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J is indexing each of the available style layers. Sl1 and Sl2 compute the loss separately for each of the J style images passed, and then sl computes the difference between each of these (sl1_j, sl2_j) pairs, and these differences are summed up using geometric weighing of the loss terms based on depth of the network.
Neural-Style-Transfer/INetwork.py
Line 513 in 536a96d
Between these two lines, sl is only decided by the last style image? Am I understanding it correctly?
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