Allow Using Specific Dataloaders in LightningCLI (Instead of a DataModule)

Nobody has claimed this yet.

### Description & Motivation

I would like to configure the LightningCLI to use dataloaders in the `test` subcommand, similar to this example from [the docs](https://lightning.ai/docs/pytorch/stable/common/trainer.html#testing)
```python
trainer.test(dataloaders=test_dataloaders)
```

As far as I can tell this impossible using the LightningCLI because you can only pass a `datamodule` into it. My test set is defined differently from various training sets I have so this becomes annoying to create separate datamodules for each.

You can see that the `dataloaders` option is specifically ignored in [the `cli.py` `subcommands` method](https://github.com/Lightning-AI/pytorch-lightning/blob/df5dee674243e124a2bf34d9975dd586ff008d4b/src/lightning/pytorch/cli.py#L476).

### Pitch

I would like to specify `dataloaders` in the `LightningCLI`. Perhaps like:

```python
LightningCLI(
MyModule,
train_dataloaders=MyTrainDataloader,
test_dataloaders=MyTestDataloader,
args=args
)
```

### Alternatives

The alternative is having to create different datamodules for every combination of train/test dataloaders.
Or you have to simply just not use the CLI stuff and call lightning directly.

### Additional context

I would be willing to open a PR if this feature is deemed useful.

cc @lantiga @borda @mauvilsa

Start in src/lightning/pytorch/cli.py at the subcommands method, where the issue says the dataloaders option is ignored, and compare the supported LightningCLI inputs with the trainer.test(dataloaders=...) usage in the linked documentation. Done means the CLI can configure test dataloaders without requiring a separate datamodule, with the requested train and test dataloader forms accounted for.

Written by the indexing model from the issue text.