Title: .map() fails if function uses pyvista
State: open

### Describe the bug

Using PyVista inside a .map() produces a crash with `objc[78796]: +[NSResponder initialize] may have been in progress in another thread when fork() was called. We cannot safely call it or ignore it in the fork() child process. Crashing instead. Set a breakpoint on objc_initializeAfterForkError to debug.`

### Steps to reproduce the bug

Run 

```python
import numpy as np
import pyvista as pv
import datasets

data = [{"coords": np.random.rand(5, 3)} for _ in range(3)]


def render_point(example):
  plotter = pv.Plotter(off_screen=True)
  cloud = pv.PolyData(example["coords"])
  plotter.add_mesh(cloud)
  img = plotter.screenshot(return_img=True)
  return {"image": img}


# breaks if num_proc>1
ds = datasets.Dataset.from_list(data).map(render_point, num_proc=2)

```

### Expected behavior

It should work. Just like when I use a process pool to make it work.

```python
import numpy as np
import pyvista as pv
import multiprocessing

data = [{"coords": np.random.rand(5, 3)} for _ in range(3)]


def render_point(example):
  plotter = pv.Plotter(off_screen=True)
  cloud = pv.PolyData(example["coords"])
  plotter.add_mesh(cloud)
  img = plotter.screenshot(return_img=True)
  return {"image": img}


if __name__ == "__main__":
  with multiprocessing.Pool(processes=2) as pool:
    results = pool.map(render_point, data)
  print(results[0]["image"].shape)
```

### Environment info


- `datasets` version: 3.3.2
- Platform: macOS-15.3.2-arm64-arm-64bit
- Python version: 3.11.10
- `huggingface_hub` version: 0.28.1
- PyArrow version: 18.1.0
- Pandas version: 2.2.3
- `fsspec` version: 2024.10.0

And then I suppose pyvista info is good to have.

```python
import pyvista as pv
print(pv.Report())
```
gives 
--------------------------------------------------------------------------------
  Date: Mon Apr 14 21:42:08 2025 CEST

                OS : Darwin (macOS 15.3.2)
            CPU(s) : 10
           Machine : arm64
      Architecture : 64bit
               RAM : 32.0 GiB
       Environment : IPython
       File system : apfs
        GPU Vendor : Apple
      GPU Renderer : Apple M1 Max
       GPU Version : 4.1 Metal - 89.3
  MathText Support : True

  Python 3.11.10 (main, Oct  7 2024, 23:25:27) [Clang 18.1.8 ]

           pyvista : 0.44.2
               vtk : 9.4.0
             numpy : 2.2.2
        matplotlib : 3.10.0
            scooby : 0.10.0
             pooch : 1.8.2
            pillow : 11.1.0
           imageio : 2.36.1
             PyQt5 : 5.15.11
           IPython : 8.30.0
             scipy : 1.14.1
              tqdm : 4.67.1
        jupyterlab : 4.3.5
      nest_asyncio : 1.6.0
--------------------------------------------------------------------------------

Comments: I found a similar (?) issue in https://github.com/huggingface/datasets/issues/6435, where someone had issues with forks and CUDA. According to https://huggingface.co/docs/datasets/main/en/process#multiprocessing we should do 

```
from multiprocess import set_start_method
set_start_method("spawn")
```

to avoid the fork. The updated code

```python
import numpy as np
import pyvista as pv
import datasets
import multiprocess

data = [{"coords": np.random.rand(5, 3)} for _ in range(3)]

def render_point(example):
  plotter = pv.Plotter(off_screen=True)
  cloud = pv.PolyData(example["coords"])
  plotter.add_mesh(cloud)
  img = plotter.screenshot(return_img=True)
  return {"image": img}


# breaks if num_proc>1
multiprocess.set_start_method("spawn")
ds = datasets.Dataset.from_list(data).map(render_point, num_proc=2)
```

instead fails with `TypeError: fork_exec() takes exactly 23 arguments (21 given)` which also seems like a bug to me.