train mel head even when not
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@ -304,7 +304,7 @@ class DiffusionTtsFlat(nn.Module):
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assert precomputed_aligned_embeddings is not None or (aligned_conditioning is not None and conditioning_input is not None)
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assert not (return_code_pred and precomputed_aligned_embeddings is not None) # These two are mutually exclusive.
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unused_params = []
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unused_params = [self.mel_head.parameters()]
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if conditioning_free:
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code_emb = self.unconditioned_embedding.repeat(x.shape[0], 1, x.shape[-1])
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unused_params.extend(list(self.code_converter.parameters()) + list(self.code_embedding.parameters()))
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