check_val_every_n_epoch bug with list of dataloaders

Nobody has claimed this yet.

## 🐛 Bug

If you have a list of dataloaders (used in a continual learning setting) and `check_val_every_n_epoch` in the trainer is not equal to 1 then `validation_step()` won't return the index of the dataloader currently being used.

### To Reproduce

Dataloader for validation:

```
def val_dataloader(self):
return [DataLoader(ds, batch_size=self.batch_size, shuffle=True , num_workers=self.num_workers) for ds in self.test_datasets[:self.curr_index+1]]
```

Validation step:
```
def validation_step(self, val_batch, batch_idx, dataloader_idx=None):
if dataloader_idx:
print("data loader index provided")
```

Run this in a training loop with `check_val_every_n_epoch=1` and compare to `check_val_every_n_epoch=5`. The latter will always have `dataloader_idx=None`.

### Expected behavior

The dataloader_idx is always correctly provided independently of how often the validation is called.

### Environment

- PyTorch Lightning Version (e.g., 1.5.0): 1.5.4
- PyTorch Version (e.g., 1.10): 1.10.0 py3.8_cuda10.2_cudnn7.6.5_0
- Python version (e.g., 3.9): 3.8.3
- OS (e.g., Linux): Linux
- CUDA/cuDNN version: 10.1
- GPU models and configuration: v100
- How you installed PyTorch (`conda`, `pip`, source): conda

### Additional context

Thanks.

cc @carmocca @justusschock @ananthsub @ninginthecloud @rohitgr7