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import argparse | |
import pandas as pd | |
from openhands.core.logger import openhands_logger as logger | |
def verify_instance_costs(row: pd.Series) -> float: | |
""" | |
Verifies that the accumulated_cost matches the sum of individual costs in metrics. | |
Also checks for duplicate consecutive costs which might indicate buggy counting. | |
If the consecutive costs are identical, the file is affected by this bug: | |
https://github.com/All-Hands-AI/OpenHands/issues/5383 | |
Args: | |
row: DataFrame row containing instance data with metrics | |
Returns: | |
float: The verified total cost for this instance (corrected if needed) | |
""" | |
try: | |
metrics = row.get('metrics') | |
if not metrics: | |
logger.warning(f'Instance {row["instance_id"]}: No metrics found') | |
return 0.0 | |
accumulated = metrics.get('accumulated_cost') | |
costs = metrics.get('costs', []) | |
if accumulated is None: | |
logger.warning( | |
f'Instance {row["instance_id"]}: No accumulated_cost in metrics' | |
) | |
return 0.0 | |
# Check for duplicate consecutive costs and systematic even-odd pairs | |
has_duplicate = False | |
all_pairs_match = True | |
# Check each even-odd pair (0-1, 2-3, etc.) | |
for i in range(0, len(costs) - 1, 2): | |
if abs(costs[i]['cost'] - costs[i + 1]['cost']) < 1e-6: | |
has_duplicate = True | |
logger.debug( | |
f'Instance {row["instance_id"]}: Possible buggy double-counting detected! ' | |
f'Steps {i} and {i + 1} have identical costs: {costs[i]["cost"]:.2f}' | |
) | |
else: | |
all_pairs_match = False | |
break | |
# Calculate total cost, accounting for buggy double counting if detected | |
if len(costs) >= 2 and has_duplicate and all_pairs_match: | |
paired_steps_cost = sum( | |
cost_entry['cost'] | |
for cost_entry in costs[: -1 if len(costs) % 2 else None] | |
) | |
real_paired_cost = paired_steps_cost / 2 | |
unpaired_cost = costs[-1]['cost'] if len(costs) % 2 else 0 | |
total_cost = real_paired_cost + unpaired_cost | |
else: | |
total_cost = sum(cost_entry['cost'] for cost_entry in costs) | |
if not abs(total_cost - accumulated) < 1e-6: | |
logger.warning( | |
f'Instance {row["instance_id"]}: Cost mismatch: ' | |
f'accumulated: {accumulated:.2f}, sum of costs: {total_cost:.2f}, ' | |
) | |
return total_cost | |
except Exception as e: | |
logger.error( | |
f'Error verifying costs for instance {row.get("instance_id", "UNKNOWN")}: {e}' | |
) | |
return 0.0 | |
def main(): | |
parser = argparse.ArgumentParser( | |
description='Verify costs in SWE-bench output file' | |
) | |
parser.add_argument( | |
'input_filepath', type=str, help='Path to the output.jsonl file' | |
) | |
args = parser.parse_args() | |
try: | |
# Load and verify the JSONL file | |
df = pd.read_json(args.input_filepath, lines=True) | |
logger.info(f'Loaded {len(df)} instances from {args.input_filepath}') | |
# Verify costs for each instance and sum up total | |
total_cost = df.apply(verify_instance_costs, axis=1).sum() | |
logger.info(f'Total verified cost across all instances: ${total_cost:.2f}') | |
except Exception as e: | |
logger.error(f'Failed to process file: {e}') | |
raise | |
if __name__ == '__main__': | |
main() | |