Merge pull request #5 from ml-energy/add_compute_script

extract.py

@@ -0,0 +1,69 @@
+import re
+import json
+import numpy as np
+import statistics
+import os
+import csv
+
+model = []
+throughput = []
+response_length = []
+latency = []
+energy = []
+
+temp_throughput = []
+temp_response_length = []
+temp_latency = []
+temp_energy = []
+
+model_name = os.listdir("data/chat")
+
+match_name = False
+
+for models in model_name:
+    with open("data/chat/"+models+"/benchmark.json", 'r') as file:
+        json_data = json.load(file)
+
+    for obj in json_data:
+        if not match_name:
+            name = str(obj["model"])
+            model.append(name.replace('--','/'))
+            match_name = True
+        temp_throughput.append(float(obj["throughput"]))
+        temp_response_length.append(float(obj["response_length"]))
+        temp_latency.append(float(obj["latency"]))
+        temp_energy.append(float(obj["energy"]))
+        
+    match_name = False
+
+    throughput.append(temp_throughput.copy())
+    response_length.append(temp_response_length.copy())
+    latency.append(temp_latency.copy())
+    energy.append(temp_energy.copy())
+
+    temp_throughput.clear()
+    temp_response_length.clear()
+    temp_latency.clear()
+    temp_energy.clear()
+
+
+avg_throughput = [statistics.mean(row) for row in throughput]
+avg_response_length = [statistics.mean(row) for row in response_length]
+avg_latency = [statistics.mean(row) for row in latency]
+avg_energy = [statistics.mean(row) for row in energy]
+
+for i in range(len(model)):
+    print(model[i])
+    print(len(throughput[i]))
+    print(len(response_length[i]))
+    print(len(latency[i]))
+    print(len(energy[i]))
+
+csv_file = "leaderboard.csv"
+
+with open(csv_file, "w", newline="") as file:
+    writer = csv.writer(file)
+    writer.writerow(["model","throughput","response_length","latency","energy"])  
+    for i in range(len(model)):
+        writer.writerow([model[i], avg_throughput[i], avg_response_length[i], avg_latency[i], avg_energy[i]])
+