About two softmax outputs

[321hallelujah]

Hi,
When SSLtraining In your paper, you claim to use two softmax for the pseudo-task. However, in this code, it seems you use tf.split to split the prediction（eg. 8 class for all, and 4 for skip ,the other 4 for transforms）, which lead to only one softmax. what is the difference about this, or just my misunderstanding.
Looking forward to your reply.

[sjenni]

Hi,
Thanks for the question. The softmax is applied in the loss function, so in the end, two softmax functions are applied.
The code with splitting should be equivalent to two separate heads. Hope that clarifies the issue? :)
Cheers

[321hallelujah]

I got it! the split variable is just fully_connected output of C3D. So it can be split to any pseudo-task. The softmax is applied in every loss function. Finally, the learned temporal-spatial representation is a concatenation style of two pseudo-task.
Is it right? Thanks