Added thread lock to prevent overlapping executions

src/app.py

@@ -53,27 +53,30 @@ def translate_audio(
     :yield: the tuple containing the sampling rate and the audio array
     :rtype: tuple[int, np.ndarray]
     """
-    # with translate_lock:
-    orig_freq, np_array = audio
-    waveform = torch.from_numpy(np_array)
-    waveform = waveform.to(torch.float32)
-    waveform = waveform / 32768.0  # normalize int16 to [-1, 1]
-
-    audio = torchaudio.functional.resample(
-        waveform, orig_freq=orig_freq, new_freq=default_sampling_rate
-    )  # must be a 16 kHz waveform array
-
-    audio_inputs = processor(
-        audios=audio,
-        return_tensors="pt",
-        sampling_rate=default_sampling_rate,
-    )
-
-    audio_array_from_audio = (
-        model.generate(**audio_inputs, tgt_lang=tgt_language)[0].cpu().numpy().squeeze()
-    )
-
-    yield (default_sampling_rate, audio_array_from_audio)
+    with translate_lock:
+        orig_freq, np_array = audio
+        waveform = torch.from_numpy(np_array)
+        waveform = waveform.to(torch.float32)
+        waveform = waveform / 32768.0  # normalize int16 to [-1, 1]
+
+        audio = torchaudio.functional.resample(
+            waveform, orig_freq=orig_freq, new_freq=default_sampling_rate
+        )  # must be a 16 kHz waveform array
+
+        audio_inputs = processor(
+            audios=audio,
+            return_tensors="pt",
+            sampling_rate=default_sampling_rate,
+        )
+
+        audio_array_from_audio = (
+            model.generate(**audio_inputs, tgt_lang=tgt_language)[0]
+            .cpu()
+            .numpy()
+            .squeeze()
+        )
+
+        yield (default_sampling_rate, audio_array_from_audio)
 
 
 # Supported target languages for speech