Upload custom_interface.py

custom_interface.py

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+from speechbrain.pretrained import EncoderClassifier
+
+class CustomEncoderWav2vec2Classifier(EncoderClassifier):
+    def compute_forward(self, batch, stage):
+        wavs, wav_lens = batch.sig
+        feats = self.mods.compute_features(wavs)
+        if self.mods.normalize:
+            feats = self.mods.normalize(feats, wav_lens)
+        x = self.mods.encoder(feats)
+        outputs = self.mods.classifier(x)
+        return outputs
+
+    def classify_file(self, path):
+        signal = self.load_audio(path)
+        batch = self.make_batch(signal)
+        probs = self.forward(batch)
+        score, index = probs.max(1)
+        label = self.hparams.label_encoder.decode(index)
+        return probs, score.item(), index.item(), label