Negative JSELoss

[HannesStark]

I was initially confused by getting a negative loss using the JSELoss and by the implementation here where the Jensen Shannon Divergence is shifted:

DIG/dig/sslgraph/sslgraph/contrastive/objectives/jse.py

Lines 137 to 142 in 1e27dca

	log_2 = np.log(2.)
	if positive:
	score = log_2 - F.softplus(-masked_d_prime)
	else:
	score = F.softplus(-masked_d_prime) + masked_d_prime - log_2
	return score

To avoid others stumbling over this:
Apparently, this choice was made for consistency with other divergences, and it does not affect anything in training and model performance.
This issue in the Deep Infomax library explains why the shift is included rdevon/DIM#19

[ycremar]

Thank you, @HannesStark !