Complete Refactor

Backend/src/models/audio_model.py

@@ -0,0 +1,28 @@
+from dataclasses import dataclass
+import torch
+
+@dataclass
+class AudioModel:
+    model: torch.nn.Module
+    sample_rate: int
+
+    def __post_init__(self):
+        self.model.eval()
+
+    def process_audio(self, audio_tensor: torch.Tensor) -> torch.Tensor:
+        with torch.no_grad():
+            processed_audio = self.model(audio_tensor)
+        return processed_audio
+
+    def resample_audio(self, audio_tensor: torch.Tensor, target_sample_rate: int) -> torch.Tensor:
+        if self.sample_rate != target_sample_rate:
+            resampled_audio = torchaudio.functional.resample(audio_tensor, orig_freq=self.sample_rate, new_freq=target_sample_rate)
+            return resampled_audio
+        return audio_tensor
+
+    def save_model(self, path: str):
+        torch.save(self.model.state_dict(), path)
+
+    def load_model(self, path: str):
+        self.model.load_state_dict(torch.load(path))
+        self.model.eval()