TorchScript export incompatible with DeviceDtypeModuleMixin properties

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## 🐛 Bug

My model code makes extensive use of tensors created during the forward pass. As part of this, I have to specify the device associated with each tensor to avoid conflicts. I want to export my model in TorchScript for deployment elsewhere, but the DeviceDtypeModuleMixin properties do not appear to be compatible with TorchScript.

While this appears to affect the `dtype` property too, for my use case, using `self.device` in a LightningModule prevents successful TorchScript export.

### To Reproduce

```python
import pytorch_lightning as pl
import torch

class TestModel(pl.LightningModule):
def forward(self):
return torch.zeros((2, 2), device=self.device)

model = TestModel()
model.to_torchscript()
```

results in the following error:

```
RuntimeError:
Module 'TestModel' has no attribute 'device' :
File "/test.py", line 7
def forward(self):
return torch.zeros((2, 2), device=self.device)
~~~~~~~~~~~ <--- HERE
```

I am not sure how this can be fixed without changing the way DeviceDtypeModuleMixin works. It relies on the `@property` decorator, which uses descriptors. [TorchScript is not compatible with descriptors (3.3.2.2, 3.3.2.3)](https://pytorch.org/docs/stable/jit_python_reference.html#python-language-reference).

Additionally, the `device` property returns a `Union[str, torch.device]`, so even if it worked as a property in TorchScript, the return value of the function is incompatible with the type expected by the `device` keyword option (`Optional[Device]`). There appears to have been some discussion of this in [this issue](https://github.com/Lightning-AI/lightning/issues/1951), but I'm not sure how it was resolved.

I am happy to try contributing a solution, but I wanted to discuss here first. A possible solution seems to involve eliminating the `@property` decorator and save the current state of the device as a plain `device` attribute on the model object. The actions currently in the `device()` function body should be performed as the `device` attribute is being set rather than on the way out.

### Expected behavior

The code shown above is successfully saved as TorchScript.

### Environment

- Lightning Component (e.g. Trainer, LightningModule, LightningApp, LightningWork, LightningFlow): LightningModule
- PyTorch Lightning Version (e.g., 1.5.0): 1.6.5
- PyTorch Version (e.g., 1.10): 1.12.0
- Python version (e.g., 3.9): 3.9.13
- OS (e.g., Linux): Linux
- CUDA/cuDNN version: 11.6
- How you installed PyTorch (`conda`, `pip`, source): pip

cc @carmocca @justusschock @awaelchli @borda @ananthsub @ninginthecloud @jjenniferdai @rohitgr7

Start with LightningModule.to_torchscript and the DeviceDtypeModuleMixin device and dtype properties, then run the provided TestModel reproduction with the stated versions. The work is done when a model using self.device can be successfully exported as TorchScript, with coverage for the reported behavior.

Written by the indexing model from the issue text.