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| from onnx_modules.V220_OnnxInference import OnnxInferenceSession | |
| import numpy as np | |
| Session = OnnxInferenceSession( | |
| { | |
| "enc" : "onnx/BertVits2.2PT/BertVits2.2PT_enc_p.onnx", | |
| "emb_g" : "onnx/BertVits2.2PT/BertVits2.2PT_emb.onnx", | |
| "dp" : "onnx/BertVits2.2PT/BertVits2.2PT_dp.onnx", | |
| "sdp" : "onnx/BertVits2.2PT/BertVits2.2PT_sdp.onnx", | |
| "flow" : "onnx/BertVits2.2PT/BertVits2.2PT_flow.onnx", | |
| "dec" : "onnx/BertVits2.2PT/BertVits2.2PT_dec.onnx" | |
| }, | |
| Providers = ["CPUExecutionProvider"] | |
| ) | |
| #这里的输入和原版是一样的，只需要在原版预处理结果出来之后加上.numpy()即可 | |
| x = np.array( | |
| [ | |
| 0, | |
| 97, | |
| 0, | |
| 8, | |
| 0, | |
| 78, | |
| 0, | |
| 8, | |
| 0, | |
| 76, | |
| 0, | |
| 37, | |
| 0, | |
| 40, | |
| 0, | |
| 97, | |
| 0, | |
| 8, | |
| 0, | |
| 23, | |
| 0, | |
| 8, | |
| 0, | |
| 74, | |
| 0, | |
| 26, | |
| 0, | |
| 104, | |
| 0, | |
| ] | |
| ) | |
| tone = np.zeros_like(x) | |
| language = np.zeros_like(x) | |
| sid = np.array([0]) | |
| bert = np.random.randn(x.shape[0], 1024) | |
| ja_bert = np.random.randn(x.shape[0], 1024) | |
| en_bert = np.random.randn(x.shape[0], 1024) | |
| emo = np.random.randn(512, 1) | |
| audio = Session( | |
| x, | |
| tone, | |
| language, | |
| bert, | |
| ja_bert, | |
| en_bert, | |
| emo, | |
| sid | |
| ) | |
| print(audio) | |