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"""Run multiple trials of iterative refinement to get statistics.""" |
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import json |
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import os |
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import shutil |
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import sys |
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from pathlib import Path |
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os.chdir(Path(__file__).parent) |
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from iterative_agent import run_iterative_refinement, load_config |
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def run_trials(num_trials: int = 10, max_iterations: int = 100): |
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"""Run multiple trials and collect statistics.""" |
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config = load_config("config.yaml") |
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results = [] |
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solutions_found = [] |
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for trial in range(num_trials): |
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print(f"\n{'#'*60}") |
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print(f"# TRIAL {trial + 1}/{num_trials}") |
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print('#'*60) |
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output_dir = f"iterative_output_trial_{trial}" |
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if os.path.exists(output_dir): |
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shutil.rmtree(output_dir) |
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result = run_iterative_refinement( |
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initial_program="initial_program.py", |
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evaluator_path="evaluator.py", |
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config=config, |
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max_iterations=max_iterations, |
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output_dir=output_dir, |
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) |
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results.append({ |
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"trial": trial, |
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"solution_found_at": result["solution_found_at"], |
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"final_best_score": result["final_best_score"], |
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"total_iterations": result["total_iterations"], |
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}) |
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if result["solution_found_at"] is not None: |
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solutions_found.append(result["solution_found_at"]) |
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success_rate = len(solutions_found) / num_trials |
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avg_iterations = sum(solutions_found) / len(solutions_found) if solutions_found else float('inf') |
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min_iterations = min(solutions_found) if solutions_found else None |
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max_iterations_found = max(solutions_found) if solutions_found else None |
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print(f"\n{'='*60}") |
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print("ITERATIVE REFINEMENT TRIAL RESULTS") |
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print('='*60) |
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print(f"Trials: {num_trials}") |
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print(f"Max iterations per trial: {max_iterations}") |
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print(f"Success rate: {success_rate:.1%} ({len(solutions_found)}/{num_trials})") |
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if solutions_found: |
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print(f"Avg iterations to solution: {avg_iterations:.1f}") |
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print(f"Min iterations: {min_iterations}") |
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print(f"Max iterations: {max_iterations_found}") |
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print('='*60) |
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summary = { |
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"config": { |
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"num_trials": num_trials, |
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"max_iterations": max_iterations, |
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}, |
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"summary": { |
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"success_rate": success_rate, |
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"avg_iterations_to_solution": avg_iterations if solutions_found else None, |
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"min_iterations": min_iterations, |
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"max_iterations": max_iterations_found, |
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"solutions_found": len(solutions_found), |
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}, |
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"trials": results, |
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} |
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with open("iterative_trials_results.json", "w") as f: |
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json.dump(summary, f, indent=2) |
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print(f"\nResults saved to: iterative_trials_results.json") |
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return summary |
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if __name__ == "__main__": |
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import argparse |
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parser = argparse.ArgumentParser() |
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parser.add_argument("--trials", type=int, default=10, help="Number of trials") |
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parser.add_argument("--iterations", type=int, default=100, help="Max iterations per trial") |
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args = parser.parse_args() |
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run_trials(num_trials=args.trials, max_iterations=args.iterations) |
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