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export_onnx.py

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+from infer_pack.models_onnx import SynthesizerTrnMs256NSFsid
+import torch
+
+person = "Shiroha/shiroha.pth"
+exported_path = "model.onnx"
+
+
+
+cpt = torch.load(person, map_location="cpu")
+cpt["config"][-3]=cpt["weight"]["emb_g.weight"].shape[0]#n_spk
+print(*cpt["config"])
+net_g = SynthesizerTrnMs256NSFsid(*cpt["config"], is_half=False)
+net_g.load_state_dict(cpt["weight"], strict=False)
+
+test_phone = torch.rand(1, 200, 256)
+test_phone_lengths = torch.tensor([200]).long()
+test_pitch = torch.randint(size=(1 ,200),low=5,high=255)
+test_pitchf = torch.rand(1, 200)
+test_ds = torch.LongTensor([0])
+test_rnd = torch.rand(1, 192, 200)
+input_names = ["phone", "phone_lengths", "pitch", "pitchf", "ds", "rnd"]
+output_names = ["audio", ]
+device="cpu"
+torch.onnx.export(net_g,
+            (
+                test_phone.to(device),
+                test_phone_lengths.to(device),
+                test_pitch.to(device),
+                test_pitchf.to(device),
+                test_ds.to(device),
+                test_rnd.to(device)
+            ),
+            exported_path,
+            dynamic_axes={
+                "phone": [1],
+                "pitch": [1],
+                "pitchf": [1],
+                "rnd": [2],
+            },
+            do_constant_folding=False,
+            opset_version=16,
+            verbose=False,
+            input_names=input_names,
+            output_names=output_names)