Medix-AI/coqui-tts
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coqui-tts
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normal attention

This commit is contained in:
Eren Golge 2018-03-25 12:01:41 -07:00
parent ed35ae7e20
commit 632c08a638
1 changed files with 9 additions and 11 deletions
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20
layers/attention.py
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@ -57,11 +57,19 @@ class AttentionRNN(nn.Module):
if annotations_lengths is not None and mask is None:
mask = get_mask_from_lengths(annotations, annotations_lengths)
# Concat input query and previous context context
rnn_input = torch.cat((memory, context), -1)
#rnn_input = rnn_input.unsqueeze(1)
# Feed it to RNN
# s_i = f(y_{i-1}, c_{i}, s_{i-1})
rnn_output = self.rnn_cell(rnn_input, rnn_state)
# Alignment
# (batch, max_time)
# e_{ij} = a(s_{i-1}, h_j)
alignment = self.alignment_model(annotations, rnn_state)
alignment = self.alignment_model(annotations, rnn_output)
# TODO: needs recheck.
if mask is not None:
@ -75,16 +83,6 @@ class AttentionRNN(nn.Module):
# (batch, 1, dim)
# c_i = \sum_{j=1}^{T_x} \alpha_{ij} h_j
context = torch.bmm(alignment.unsqueeze(1), annotations)
context = context.squeeze(1)
# Concat input query and previous context context
rnn_input = torch.cat((memory, context), -1)
#rnn_input = rnn_input.unsqueeze(1)
# Feed it to RNN
# s_i = f(y_{i-1}, c_{i}, s_{i-1})
rnn_output = self.rnn_cell(rnn_input, rnn_state)
context = context.squeeze(1)
return rnn_output, context, alignment