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Fix: 由于 export_torch_script_v3 的改动，v2 现在需要传入 top_k

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csh 2025-03-23 14:20:50 +08:00
parent b12ac35b04
commit 1ceab938bb
1 changed files with 20 additions and 4 deletions
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24
GPT_SoVITS/export_torch_script.py
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@ -654,6 +654,8 @@ def export(gpt_path, vits_path, ref_audio_path, ref_text, output_path, export_be
torch._dynamo.mark_dynamic(ref_bert, 0)
torch._dynamo.mark_dynamic(text_bert, 0)
top_k = torch.LongTensor([5]).to(device)
with torch.no_grad():
gpt_sovits_export = torch.jit.trace(
gpt_sovits,
@ -663,7 +665,8 @@ def export(gpt_path, vits_path, ref_audio_path, ref_text, output_path, export_be
ref_seq,
text_seq,
ref_bert,
text_bert))
text_bert,
top_k))
gpt_sovits_path = os.path.join(output_path, "gpt_sovits_model.pt")
gpt_sovits_export.save(gpt_sovits_path)
@ -685,15 +688,26 @@ class GPT_SoVITS(nn.Module):
self.t2s = t2s
self.vits = vits
def forward(self, ssl_content:torch.Tensor, ref_audio_sr:torch.Tensor, ref_seq:Tensor, text_seq:Tensor, ref_bert:Tensor, text_bert:Tensor, speed=1.0):
def forward(
self,
ssl_content: torch.Tensor,
ref_audio_sr: torch.Tensor,
ref_seq: Tensor,
text_seq: Tensor,
ref_bert: Tensor,
text_bert: Tensor,
top_k: LongTensor,
speed=1.0,
):
codes = self.vits.vq_model.extract_latent(ssl_content)
prompt_semantic = codes[0, 0]
prompts = prompt_semantic.unsqueeze(0)
pred_semantic = self.t2s(prompts, ref_seq, text_seq, ref_bert, text_bert)
pred_semantic = self.t2s(prompts, ref_seq, text_seq, ref_bert, text_bert, top_k)
audio = self.vits(text_seq, pred_semantic, ref_audio_sr, speed)
return audio
def test():
parser = argparse.ArgumentParser(description="GPT-SoVITS Command Line Tool")
parser.add_argument('--gpt_model', required=True, help="Path to the GPT model file")
@ -785,8 +799,10 @@ def test():
print('text_bert:',text_bert.shape)
text_bert=text_bert.to('cuda')
top_k = torch.LongTensor([5]).to('cuda')
with torch.no_grad():
audio = gpt_sovits(ssl_content, ref_audio_sr, ref_seq, text_seq, ref_bert, test_bert)
audio = gpt_sovits(ssl_content, ref_audio_sr, ref_seq, text_seq, ref_bert, test_bert, top_k)
print('start write wav')
soundfile.write("out.wav", audio.detach().cpu().numpy(), 32000)