dc3462d4f4fe48bc075b48815d026dc4a8acceb7,nussl/separation/clustering/clustering_algorithms.py,DeepClustering,extract_features,#DeepClustering#,190

Before Change

        input_data = self._preprocess()
        with torch.no_grad():
            output = self.model(input_data)
            output = {k: output[k].cpu() for k in output}
            if "embedding" not in output:
                raise ValueError("This model is not a deep clustering model!")

            embedding = output["embedding"]

After Change

            embedding = embedding.squeeze(-2)
            embedding = embedding.permute(2, 1, 0, 3)
            embedding = embedding.reshape(-1, embedding_size)
            embedding = embedding.data.cpu().numpy()
        return embedding

    def make_audio_signals(self):
        signals = super().make_audio_signals()

Instances