✨ | Added app.py script so the model can be used.

AudioUtils.py

@@ -50,3 +50,22 @@ def split_audio(audio_tensor: torch.Tensor, chunk_size: int = 128) -> list[torch
     chunks = list(torch.split(audio_tensor, chunk_size, dim=split_dim))
 
     return chunks
+
+def reconstruct_audio(chunks: list[torch.Tensor]) -> torch.Tensor:
+    if not chunks:
+        return torch.empty(0)
+
+    if len(chunks) == 1 and chunks[0].dim() == 0:
+        return chunks[0]
+
+    concat_dim = -1
+
+    try:
+        reconstructed_tensor = torch.cat(chunks, dim=concat_dim)
+    except RuntimeError as e:
+        raise RuntimeError(
+            f"Failed to concatenate audio chunks. Ensure chunks have compatible shapes "
+            f"for concatenation along dimension {concat_dim}. Original error: {e}"
+        )
+
+    return reconstructed_tensor