def forward(self, context, question):
context = LongVar(context)
question = LongVar(question)
batch_size, context_size = context.size()
_, question_size = question.size()
context = self.__(self.embed(context), 'context_emb')
question = self.__(self.embed(question), 'question_emb')
context = context.transpose(1, 0)
C, _ = self.__(
self.encode(context, init_hidden(batch_size, self.encode)), 'C')
C = self.__(C.transpose(1, 0), 'C')
s = self.__(self.sentinel(batch_size), 's')
C = self.__(torch.cat([C, s], dim=1), 'C')
question = question.transpose(1, 0)
Q, _ = self.__(
self.encode(question, init_hidden(batch_size, self.encode)), 'Q')
Q = self.__(Q.transpose(1, 0), 'Q')
s = self.__(self.sentinel(batch_size), 's')
Q = self.__(torch.cat([Q, s], dim=1), 'Q')
squashedQ = self.__(Q.view(batch_size * (question_size + 1), -1),
'squashedQ')
transformedQ = self.__(F.tanh(self.linear(Q)), 'transformedQ')
Q = self.__(Q.view(batch_size, question_size + 1, -1), 'Q')
affinity = self.__(torch.bmm(C, Q.transpose(1, 2)), 'affinity')
affinity = F.softmax(affinity, dim=-1)
context_attn = self.__(affinity.transpose(1, 2), 'context_attn')
question_attn = self.__(affinity, 'question_attn')
context_question = self.__(torch.bmm(C.transpose(1, 2), question_attn),
'context_question')
context_question = self.__(
torch.cat([Q, context_question.transpose(1, 2)], -1),
'context_question')
attn_cq = self.__(
torch.bmm(context_question.transpose(1, 2), context_attn),
'attn_cq')
attn_cq = self.__(attn_cq.transpose(1, 2).transpose(0, 1), 'attn_cq')
hidden = self.__(init_hidden(batch_size, self.attend), 'hidden')
final_repr, _ = self.__(self.attend(attn_cq, hidden), 'final_repr')
final_repr = self.__(final_repr.transpose(0, 1), 'final_repr')
return final_repr[:, :-1] #exclude sentinel
def batchop(datapoints, VOCAB, config, *args, **kwargs):
indices = [d.id for d in datapoints]
sequence = []
for d in datapoints:
sequence.append([VOCAB[w] for w in d.sequence])
sequence = LongVar(config, pad_seq(sequence))
sequence = sequence.transpose(1, 0)
batch = indices, (sequence[:-1]), (sequence[1:])
return batch
