Update tasks/audio.py

tasks/audio.py

@@ -84,7 +84,7 @@ async def evaluate_audio(request: AudioEvaluationRequest):
         batch_size=128,
         shuffle=False,
         pin_memory=True,
-        num_workers=4 
+        num_workers=2
     )
 
     scripted_model = torch.jit.load("./optimized_qat_blazeface_model.pt", map_location=torch.device('cpu'))
@@ -101,7 +101,8 @@ async def evaluate_audio(request: AudioEvaluationRequest):
     predictions = []
     with torch.no_grad():
         #with autocast():
-        with torch.amp.autocast(device_type='cpu'):
+        #with torch.amp.autocast(device_type='cpu'):
+        with torch.autocast(device_type='cpu'):
             for data, target in test_loader:
                 outputs = scripted_model(data)
                 _, predicted = torch.max(outputs, 1)