def interact_features(self, x, ly):
if self.arch_interaction_op == "dot":
if self.bf16:
T = [x] + ly
R = ipex.interaction(*T)
else:
# concatenate dense and sparse features
(batch_size, d) = x.shape
T = torch.cat([x] + ly, dim=1).view((batch_size, -1, d))
# perform a dot product
Z = torch.bmm(T, torch.transpose(T, 1, 2))
# append dense feature with the interactions (into a row vector)
# approach 1: all
# Zflat = Z.view((batch_size, -1))
# approach 2: unique
_, ni, nj = Z.shape
# approach 1: tril_indices
# offset = 0 if self.arch_interaction_itself else -1
# li, lj = torch.tril_indices(ni, nj, offset=offset)
# approach 2: custom
offset = 1 if self.arch_interaction_itself else 0
li = torch.tensor(
[i for i in range(ni) for j in range(i + offset)])
lj = torch.tensor(
[j for i in range(nj) for j in range(i + offset)])
Zflat = Z[:, li, lj]
# concatenate dense features and interactions
R = torch.cat([x] + [Zflat], dim=1)
elif self.arch_interaction_op == "cat":
# concatenation features (into a row vector)
R = torch.cat([x] + ly, dim=1)
else:
sys.exit("ERROR: --arch-interaction-op=" +
self.arch_interaction_op + " is not supported")
return R
def interact_fusion(x, ly):
A = [x] + ly
R = ipex.interaction(*A)
return R