49 lines
1.2 KiB
Python
49 lines
1.2 KiB
Python
import argparse
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import json
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import os
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import pandas as pd
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from tabulate import tabulate
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# Parse command-line arguments
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parser = argparse.ArgumentParser(description="Parse JSONL benchmark and summarize.")
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parser.add_argument("input_file", type=str, help="Path to input JSONL file")
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args = parser.parse_args()
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input_file = args.input_file
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base_name = os.path.splitext(os.path.basename(input_file))[0]
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output_file = f"{base_name}_summary.csv"
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fields = [
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"max_concurrency",
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"input_throughput",
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"output_throughput",
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"mean_ttft_ms",
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"median_ttft_ms",
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"p99_ttft_ms",
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"mean_tpot_ms",
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"median_tpot_ms",
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"p99_tpot_ms",
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]
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# Read JSONL and parse
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results = []
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with open(input_file, "r") as f:
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for line in f:
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data = json.loads(line)
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row = {field: data.get(field, None) for field in fields}
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max_conc = data.get("max_concurrency")
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out_tp = data.get("output_throughput")
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row["per_user_throughput"] = out_tp / max_conc if max_conc else None
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results.append(row)
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# Convert to DataFrame
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df = pd.DataFrame(results)
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# Save to CSV
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df.to_csv(output_file, index=False)
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print(f"\nSaved summary to: {output_file}\n")
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# Print ASCII table
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print(tabulate(df, headers="keys", tablefmt="grid", floatfmt=".3f"))
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