chore: import upstream snapshot with attribution

examples/flows/evaluation/eval-accuracy-maths-to-code/aggregate.py

@@ -0,0 +1,37 @@
+from typing import List
+from promptflow.core import tool
+from promptflow.core import log_metric
+
+
+@tool
+def accuracy_aggregate(processed_results: List[int]):
+
+    num_exception = 0
+    num_correct = 0
+
+    for i in range(len(processed_results)):
+        if processed_results[i] == -1:
+            num_exception += 1
+        elif processed_results[i] == 1:
+            num_correct += 1
+
+    num_total = len(processed_results)
+    accuracy = round(1.0 * num_correct / num_total, 2)
+    error_rate = round(1.0 * num_exception / num_total, 2)
+
+    log_metric(key="accuracy", value=accuracy)
+    log_metric(key="error_rate", value=error_rate)
+
+    return {
+        "num_total": num_total,
+        "num_correct": num_correct,
+        "num_exception": num_exception,
+        "accuracy": accuracy,
+        "error_rate": error_rate
+    }
+
+
+if __name__ == "__main__":
+    numbers = [1, 1, 1, 1, 0, -1, -1]
+    accuracy = accuracy_aggregate(numbers)
+    print("The accuracy is", accuracy)