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import os
import torch
import torch.nn.functional as F
from torch import nn
from text_to_speech.modules.tts.syntaspeech.syntaspeech import SyntaSpeech
from tasks.tts.ps_adv import PortaSpeechAdvTask
from text_to_speech.utils.commons.hparams import hparams
class SyntaSpeechTask(PortaSpeechAdvTask):
def build_tts_model(self):
ph_dict_size = len(self.token_encoder)
word_dict_size = len(self.word_encoder)
self.model = SyntaSpeech(ph_dict_size, word_dict_size, hparams)
self.gen_params = [p for p in self.model.parameters() if p.requires_grad]
self.dp_params = [p for k, p in self.model.named_parameters() if (('dur_predictor' in k) and p.requires_grad)]
self.gen_params_except_dp = [p for k, p in self.model.named_parameters() if (('dur_predictor' not in k) and p.requires_grad)]
self.bert_params = [p for k, p in self.model.named_parameters() if (('bert' in k) and p.requires_grad)]
self.gen_params_except_bert_and_dp = [p for k, p in self.model.named_parameters() if ('dur_predictor' not in k) and ('bert' not in k) and p.requires_grad ]
self.use_bert = True if len(self.bert_params) > 0 else False
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