How to combine multiple criterions to a loss function?

8

Doing that is fine, it would be:

b = nn.MSELoss()(output_x, x_labels)
a = nn.CrossEntropyLoss()(output_y, y_labels)
loss = a + b

loss.backward()

Note the additional parentheses, as James mentioned above.

This is equivalent to:

b = nn.MSELoss()
a = nn.CrossEntropyLoss()

loss_a = a(output_x, x_labels)
loss_b = b(output_y, y_labels)

loss = loss_a + loss_b

loss.backward()
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