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51 lines
1.6 KiB
Python
51 lines
1.6 KiB
Python
from utils import get_hparams_from_file, load_checkpoint
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import json
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def export_onnx(export_path, model_path, config_path):
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hps = get_hparams_from_file(config_path)
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version = hps.version[0:3]
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if version == "2.0":
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from .V200 import SynthesizerTrn, symbols
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elif version == "2.1":
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from .V210 import SynthesizerTrn, symbols
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elif version == "2.2":
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from .V220 import SynthesizerTrn, symbols
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net_g = SynthesizerTrn(
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len(symbols),
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hps.data.filter_length // 2 + 1,
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hps.train.segment_size // hps.data.hop_length,
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n_speakers=hps.data.n_speakers,
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**hps.model,
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)
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_ = net_g.eval()
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_ = load_checkpoint(model_path, net_g, None, skip_optimizer=True)
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net_g.cpu()
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net_g.export_onnx(export_path)
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spklist = []
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for key in hps.data.spk2id.keys():
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spklist.append(key)
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MoeVSConf = {
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"Folder": f"{export_path}",
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"Name": f"{export_path}",
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"Type": "BertVits",
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"Symbol": symbols,
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"Cleaner": "",
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"Rate": hps.data.sampling_rate,
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"CharaMix": True,
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"Characters": spklist,
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"LanguageMap": {"ZH": [0, 0], "JP": [1, 6], "EN": [2, 8]},
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"Dict": "BasicDict",
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"BertPath": [
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"chinese-roberta-wwm-ext-large",
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"deberta-v2-large-japanese",
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"bert-base-japanese-v3",
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],
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"Clap": "clap-htsat-fused",
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}
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with open(f"onnx/{export_path}.json", "w") as MoeVsConfFile:
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json.dump(MoeVSConf, MoeVsConfFile, indent=4)
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