Whether it is the same depends on the batchsizes of the two dataloaders and the network:

The first enforces the 1/4-3/4 weighting even if the batch sizes are not in that ratio. If the criterion self.crit takes the mean over batch size, this would be identical if the batch size is 3 duts inputs to 9 flick inputs.
If you have batch norm in your network, separate runs will take batch norms for the two runs through the network separately. Depending on whether both datasets generate similar statistics, this might give a difference. - They would also lead to different averages to be used in inference, but that likely doesn’t matter if you train for many epochs using the else branch. It may have an effect on the intermediate validation stats.

So it is likely close, but not the same.
Best regards
Thomas