def _get_triple_score(self, head: BoxTensor, tail: BoxTensor,
relation: BoxTensor) -> torch.Tensor:
if self.is_eval():
if len(head.data.shape) > len(tail.data.shape):
tail.data = torch.cat(head.data.shape[-3] * [tail.data])
relation.data = torch.cat(head.data.shape[-3] *
[relation.data])
elif len(head.data.shape) < len(tail.data.shape):
head.data = torch.cat(tail.data.shape[-3] * [head.data])
relation.data = torch.cat(tail.data.shape[-3] *
[relation.data])
head_relation_box = relation.gumbel_intersection(
head, gumbel_beta=self.gumbel_beta)
tail_relation_box = relation.gumbel_intersection(
tail, gumbel_beta=self.gumbel_beta)
tail_head_relation_box = tail_relation_box.gumbel_intersection(
head, gumbel_beta=self.gumbel_beta)
tail_head_relation_box_vol = tail_head_relation_box._log_soft_volume_adjusted(
tail_head_relation_box.z,
tail_head_relation_box.Z,
temp=self.softbox_temp,
gumbel_beta=self.gumbel_beta)
tail_relation_box_vol = tail_relation_box._log_soft_volume_adjusted(
tail_relation_box.z,
tail_relation_box.Z,
temp=self.softbox_temp,
gumbel_beta=self.gumbel_beta)
score_head = tail_head_relation_box_vol - tail_relation_box_vol
return score_head
def _get_triple_score(self, head: BoxTensor, tail: BoxTensor,
relation: BoxTensor) -> torch.Tensor:
intersection_box = head.gumbel_intersection(
tail, gumbel_beta=self.gumbel_beta)
intersection_vol = intersection_box._log_soft_volume_adjusted(
intersection_box.z,
intersection_box.Z,
temp=self.softbox_temp,
gumbel_beta=self.gumbel_beta)
tail_vol = tail._log_soft_volume_adjusted(tail.z,
tail.Z,
temp=self.softbox_temp,
gumbel_beta=self.gumbel_beta)
score = intersection_vol - tail_vol
return score
def _get_triple_score(self, head: BoxTensor, tail: BoxTensor,
relation: BoxTensor) -> torch.Tensor:
if self.is_eval():
if len(head.data.shape) > len(tail.data.shape):
tail.data = torch.cat(head.data.shape[-3] * [tail.data])
elif len(head.data.shape) < len(tail.data.shape):
head.data = torch.cat(tail.data.shape[-3] * [head.data])
intersection_box = head.gumbel_intersection(
tail, gumbel_beta=self.gumbel_beta)
intersection_vol = intersection_box._log_bessel_volume(
intersection_box.z,
intersection_box.Z,
gumbel_beta=self.gumbel_beta)
tail_vol = tail._log_bessel_volume(tail.z,
tail.Z,
gumbel_beta=self.gumbel_beta)
score = intersection_vol - tail_vol
return score
def _get_triple_score(self, head: BoxTensor, tail: BoxTensor,
relation: BoxTensor) -> torch.Tensor:
if self.is_eval():
if len(head.data.shape) > len(tail.data.shape):
tail.data = torch.cat(head.data.shape[-3] * [tail.data])
elif len(head.data.shape) < len(tail.data.shape):
head.data = torch.cat(tail.data.shape[-3] * [head.data])
head_sample = self.reparam_trick(head,
gumbel_beta=self.gumbel_beta,
n_samples=self.n_samples)
tail_sample = self.reparam_trick(tail,
gumbel_beta=self.gumbel_beta,
n_samples=self.n_samples)
intersection_sample_box = head_sample.gumbel_intersection(
tail_sample, gumbel_beta=self.gumbel_beta)
intersection_box = head.gumbel_intersection(
tail, gumbel_beta=self.gumbel_beta)
intersection_volume_fwd = intersection_sample_box._log_gumbel_volume(
intersection_sample_box.z, intersection_box.Z)
intersection_volume_bwd = intersection_sample_box._log_gumbel_volume(
intersection_box.z, intersection_sample_box.Z)
tail_volume_fwd = tail_sample._log_gumbel_volume(tail.z, tail_sample.Z)
tail_volume_bwd = tail_sample._log_gumbel_volume(tail_sample.z, tail.Z)
# score = (intersection_volume_fwd + intersection_volume_bwd)/2 - (
# tail_volume_fwd + tail_volume_bwd)/2
intersection_score = torch.logsumexp(
torch.stack((intersection_volume_fwd, intersection_volume_bwd)), 0)
tail_score = torch.logsumexp(
torch.stack((tail_volume_fwd, tail_volume_bwd)), 0)
score = intersection_score - tail_score
if len(torch.where(score > 0)[0]):
breakpoint()
return score
