LightningModule self.log add_dataloader_idx doesn't reduce properly the metric across dataloaders

Nobody has claimed this yet.

## 🐛 Bug

### To Reproduce

The current behavior with `add_dataloader_idx` seems quite confusing to me. As a user, I don't know if I would expect to get the value reduced across all dataloaders and be added to both results objects.

```py
def test_multiple_dataloaders_logging(tmpdir):
class TestModel(BoringModel):
def validation_step(self, batch, batch_idx, dataloader_idx):
self.log("value_1", dataloader_idx, add_dataloader_idx=False)
self.log("value_2", dataloader_idx, add_dataloader_idx=True)

def val_dataloader(self):
return [self.train_dataloader(), self.train_dataloader()]

model = TestModel()
model.validation_epoch_end = None
trainer = Trainer(default_root_dir=tmpdir)
results = trainer.validate(model)
assert results == [
{"value_2/dataloader_idx_0": 0.0, "value_1": 0.5},
{"value_2/dataloader_idx_1": 1.0, "value_1": 0.5},
]
```

### Expected behavior

### Environment

- PyTorch Lightning Version (e.g., 1.5.0):
- PyTorch Version (e.g., 1.10):
- Python version (e.g., 3.9):
- OS (e.g., Linux):
- CUDA/cuDNN version:
- GPU models and configuration:
- How you installed PyTorch (`conda`, `pip`, source):
- If compiling from source, the output of `torch.__config__.show()`:
- Any other relevant information:

### Additional context

cc @tchaton

Start with LightningModule.self.log, the validation_step example, and Trainer.validate using the provided BoringModel reproduction. Trace how value_1 and value_2 are reduced across the two dataloaders, then add or update the multiple-dataloader logging test so the agreed reduction behavior is verified.

Written by the indexing model from the issue text.