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fix lint

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lyuxiang.lx
2025-12-10 02:17:00 +00:00
parent a051a09ba4
commit 927addadd8
14 changed files with 75 additions and 59 deletions
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8
cosyvoice/flow/flow.py
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@@ -402,11 +402,12 @@ class CausalMaskedDiffWithDiT(torch.nn.Module):
assert feat.shape[2] == mel_len2
return feat.float(), None
if __name__ == '__main__':
torch.backends.cudnn.deterministic = True
torch.backends.cudnn.benchmark = False
from hyperpyyaml import load_hyperpyyaml
with open('./pretrained_models/CosyVoice3-0.5B/cosyvoice3.yaml', 'r') as f:
with open('./pretrained_models/Fun-CosyVoice3-0.5B/cosyvoice3.yaml', 'r') as f:
configs = load_hyperpyyaml(f, overrides={'llm': None, 'hift': None})
model = configs['flow']
device = 'cuda' if torch.cuda.is_available() else 'cpu'
@@ -425,6 +426,7 @@ if __name__ == '__main__':
pred_gt, _ = model.inference(token, token_len, prompt_token, prompt_token_len, prompt_feat, prompt_feat_len, prompt_embedding, streaming=True, finalize=True)
for i in range(0, max_len, chunk_size):
finalize = True if i + chunk_size + context_size >= max_len else False
pred_chunk, _ = model.inference(token[:, :i + chunk_size + context_size], torch.tensor([token[:, :i + chunk_size + context_size].shape[1]]).to(device), prompt_token, prompt_token_len, prompt_feat, prompt_feat_len, prompt_embedding, streaming=True, finalize=finalize)
pred_chunk, _ = model.inference(token[:, :i + chunk_size + context_size], torch.tensor([token[:, :i + chunk_size + context_size].shape[1]]).to(device),
prompt_token, prompt_token_len, prompt_feat, prompt_feat_len, prompt_embedding, streaming=True, finalize=finalize)
pred_chunk = pred_chunk[:, :, i * model.token_mel_ratio:]
print((pred_gt[:, :, i * model.token_mel_ratio: i * model.token_mel_ratio + pred_chunk.shape[2]] - pred_chunk).abs().max().item())
print((pred_gt[:, :, i * model.token_mel_ratio: i * model.token_mel_ratio + pred_chunk.shape[2]] - pred_chunk).abs().max().item())