60 lines
2.4 KiB
Python
60 lines
2.4 KiB
Python
|
import paddle.fluid.dygraph as dg
|
||
|
|
import paddle.fluid as fluid
|
||
|
|
from parakeet.modules.utils import *
|
||
|
|
from parakeet.models.fastspeech.FFTBlock import FFTBlock
|
||
|
|
|
||
|
|
class Decoder(dg.Layer):
|
||
|
|
def __init__(self,
|
||
|
|
len_max_seq,
|
||
|
|
n_layers,
|
||
|
|
n_head,
|
||
|
|
d_k,
|
||
|
|
d_v,
|
||
|
|
d_model,
|
||
|
|
d_inner,
|
||
|
|
fft_conv1d_kernel,
|
||
|
|
fft_conv1d_padding,
|
||
|
|
dropout=0.1):
|
||
|
|
super(Decoder, self).__init__()
|
||
|
|
|
||
|
|
n_position = len_max_seq + 1
|
||
|
|
self.pos_inp = get_sinusoid_encoding_table(n_position, d_model, padding_idx=0)
|
||
|
|
self.position_enc = dg.Embedding(size=[n_position, d_model],
|
||
|
|
padding_idx=0,
|
||
|
|
param_attr=fluid.ParamAttr(
|
||
|
|
initializer=fluid.initializer.NumpyArrayInitializer(self.pos_inp),
|
||
|
|
trainable=False))
|
||
|
|
self.layer_stack = [FFTBlock(d_model, d_inner, n_head, d_k, d_v, fft_conv1d_kernel, fft_conv1d_padding, dropout=dropout) for _ in range(n_layers)]
|
||
|
|
for i, layer in enumerate(self.layer_stack):
|
||
|
|
self.add_sublayer('fft_{}'.format(i), layer)
|
||
|
|
|
||
|
|
def forward(self, enc_seq, enc_pos):
|
||
|
|
"""
|
||
|
|
Decoder layer of FastSpeech.
|
||
|
|
|
||
|
|
Args:
|
||
|
|
enc_seq (Variable), Shape(B, text_T, C), dtype: float32.
|
||
|
|
The output of length regulator.
|
||
|
|
enc_pos (Variable, optional): Shape(B, T_mel),
|
||
|
|
dtype: int64. The spectrum position. T_mel means the timesteps of input spectrum.
|
||
|
|
Returns:
|
||
|
|
dec_output (Variable), Shape(B, mel_T, C), the decoder output.
|
||
|
|
dec_slf_attn_list (Variable), Shape(B, mel_T, mel_T), the decoder self attention list.
|
||
|
|
"""
|
||
|
|
dec_slf_attn_list = []
|
||
|
|
|
||
|
|
# -- Prepare masks
|
||
|
|
slf_attn_mask = get_attn_key_pad_mask(seq_k=enc_pos, seq_q=enc_pos)
|
||
|
|
non_pad_mask = get_non_pad_mask(enc_pos)
|
||
|
|
|
||
|
|
# -- Forward
|
||
|
|
dec_output = enc_seq + self.position_enc(enc_pos)
|
||
|
|
|
||
|
|
for dec_layer in self.layer_stack:
|
||
|
|
dec_output, dec_slf_attn = dec_layer(
|
||
|
|
dec_output,
|
||
|
|
non_pad_mask=non_pad_mask,
|
||
|
|
slf_attn_mask=slf_attn_mask)
|
||
|
|
dec_slf_attn_list += [dec_slf_attn]
|
||
|
|
|
||
|
|
return dec_output, dec_slf_attn_list
|