Forcing BCE for DiceCELoss when overlapping labels predictions

[SebGoll]

Hello,

I have encountered multiple projects in which I need to output multiple labels for a single voxel. In this case, I'd like to use the DiceCELoss, but forcing it to use the binary cross entropy loss instead of the cross entropy one (since each channel predicted is either on or off independently of the other channels).
In the current state of DiceCELoss, it automatically choose to use either ce/bce based on the number of channels:

MONAI/monai/losses/dice.py

Line 804 in e72145c

ce_loss = self.ce(input, target) if input.shape[1] != 1 else self.bce(input, target)

I wanted to see if there is an officially supported way to achieve the behavior described above before contributing.

Thank you