cann't find a way to do like those python code in C++:

sm = torch.jit.script(model)
torch.jit.save(sm, "./myModel.pt")

or
    sample = torch.randn(1, 3, 32, 32)
    #sample = sample.to(device)
    trace_model = torch.jit.trace(model, sample)
    trace_model.save("./myModel.pt")

### Alternatives

_No response_

### Additional context

_No response_

cc @EikanWang @jgong5 @wenzhe-nrv @sanchitintel
Repository: tensorflow
Issue: Aborted (core dumped) with `tf.raw_ops.FakeQuantWithMinMaxVarsPerChannelGradient`
Labels: stat:awaiting tensorflower,type:bug,comp:ops,TF 2.16

### Issue type

Bug

### Have you reproduced the bug with TensorFlow Nightly?

Yes

### Source

source

### TensorFlow version

tf 2.16.1

### Custom code

Yes

### OS platform and distribution

Ubuntu 20.04

### Mobile device

_No response_

### Python version

3.11

### Bazel version

_No response_

### GCC/compiler version

_No response_

### CUDA/cuDNN version

_No response_

### GPU model and memory

_No response_

### Current behavior?

Check Failed in `tf.raw_ops.FakeQuantWithMinMaxVarsPerChannelGradient` when the input of inputs is scalar, which causes the program to crash.

### Standalone code to reproduce the issue

```shell
# FakeQuantWithMinMaxVarsPerChannelGradientOp

import tensorflow as tf

num_bits = 8
narrow_range = False
gradients = tf.constant(0, shape=[], dtype=tf.float32)
inputs = tf.constant(0, shape=[], dtype=tf.float32)
min = tf.constant(124, shape=[3,1], dtype=tf.float32)
max = tf.constant(124, shape=[3,1], dtype=tf.float32)
tf.raw_ops.FakeQuantWithMinMaxVarsPerChannelGradient(gradients=gradients, inputs=inputs, min=min, max=max, num_bits=num_bits, narrow_range=narrow_range)
```


### Relevant log output

```shell
2024-05-01 03:10:46.669162: F tensorflow/core/framework/tensor_shape.cc:356] Check failed: d >= 0 (0 vs. -1)
Aborted (core dumped)
```
Repository: tensorflow
Issue: Aborted (core dumped) with `tf.raw_ops.LRNGrad`
Labels: stat:awaiting tensorflower,type:bug,comp:ops,TF 2.16

### Issue type

Bug

### Have you reproduced the bug with TensorFlow Nightly?

Yes

### Source

source

### TensorFlow version

tf 2.16.1

### Custom code

Yes

### OS platform and distribution

Ubuntu 20.04

### Mobile device

_No response_

### Python version

3.11

### Bazel version

_No response_

### GCC/compiler version

_No response_

### CUDA/cuDNN version

_No response_

### GPU model and memory

_No response_

### Current behavior?

If  the dimension of `output_image` is less than `input_grads` and `input_image`, tf.raw_ops.tf.raw_ops.LoadAndRemapMatrix encounters "Aborted (core dumped)".

### Standalone code to reproduce the issue

```shell
# LRNGradOp

import tensorflow as tf

depth_radius = 1
bias = 1.59018219
alpha = 0.117728651
beta = 0.404427052
input_grads = tf.constant([], shape=[0,0,0,0], dtype=tf.float32)
input_image = tf.constant([], shape=[0,0,0,0], dtype=tf.float32)
output_image = tf.constant([], shape=[0], dtype=tf.float32)
tf.raw_ops.LRNGrad(input_grads=input_grads, input_image=input_image, output_image=output_image, depth_radius=depth_radius, bias=bias, alpha=alpha, beta=beta)
```


### Relevant log output

```shell
2024-05-01 03:28:07.055077: F tensorflow/core/framework/tensor_shape.cc:357] Check failed: d < dims() (1 vs. 1)
Aborted (core dumped)
```
Repository: tensorflow
Issue: Aborted (core dumped) with `tf.raw_ops.LSTMBlockCell`
Labels: stat:awaiting tensorflower,type:bug,comp:ops,TF 2.16

### Issue type

Bug

### Have you reproduced the bug with TensorFlow Nightly?

Yes

### Source

source

### TensorFlow version

tf 2.16.1

### Custom code

Yes

### OS platform and distribution

Ubuntu 20.04

### Mobile device

_No response_

### Python version

3.11

### Bazel version

_No response_

### GCC/compiler version

_No response_

### CUDA/cuDNN version

_No response_

### GPU model and memory

_No response_

### Current behavior?

Under specific input, `tf.raw_ops.LSTMBlockCell` encounters "Aborted (core dumped)".

### Standalone code to reproduce the issue

```shell
import tensorflow as tf

forget_bias = 1
cell_clip = 0
use_peephole = False
x = tf.constant([], shape=[0], dtype=tf.float32)
cs_prev = tf.constant([], shape=[0], dtype=tf.float32)
h_prev = tf.constant([], shape=[0,0], dtype=tf.float32)
w = tf.constant([], shape=[0], dtype=tf.float32)
wci = tf.constant([], shape=[0,0], dtype=tf.float32)
wcf = tf.constant(0.837607, shape=[28,29], dtype=tf.float32)
wco = tf.constant(0.837607, shape=[28,29], dtype=tf.float32)
b = tf.constant(0.837607, shape=[28,29], dtype=tf.float32)
tf.raw_ops.LSTMBlockCell(x=x, cs_prev=cs_prev, h_prev=h_prev, w=w, wci=wci, wcf=wcf, wco=wco, b=b, forget_bias=forget_bias, cell_clip=cell_clip, use_peephole=use_peephole)
```


### Relevant log output

```shell
2024-05-01 03:36:12.005999: F tensorflow/core/framework/tensor_shape.cc:357] Check failed: d < dims() (1 vs. 1)
Aborted (core dumped)
```
Repository: tensorflow
Issue: Aborted (core dumped) with `tf.raw_ops.LSTMBlockCellGrad`
Labels: stat:awaiting tensorflower,type:bug,comp:ops,TF 2.16

### Issue type

Bug

### Have you reproduced the bug with TensorFlow Nightly?

Yes

### Source

source

### TensorFlow version

tf 2.16.1

### Custom code

Yes

### OS platform and distribution

Ubuntu 20.04

### Mobile device

_No response_

### Python version

3.11

### Bazel version

_No response_

### GCC/compiler version

_No response_

### CUDA/cuDNN version

_No response_

### GPU model and memory

_No response_

### Current behavior?

The parameter x is expected to be two-dimensional, and an error will occur when x is one-dimensional

### Standalone code to reproduce the issue

```shell
import tensorflow as tf

use_peephole = False
x = tf.constant(0, shape=[17], dtype=tf.float32)
cs_prev = tf.constant(0.837607, shape=[28,29], dtype=tf.float32)
h_prev = tf.constant(0.837607, shape=[28,29], dtype=tf.float32)
w = tf.constant(0.837607, shape=[28,29], dtype=tf.float32)
wci = tf.constant(0.837607, shape=[28,29], dtype=tf.float32)
wcf = tf.constant(0.837607, shape=[28,29], dtype=tf.float32)
wco = tf.constant(0.837607, shape=[28,29], dtype=tf.float32)
b = tf.constant(0.837607, shape=[28,29], dtype=tf.float32)
i = tf.constant(0.837607, shape=[28,29], dtype=tf.float32)
cs = tf.constant(0.837607, shape=[28,29], dtype=tf.float32)
f = tf.constant(0.837607, shape=[28,29], dtype=tf.float32)
o = tf.constant(0.837607, shape=[28,29], dtype=tf.float32)
ci = tf.constant(0.837607, shape=[28,29], dtype=tf.float32)
co = tf.constant(0.837607, shape=[28,29], dtype=tf.float32)
cs_grad = tf.constant(0.837607, shape=[28,29], dtype=tf.float32)
h_grad = tf.constant(0.837607, shape=[28,29], dtype=tf.float32)
tf.raw_ops.LSTMBlockCellGrad(x=x, cs_prev=cs_prev, h_prev=h_prev, w=w, wci=wci, wcf=wcf, wco=wco, b=b, i=i, cs=cs, f=f, o=o, ci=ci, co=co, cs_grad=cs_grad, h_grad=h_grad, use_peephole=use_peephole)
```


### Relevant log output

```shell
2024-05-01 03:41:18.804132: F tensorflow/core/framework/tensor_shape.cc:357] Check failed: d < dims() (1 vs. 1)
Aborted (core dumped)
```
Repository: tensorflow
Issue: Check fail in `tf.raw_ops.MaxPoolGradWithArgmax`
Labels: stat:awaiting tensorflower,type:bug,comp:ops,TF 2.16

### Issue type

Bug

### Have you reproduced the bug with TensorFlow Nightly?

Yes

### Source

source

### TensorFlow version

tf 2.16.1

### Custom code

Yes

### OS platform and distribution

Ubuntu 20.04

### Mobile device

_No response_

### Python version

3.11

### Bazel version

_No response_

### GCC/compiler version

_No response_

### CUDA/cuDNN version

_No response_

### GPU model and memory

_No response_

### Current behavior?

When argmax is set to a maximum value， `tf.raw_ops.MaxPoolGradWithArgmax` encounters "Aborted (core dumped)".

### Standalone code to reproduce the issue

```shell
import tensorflow as tf

ksize = [1, 1, 1, 1]
strides = [1, 1, 1, 1]
padding = "VALID"
include_batch_in_index = False
input = tf.constant(1, shape=[1,1,1,1], dtype=tf.float32)
grad = tf.constant(1, shape=[1,1,1,1], dtype=tf.float32)
argmax = tf.constant(1250999896764, shape=[1,1,1,1], dtype=tf.int64)
tf.raw_ops.MaxPoolGradWithArgmax(input=input, grad=grad, argmax=argmax, ksize=ksize, strides=strides, padding=padding, include_batch_in_index=include_batch_in_index)
```


### Relevant log output

```shell
2024-05-01 03:42:17.994627: F tensorflow/core/kernels/maxpooling_op.cc:1081] Check failed: grad_out_index >= output_start && grad_out_index < output_end Invalid output gradient index: 1250999896764, 0, 1
Aborted (core dumped)
```
Repository: tauri
Issue: [bug] tauri dev command uses "frontendDist" instead of "devUrl"
Labels: type: bug,status: needs triage

### Describe the bug

I'm building an app using Nuxt 3 and Tauri. I'm on Windows 11.

The build section of my `tauri.conf.json` looks like this:
```
"build": {
        "beforeDevCommand": "pnpm dev",
        "devUrl": "http://localhost:3000",
        "beforeBuildCommand": "pnpm generate",
        "frontendDist": ".output/public"
},
```

When I run the `cargo tauri dev` command it serves from `.output/public` thus it doesn't react to changes in the src files.

If I change my `tauri.conf.json` to this:

```
"build": {
        "beforeDevCommand": "pnpm dev",
        "devUrl": "http://localhost:3000",
        "beforeBuildCommand": "pnpm generate",
        "frontendDist": "http://localhost:3000"
},
```

Then it works great.

This seems to have just started after upgrading Tauri CLI from `beta.0` to `beta.14`.

### Reproduction

_No response_

### Expected behavior

_No response_

### Full `tauri info` output

```text
[✔] Environment
    - OS: Windows 10.0.22635 X64
    ✔ WebView2: 124.0.2478.67
    ✔ MSVC: Visual Studio Community 2022
    ✔ rustc: 1.79.0-nightly (ef8b9dcf2 2024-04-24)
    ✔ cargo: 1.79.0-nightly (c93926759 2024-04-23)
    ✔ rustup: 1.27.0 (bbb9276d2 2024-03-08)
    ✔ Rust toolchain: nightly-x86_64-pc-windows-msvc (environment override by RUSTUP_TOOLCHAIN)
    - node: 20.12.2
    - pnpm: 9.0.6
    - yarn: 1.22.19
    - npm: 10.5.1

[-] Packages
    - tauri [RUST]: 2.0.0-beta.16
    - tauri-build [RUST]: 2.0.0-beta.13
    - wry [RUST]: 0.39.3
    - tao [RUST]: 0.27.1
    - tauri-cli [RUST]: 2.0.0-beta.14
    - @tauri-apps/api [NPM]: 2.0.0-beta.9
    - @tauri-apps/cli [NPM]: 2.0.0-beta.14

[-] App
    - build-type: bundle
    - CSP: unset
    - frontendDist: http://localhost:3000/
    - devUrl: http://localhost:3000/
    - framework: Vue.js (Nuxt)
    - bundler: Vite
```


### Stack trace

_No response_

### Additional context

_No response_
Repository: tensorflow
Issue: Aborted (core dumped) in `tf.raw_ops.NearestNeighbors`
Labels: stat:awaiting tensorflower,type:bug,comp:ops,TF 2.16

### Issue type

Bug

### Have you reproduced the bug with TensorFlow Nightly?

Yes

### Source

source

### TensorFlow version

tf 2.16.1

### Custom code

Yes

### OS platform and distribution

Ubuntu 20.04

### Mobile device

_No response_

### Python version

3.11

### Bazel version

_No response_

### GCC/compiler version

_No response_

### CUDA/cuDNN version

_No response_

### GPU model and memory

_No response_

### Current behavior?

Parameter k being set to a negative number will cause a crash.

### Standalone code to reproduce the issue

```shell
import tensorflow as tf

points = tf.constant(0.554979503, shape=[1000,100], dtype=tf.float32)
centers = tf.constant(0.554979503, shape=[1000,100], dtype=tf.float32)
k = tf.constant(-1250999896764, shape=[], dtype=tf.int64)
tf.raw_ops.NearestNeighbors(points=points, centers=centers, k=k)
```


### Relevant log output

```shell
2024-05-01 03:49:00.796702: F tensorflow/core/framework/tensor_shape.cc:201] Non-OK-status: InitDims(dim_sizes) status: INVALID_ARGUMENT: Expected shape dimensions to be non-negative, got -1250999896764
Aborted (core dumped)
```
Repository: tensorflow
Issue: Aborted (core dumped) in `tf.raw_ops.SparseBincount`
Labels: stat:awaiting tensorflower,type:bug,comp:ops,TF 2.16

### Issue type

Bug

### Have you reproduced the bug with TensorFlow Nightly?

Yes

### Source

source

### TensorFlow version

tf 2.16.1

### Custom code

Yes

### OS platform and distribution

Ubuntu 20.04

### Mobile device

_No response_

### Python version

3.11

### Bazel version

_No response_

### GCC/compiler version

_No response_

### CUDA/cuDNN version

_No response_

### GPU model and memory

_No response_

### Current behavior?

Multiplication of `dense_shape` and `size` causes integer overflow

### Standalone code to reproduce the issue

```shell
import tensorflow as tf

binary_output = True
indices = tf.constant(0, shape=[3456,2], dtype=tf.int64)
values = tf.constant(-536870912, shape=[3456], dtype=tf.int32)
dense_shape = tf.constant([1250999896764,1250999896764], shape=[2], dtype=tf.int64)
size = tf.constant(305032608, shape=[], dtype=tf.int32)
weights = tf.constant(51, shape=[3456], dtype=tf.int32)
tf.raw_ops.SparseBincount(indices=indices, values=values, dense_shape=dense_shape, size=size, weights=weights, binary_output=binary_output)
```


### Relevant log output

```shell
2024-05-01 03:51:04.482001: F tensorflow/core/framework/tensor_shape.cc:201] Non-OK-status: InitDims(dim_sizes) status: INVALID_ARGUMENT: Encountered overflow when multiplying 1250999896764 with 305032608, result: -1
Aborted (core dumped)
```
Repository: tensorflow
Issue: Aborted (core dumped) in `TensorScatterOp`
Labels: stat:awaiting tensorflower,type:bug,comp:ops,TF 2.16

### Issue type

Bug

### Have you reproduced the bug with TensorFlow Nightly?

Yes

### Source

source

### TensorFlow version

tf 2.16.1

### Custom code

Yes

### OS platform and distribution

Ubuntu 20.04

### Mobile device

_No response_

### Python version

3.11

### Bazel version

_No response_

### GCC/compiler version

_No response_

### CUDA/cuDNN version

_No response_

### GPU model and memory

_No response_

### Current behavior?

The dimensions of `indices` and `updates` must be equal.If not equal,`tf.raw
_ops.TensorScatterSub,tf.raw
_ops.TensorScatterAdd,tf.raw
_ops.TensorScatterMin,tf.raw
_ops.TensorScatterMax,tf.raw
_ops.TensorScatterUpdate ` will crash.

### Standalone code to reproduce the issue

```shell
import tensorflow as tf

tensor = tf.constant(0, shape=[101,32], dtype=tf.float32)
indices = tf.constant([], shape=[0,0,0,6], dtype=tf.int32)
updates = tf.constant([], shape=[0,0], dtype=tf.float32)
tf.raw_ops.TensorScatterAdd(tensor=tensor, indices=indices, updates=updates)
```
```
import tensorflow as tf

tensor = tf.constant(0, shape=[101,32], dtype=tf.float32)
indices = tf.constant([], shape=[0,0,0,6], dtype=tf.int32)
updates = tf.constant([], shape=[0,0], dtype=tf.float32)
tf.raw_ops.TensorScatterMax(tensor=tensor, indices=indices, updates=updates)
```
```
import tensorflow as tf

tensor = tf.constant(0, shape=[101,32], dtype=tf.float32)
indices = tf.constant([], shape=[0,0,0,6], dtype=tf.int32)
updates = tf.constant([], shape=[0,0], dtype=tf.float32)
tf.raw_ops.TensorScatterMin(tensor=tensor, indices=indices, updates=updates)
```
```
import tensorflow as tf

tensor = tf.constant(0, shape=[101,32], dtype=tf.float32)
indices = tf.constant([], shape=[0,0,0,6], dtype=tf.int32)
updates = tf.constant([], shape=[0,0], dtype=tf.float32)
tf.raw_ops.TensorScatterSub(tensor=tensor, indices=indices, updates=updates)
```
```
import tensorflow as tf

tensor = tf.constant(0, shape=[101,32], dtype=tf.float32)
indices = tf.constant([], shape=[0,0,0,6], dtype=tf.int32)
updates = tf.constant([], shape=[0,0], dtype=tf.float32)
tf.raw_ops.TensorScatterUpdate(tensor=tensor, indices=indices, updates=updates)
```
```


### Relevant log output

```shell
2024-05-01 04:00:48.333921: F tensorflow/core/framework/tensor_shape.cc:357] Check failed: d < dims() (2 vs. 2)
Aborted (core dumped)
```
Repository: ui
Issue: [bug]: Doc error - the examples in the `ComboBox` section do not work - they are missing the `CommandList` element
Labels: bug

### Describe the bug

I've tried the code examples from https://ui.shadcn.com/docs/components/combobox and they didn't work.

I investigated and I think that the samples are missing a `CommandList` element 
```tsx
 <PopoverContent className="w-[200px] p-0">
        <Command>
          <CommandInput placeholder="Search framework..." />
          <CommandList> {/* <---- this is missing ---->*/}
          <CommandEmpty>No framework found.</CommandEmpty>
          <CommandGroup>
            {frameworks.map((framework) => (
              <CommandItem
                key={framework.value}
                value={framework.value}
                onSelect={(currentValue) => {
                  setValue(currentValue === value ? "" : currentValue)
                  setOpen(false)
                }}
              >
                <Check
                  className={cn(
                    "mr-2 h-4 w-4",
                    value === framework.value ? "opacity-100" : "opacity-0"
                  )}
                />
                {framework.label}
              </CommandItem>
            ))}
          </CommandGroup>
         </CommandList> {/* <---- this is missing ---->*/}
        </Command>
      </PopoverContent>
```

Version:
    "cmdk": "^1.0.0",
    "lucide-react": "^0.373.0",




Here's the error I got:
Uncaught TypeError: undefined is not iterable (cannot read property Symbol(Symbol.iterator))
    at Function.from (<anonymous>)
    at A (index.mjs:1:3990)
    at U2 (index.mjs:1:3003)
    at index.mjs:1:1763
    at index.mjs:1:10381
    at Map.forEach (<anonymous>)
    at index.mjs:1:10370
    at commitHookEffectListMount (react-dom.development.js:23150:26)
    at commitLayoutEffectOnFiber (react-dom.development.js:23268:17)
    at commitLayoutMountEffects_complete (react-dom.development.js:24688:9)
    
    

### Affected component/components

ComboBox

### How to reproduce

Create a fresh project based on the https://ui.shadcn.com/docs/installation/vite
Add the combo box to it
Click on the combo 
See the error

Or open:
https://stackblitz.com/github/noam-honig/shadcn-combobox-docs-bug
Click on the combo
See the error


### Codesandbox/StackBlitz link

https://stackblitz.com/github/noam-honig/shadcn-combobox-docs-bug

### Logs

```bash
Uncaught TypeError: undefined is not iterable (cannot read property Symbol(Symbol.iterator))
    at Function.from (<anonymous>)
    at A (index.mjs:1:3990)
    at U2 (index.mjs:1:3003)
    at index.mjs:1:1763
    at index.mjs:1:10381
    at Map.forEach (<anonymous>)
    at index.mjs:1:10370
    at commitHookEffectListMount (react-dom.development.js:23150:26)
    at commitLayoutEffectOnFiber (react-dom.development.js:23268:17)
    at commitLayoutMountEffects_complete (react-dom.development.js:24688:9)
```


### System Info

```bash
Windows, Chrome
```


### Before submitting

- [X] I've made research efforts and searched the documentation
- [X] I've searched for existing issues