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break out get_conditioning_latent from unified_voice

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This commit is contained in:
James Betker 2022-05-01 23:04:44 -06:00
parent afa2df57c9
commit b712d3b72b
2 changed files with 13 additions and 8 deletions
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19
codes/models/audio/tts/unified_voice2.py
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@ -365,6 +365,17 @@ class UnifiedVoice(nn.Module):
else:
return first_logits
def get_conditioning_latent(self, speech_conditioning_input):
speech_conditioning_input = speech_conditioning_input.unsqueeze(1) if len(speech_conditioning_input.shape) == 3 else speech_conditioning_input
conds = []
for j in range(speech_conditioning_input.shape[1]):
conds.append(self.conditioning_encoder(speech_conditioning_input[:, j]))
conds = torch.stack(conds, dim=1)
if self.average_conditioning_embeddings:
conds = conds.mean(dim=1).unsqueeze(1)
return conds
def forward(self, speech_conditioning_input, text_inputs, text_lengths, mel_codes, wav_lengths, types=None, text_first=True, raw_mels=None, return_attentions=False,
return_latent=False, clip_inputs=True):
"""
@ -399,13 +410,7 @@ class UnifiedVoice(nn.Module):
text_inputs = F.pad(text_inputs, (0,1), value=self.stop_text_token)
mel_codes = F.pad(mel_codes, (0,1), value=self.stop_mel_token)
speech_conditioning_input = speech_conditioning_input.unsqueeze(1) if len(speech_conditioning_input.shape) == 3 else speech_conditioning_input
conds = []
for j in range(speech_conditioning_input.shape[1]):
conds.append(self.conditioning_encoder(speech_conditioning_input[:, j]))
conds = torch.stack(conds, dim=1)
if self.average_conditioning_embeddings:
conds = conds.mean(dim=1).unsqueeze(1)
conds = self.get_conditioning_latent(speech_conditioning_input)
text_inputs, text_targets = self.build_aligned_inputs_and_targets(text_inputs, self.start_text_token, self.stop_text_token)
text_emb = self.text_embedding(text_inputs) + self.text_pos_embedding(text_inputs)

2
codes/train.py
View File

@ -327,7 +327,7 @@ class Trainer:
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument('-opt', type=str, help='Path to option YAML file.', default='../options/train_tortoise_reverse_classifier.yml')
parser.add_argument('-opt', type=str, help='Path to option YAML file.', default='../options/train_tortoise_random_latent_gen.yml')
parser.add_argument('--launcher', choices=['none', 'pytorch'], default='none', help='job launcher')
args = parser.parse_args()
opt = option.parse(args.opt, is_train=True)