Distributed mode overwrites the user's choice for dataloaders shuffling

🐛 Bug

I ordered my training data in a specific manner and passed it to the DataLoader with shuffle=False (I use reload_dataloaders_every_n_epochs=1 to control it every epoch). Then, I found out that running in distributed mode re-creates the train dataloader and always set shuffle=True. The opposite happens for the val dataloader.

I think that the re-creation of the dataloaders must be using the same shuffle setting the original dataloaders had. Is there any reason not to do so?

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Here is the related code with the hard-coded shuffle values:

train - shuffle forced to be true https://github.com/PyTorchLightning/pytorch-lightning/blob/c33df2639f19d49c5e7520294e3221efe402d684/pytorch_lightning/trainer/data_loading.py#L330-L333

val - shuffle forced to be true https://github.com/PyTorchLightning/pytorch-lightning/blob/c33df2639f19d49c5e7520294e3221efe402d684/pytorch_lightning/trainer/data_loading.py#L442-L443

cc @borda @justusschock @awaelchli