Add files via upload

vencoder/ContentVec256L12_Onnx.py

@@ -0,0 +1,34 @@
+from vencoder.encoder import SpeechEncoder
+import torch
+from fairseq import checkpoint_utils
+
+class ContentVec768L12(SpeechEncoder):
+    def __init__(self,vec_path = "pretrain/checkpoint_best_legacy_500.pt",device=None):
+        print("load model(s) from {}".format(vec_path))
+        self.hidden_dim = 768
+        models, saved_cfg, task = checkpoint_utils.load_model_ensemble_and_task(
+          [vec_path],
+          suffix="",
+        )
+        if device is None:
+            self.dev = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+        else:
+            self.dev = torch.device(device)
+        self.model = models[0].to(self.dev)
+        self.model.eval()
+
+    def encoder(self, wav):
+        feats = wav
+        if feats.dim() == 2:  # double channels
+          feats = feats.mean(-1)
+        assert feats.dim() == 1, feats.dim()
+        feats = feats.view(1, -1)
+        padding_mask = torch.BoolTensor(feats.shape).fill_(False)
+        inputs = {
+          "source": feats.to(wav.device),
+          "padding_mask": padding_mask.to(wav.device),
+          "output_layer": 12,  # layer 12
+        }
+        with torch.no_grad():
+          logits = self.model.extract_features(**inputs)
+        return logits[0].transpose(1, 2)