Comments (2)
muammar
commented on May 24, 2024
This class is now working for cases where the loss functions of models are independent (backward propagation occurs independently as well), and when they are summed (weights of all models are updated according to the gradient of all of them depending on each other).
The parallelization has to be worked out because a new forward() method was created.
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muammar
commented on May 24, 2024
The parallelization has been worked out because a new forward() method was added. I just tested with MSE loss functions. I also noticed that the independent loss function case is broken now.
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