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MyGO_VIts-bert / onnx_infer.py

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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)