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Enable optional forward attention with transition agent

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Eren Golge
2019-04-10 16:41:30 +02:00
parent e2cf35bb10
commit 312a539a0e
4 changed files with 46 additions and 29 deletions
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models/tacotron2.py
+2 -2
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@@ -9,7 +9,7 @@ from utils.generic_utils import sequence_mask
# TODO: match function arguments with tacotron
class Tacotron2(nn.Module):
def __init__(self, num_chars, r, attn_win=False, attn_norm="softmax", prenet_type="original", forward_attn=False):
def __init__(self, num_chars, r, attn_win=False, attn_norm="softmax", prenet_type="original", forward_attn=False, trans_agent=False):
super(Tacotron2, self).__init__()
self.n_mel_channels = 80
self.n_frames_per_step = r
@@ -18,7 +18,7 @@ class Tacotron2(nn.Module):
val = sqrt(3.0) * std # uniform bounds for std
self.embedding.weight.data.uniform_(-val, val)
self.encoder = Encoder(512)
self.decoder = Decoder(512, self.n_mel_channels, r, attn_win, attn_norm, prenet_type, forward_attn)
self.decoder = Decoder(512, self.n_mel_channels, r, attn_win, attn_norm, prenet_type, forward_attn, trans_agent)
self.postnet = Postnet(self.n_mel_channels)
def shape_outputs(self, mel_outputs, mel_outputs_postnet, alignments):