input Jacqueline's code

tasks/text.py

@@ -70,19 +70,16 @@ async def evaluate_text(request: TextEvaluationRequest):
     # 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.
     #--------------------------------------------------------------------------------------------   
 
-    try:
-        # Tokenize the input texts
-        encoded_input = tokenizer(test_dataset["quote"], truncation=True, padding=True, return_tensors="tf")
-        
-        # Make predictions
-        outputs = model(encoded_input["input_ids"], attention_mask=encoded_input["attention_mask"], training=False)
-        predictions = tf.argmax(outputs.logits, axis=1).numpy()
+    #make predictions
+    predictions = []
+    
+    for i in range(len(test_dataset["quote"])):
+      encoded_input = tokenizer(test_dataset["quote"][i], truncation=True, padding=True, return_tensors="tf")
+      outputs = model(encoded_input["input_ids"], attention_mask=encoded_input["attention_mask"], training=False)
+      predictions.append(tf.argmax(outputs.logits, axis=1))
         
-        # Get true labels
-        true_labels = test_dataset["label"]
-    except Exception as e:
-        print(f"An error occurred during prediction: {str(e)}")
-        raise
+    # Get true labels
+    true_labels = test_dataset["label"]
 
     #--------------------------------------------------------------------------------------------
     # YOUR MODEL INFERENCE STOPS HERE