public code v1

pygrex/utils/emp_loss.py

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+import torch
+
+
+class EMFLoss(torch.nn.Module):
+    def __init__(self):
+        super(EMFLoss, self).__init__()
+
+    def forward(self, ratings_pred, ratings, u, v, reg_term, expl, expl_reg_term):
+
+        mse = (ratings - ratings_pred.view(-1)) ** 2
+        u_l2 = reg_term * torch.norm(u, 2, -1)
+        v_l2 = reg_term * torch.norm(v, 2, -1)
+        expl_constraint = expl_reg_term * torch.norm(u - v, 1, -1) * expl
+
+        loss = mse + u_l2 + v_l2 + expl_constraint
+
+        return loss.mean()