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About two softmax outputs #3
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Hi, |
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. |
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.
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