def nt_xent_loss(out1, out2, temperature=0.1):
"""Normalized Temperature-scaled Cross Entropy loss."""
out1 = F.normalize(out1, dim=1)
out2 = F.normalize(out2, dim=1)
out = torch.cat([out1, out2])
sim_matrix = F.cosine_similarity(out.unsqueeze(1), out.unsqueeze(0), dim=2)
sim_matrix = sim_matrix / temperature
mask = torch.eye(sim_matrix.shape[0]).bool().to(out.device)
pos_sim = sim_matrix[mask].view(out1.shape[0], 2).sum(dim=1)
pos_sim /= 2
loss = -pos_sim.mean()
return loss
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Let’s break down how to find what you’re actually looking for. dim=1) out2 = F.normalize(out2