mirror of
https://github.com/w-okada/voice-changer.git
synced 2025-01-24 05:55:01 +03:00
79 lines
2.6 KiB
Python
79 lines
2.6 KiB
Python
import torch
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from torch import device
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import onnxruntime
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from const import EnumInferenceTypes
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from voice_changer.RVC.inferencer.Inferencer import Inferencer
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import numpy as np
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providers = ["CPUExecutionProvider"]
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class OnnxRVCInference(Inferencer):
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def loadModel(self, file: str, dev: device, isHalf: bool = True):
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super().setProps(EnumInferenceTypes.onnxRVC, file, dev, isHalf)
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# ort_options = onnxruntime.SessionOptions()
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# ort_options.intra_op_num_threads = 8
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onnx_session = onnxruntime.InferenceSession(
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self.onnx_model, providers=providers
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)
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# check half-precision
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first_input_type = self.onnx_session.get_inputs()[0].type
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if first_input_type == "tensor(float)":
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self.isHalf = False
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else:
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self.isHalf = True
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self.model = onnx_session
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return self
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def infer(
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self,
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feats: torch.Tensor,
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pitch_length: torch.Tensor,
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pitch: torch.Tensor | None,
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pitchf: torch.Tensor | None,
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sid: torch.Tensor,
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) -> torch.Tensor:
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if pitch is None or pitchf is None:
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raise RuntimeError("[Voice Changer] Pitch or Pitchf is not found.")
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if self.isHalf:
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audio1 = self.model.run(
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["audio"],
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{
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"feats": feats.cpu().numpy().astype(np.float16),
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"p_len": pitch_length.cpu().numpy().astype(np.int64),
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"pitch": pitch.cpu().numpy().astype(np.int64),
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"pitchf": pitchf.cpu().numpy().astype(np.float32),
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"sid": sid.cpu().numpy().astype(np.int64),
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},
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)
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else:
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audio1 = self.model.run(
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["audio"],
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{
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"feats": feats.cpu().numpy().astype(np.float32),
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"p_len": pitch_length.cpu().numpy().astype(np.int64),
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"pitch": pitch.cpu().numpy().astype(np.int64),
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"pitchf": pitchf.cpu().numpy().astype(np.float32),
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"sid": sid.cpu().numpy().astype(np.int64),
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},
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)
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return torch.tensor(np.array(audio1))
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def setHalf(self, isHalf: bool):
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raise RuntimeError("half-precision is not changable.", self.isHalf)
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def setDevice(self, dev: device):
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self.dev = dev
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if self.model is not None:
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self.model = self.model.to(self.dev)
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def to(self, dev: torch.device):
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if self.model is not None:
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self.model = self.model.to(dev)
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return self
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