Update onnx_export.py

onnx_export.py

@@ -1,21 +1,7 @@
 import torch
-from torchaudio.models.wav2vec2.utils import import_fairseq_model
-from fairseq import checkpoint_utils
 from onnxexport.model_onnx import SynthesizerTrn
 import utils
 
-def get_hubert_model():
-    vec_path = "hubert/checkpoint_best_legacy_500.pt"
-    print("load model(s) from {}".format(vec_path))
-    models, saved_cfg, task = checkpoint_utils.load_model_ensemble_and_task(
-        [vec_path],
-        suffix="",
-    )
-    model = models[0]
-    model.eval()
-    return model
-
-
 def main(NetExport):
     path = "SoVits4.0V2"
     if NetExport:
@@ -27,6 +13,7 @@ def main(NetExport):
         _ = SVCVITS.eval().to(device)
         for i in SVCVITS.parameters():
             i.requires_grad = False
+        
         test_hidden_unit = torch.rand(1, 10, 256) # rand
         test_pitch = torch.rand(1, 10) # rand
         test_mel2ph = torch.LongTensor([0, 1, 2, 3, 4, 5, 6, 7, 8, 9]).unsqueeze(0)
@@ -37,14 +24,6 @@ def main(NetExport):
         test_sid = torch.LongTensor([0])
         input_names = ["c", "f0", "mel2ph", "t_window", "noise", "sid"]
         output_names = ["audio", ]
-        SVCVITS.eval()
-
-        SVCVITS(test_hidden_unit.to(device),
-                              test_pitch.to(device),
-                              test_mel2ph.to(device),
-                              test_uv.to(device),
-                              test_noise.to(device),
-                              test_sid.to(device))
         
         torch.onnx.export(SVCVITS,
                           (