commit
ddd9cdfbd8
|
@ -599,14 +599,13 @@ class ConditionalWaveNet(nn.Layer):
|
|||
self.decoder.start_sequence()
|
||||
x_t = paddle.zeros((batch_size, ), dtype=mel.dtype)
|
||||
for i in trange(time_steps):
|
||||
c_t = condition[:, :, i]
|
||||
y_t = self.decoder.add_input(x_t, c_t)
|
||||
c_t = condition[:, :, i] # (B, C)
|
||||
y_t = self.decoder.add_input(x_t, c_t) #(B, C)
|
||||
y_t = paddle.unsqueeze(y_t, 1)
|
||||
x_t = self.sample(y_t)
|
||||
x_t = paddle.squeeze(x_t, 1)
|
||||
x_t = self.sample(y_t) # (B, 1)
|
||||
x_t = paddle.squeeze(x_t, 1) #(B,)
|
||||
samples.append(x_t)
|
||||
|
||||
samples = paddle.concat(samples, -1)
|
||||
samples = paddle.stack(samples, -1)
|
||||
return samples
|
||||
|
||||
@paddle.no_grad()
|
||||
|
|
Loading…
Reference in New Issue