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Stop token layer on decoder

This commit is contained in:
Eren Golge 2018-05-11 04:14:27 -07:00
parent 1d8ad0968c
commit 3ea1a5358d
1 changed files with 7 additions and 1 deletions
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8
layers/tacotron.py
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@ -232,6 +232,7 @@ class Decoder(nn.Module):
[nn.GRUCell(256, 256) for _ in range(2)]) [nn.GRUCell(256, 256) for _ in range(2)])
# RNN_state -> |Linear| -> mel_spec # RNN_state -> |Linear| -> mel_spec
self.proj_to_mel = nn.Linear(256, memory_dim * r) self.proj_to_mel = nn.Linear(256, memory_dim * r)
self.stopnet = nn.Sequential(nn.Dropout(0.2), nn.Linear(memory_dim * self.r, 1), nn.Sigmoid())
def forward(self, inputs, memory=None): def forward(self, inputs, memory=None):
""" """
@ -272,6 +273,7 @@ class Decoder(nn.Module):
memory = memory.transpose(0, 1) memory = memory.transpose(0, 1)
outputs = [] outputs = []
alignments = [] alignments = []
stop_tokens = []
t = 0 t = 0
memory_input = initial_memory memory_input = initial_memory
while True: while True:
@ -297,8 +299,11 @@ class Decoder(nn.Module):
output = decoder_input output = decoder_input
# predict mel vectors from decoder vectors # predict mel vectors from decoder vectors
output = self.proj_to_mel(output) output = self.proj_to_mel(output)
# predict stop token
stop_token = self.stopnet(output)
outputs += [output] outputs += [output]
alignments += [alignment] alignments += [alignment]
stop_tokens += stop_token
t += 1 t += 1
if (not greedy and self.training) or (greedy and memory is not None): if (not greedy and self.training) or (greedy and memory is not None):
if t >= T_decoder: if t >= T_decoder:
@ -314,7 +319,8 @@ class Decoder(nn.Module):
# Back to batch first # Back to batch first
alignments = torch.stack(alignments).transpose(0, 1) alignments = torch.stack(alignments).transpose(0, 1)
outputs = torch.stack(outputs).transpose(0, 1).contiguous() outputs = torch.stack(outputs).transpose(0, 1).contiguous()
return outputs, alignments stop_tokens = torch.stack(stop_tokens).transpose(0, 1)
return outputs, alignments, stop_tokens
def is_end_of_frames(output, alignment, eps=0.05): # 0.2 def is_end_of_frames(output, alignment, eps=0.05): # 0.2