Update tasks/audio.py

tasks/audio.py

@@ -50,6 +50,44 @@ async def evaluate_audio(request: AudioEvaluationRequest):
     
     #--------------------------------------------------------------------------------------------
     # YOUR MODEL INFERENCE CODE HERE
+    load_pretrained(dannywillowliu/frugal_ai_space)
+    losses = []
+
+    total = 0
+    
+    correct = 0
+    
+    with torch.no_grad():
+    
+        for i in range(1000):
+    
+            inputs = []
+    
+            outputs = []
+    
+            for j in range(4):
+    
+                data = next(generator)
+    
+                x = data['audio']['array']
+    
+                y = data['label']
+    
+                inputs.append(x)
+    
+                outputs.append(y)
+    
+            input_values = processor(inputs, return_tensors="pt", padding="longest", sampling_rate=16000).input_values
+    
+            logits = model(input_values.cuda()).logits
+    
+            loss = torch.nn.functional.cross_entropy(logits, torch.tensor(outputs).cuda())
+    
+            
+    
+            probs = torch.nn.functional.softmax(logits)
+    
+            chosen = torch.argmax(probs,dim=1)
     # Update the code below to replace the random baseline by your model inference within the inference pass where the energy consumption and emissions are tracked.
     #--------------------------------------------------------------------------------------------