def compute_loss(self, batch_source, batch_pos, batch_neg):
""" Compute the loss (BPR) for a batch of examples
:param batch_source: a batch of source keyphrase indices (list of lists)
:param batch_pos: True aliases of the Mentions
:param batch_neg: False aliases of the Mentions
"""
batch_size = len(batch_source)
avg_source = torch.mean(batch_source, dim=1)
avg_pos = torch.mean(batch_pos, dim=1)
avg_neg = torch.mean(batch_neg, dim=1)
# B by dim
source_embed = self.embed(avg_source)
# B by dim
pos_embed = self.embed(avg_pos)
# B by dim
neg_embed = self.embed(avg_neg)
loss = self._bce_loss(
utils.row_wise_dot(source_embed, pos_embed) -
utils.row_wise_dot(source_embed, neg_embed),
self.ones[:batch_size])
return loss
def score_pair(self, source, target, source_len, target_len):
"""
:param source: Batchsize by Max_String_Length
:param target: Batchsize by Max_String_Length
:return: Batchsize by 1
"""
source_embed = self.embed_dev(source, source_len)
target_embed = self.embed_dev(target, target_len)
scores = utils.row_wise_dot(source_embed, target_embed)
return scores
def compute_loss(self, batch_source, pos_result, neg_result, batch_lengths,
pos_len, neg_len):
""" Compute the loss (BPR) for a batch of examples
:param batch_source: a batch of source keyphrase indices (list of lists)
:param pos_result: True aliases of the Mentions
:param neg_result: False aliases of the Mentions
:param batch_lengths: a list of sample lengths, one for each sample in the batch (list of lists)
:param pos_len: lengths of positives
:param neg_len: lengths of negatives
:return:
"""
batch_size = len(batch_source)
# B by dim
source_embed = self.embed(batch_source, batch_lengths)
# B by dim
pos_embed = self.embed(pos_result, pos_len)
# B by dim
neg_embed = self.embed(neg_result, neg_len)
loss = self._bce_loss(
utils.row_wise_dot(source_embed, pos_embed) -
utils.row_wise_dot(source_embed, neg_embed),
self.ones[:batch_size])
return loss
def score_dev_test_batch(self, batch_queries, batch_targets, batch_size):
if batch_size == self.config.dev_batch_size:
source_embed = self.embed_dev(batch_queries)
target_embed = self.embed_dev(batch_targets)
else:
source_embed = self.embed_dev(batch_queries, batch_size=batch_size)
target_embed = self.embed_dev(batch_targets, batch_size=batch_size)
scores = utils.row_wise_dot(source_embed, target_embed)
# what is this?
scores[scores != scores] = 0
return scores