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add hifigan train

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This commit is contained in:
lyuxiang.lx
2024-10-16 11:37:32 +08:00
parent cb200b21c5
commit 789ee9e5e7
13 changed files with 314 additions and 477 deletions
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6
cosyvoice/dataset/dataset.py
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@@ -126,6 +126,7 @@ class DataList(IterableDataset):
def Dataset(data_list_file,
data_pipeline,
mode='train',
gan=False,
shuffle=True,
partition=True,
tts_file='',
@@ -153,8 +154,11 @@ def Dataset(data_list_file,
shuffle=shuffle,
partition=partition)
if mode == 'inference':
# map partial arg tts_data in inference mode
# map partial arg to parquet_opener func in inference mode
data_pipeline[0] = partial(data_pipeline[0], tts_data=tts_data)
if gan is True:
# map partial arg to padding func in gan mode
data_pipeline[-1] = partial(data_pipeline[-1], gan=gan)
for func in data_pipeline:
dataset = Processor(dataset, func, mode=mode)
return dataset

20
cosyvoice/dataset/processor.py
View File

@@ -350,7 +350,7 @@ def batch(data, batch_type='static', batch_size=16, max_frames_in_batch=12000, m
logging.fatal('Unsupported batch type {}'.format(batch_type))
def padding(data, use_spk_embedding, mode='train'):
def padding(data, use_spk_embedding, mode='train', gan=False):
""" Padding the data into training data
Args:
@@ -379,11 +379,6 @@ def padding(data, use_spk_embedding, mode='train'):
speech_feat = pad_sequence(speech_feat,
batch_first=True,
padding_value=0)
pitch_feat = [sample[i]['pitch_feat'] for i in order]
pitch_feat_len = torch.tensor([i.size(0) for i in pitch_feat], dtype=torch.int32)
pitch_feat = pad_sequence(pitch_feat,
batch_first=True,
padding_value=0)
text = [sample[i]['text'] for i in order]
text_token = [torch.tensor(sample[i]['text_token']) for i in order]
text_token_len = torch.tensor([i.size(0) for i in text_token], dtype=torch.int32)
@@ -406,6 +401,19 @@ def padding(data, use_spk_embedding, mode='train'):
"utt_embedding": utt_embedding,
"spk_embedding": spk_embedding,
}
if gan is True:
# in gan train, we need pitch_feat
pitch_feat = [sample[i]['pitch_feat'] for i in order]
pitch_feat_len = torch.tensor([i.size(0) for i in pitch_feat], dtype=torch.int32)
pitch_feat = pad_sequence(pitch_feat,
batch_first=True,
padding_value=0)
batch["pitch_feat"] = pitch_feat
batch["pitch_feat_len"] = pitch_feat_len
else:
# only gan train needs speech, delete it to save memory
del batch["speech"]
del batch["speech_len"]
if mode == 'inference':
tts_text = [sample[i]['tts_text'] for i in order]
tts_index = [sample[i]['tts_index'] for i in order]