wandb/debug.log

2026-04-16 12:27:27,971 INFO    MainThread:2561065 [wandb_setup.py:_flush():81] Current SDK version is 0.24.1
2026-04-16 12:27:27,972 INFO    MainThread:2561065 [wandb_setup.py:_flush():81] Configure stats pid to 2561065
2026-04-16 12:27:27,972 INFO    MainThread:2561065 [wandb_setup.py:_flush():81] Loading settings from environment variables
2026-04-16 12:27:27,972 INFO    MainThread:2561065 [wandb_init.py:setup_run_log_directory():717] Logging user logs to /home/tengxiao/pj/ShinkaEvolve/wandb/run-20260416_122727-p255/logs/debug.log
2026-04-16 12:27:27,972 INFO    MainThread:2561065 [wandb_init.py:setup_run_log_directory():718] Logging internal logs to /home/tengxiao/pj/ShinkaEvolve/wandb/run-20260416_122727-p255/logs/debug-internal.log
2026-04-16 12:27:27,972 INFO    MainThread:2561065 [wandb_init.py:init():844] calling init triggers
2026-04-16 12:27:27,972 INFO    MainThread:2561065 [wandb_init.py:init():849] wandb.init called with sweep_config: {}
config: {'evolution_config': {'task_sys_msg': 'You are an expert competitive programmer. Your goal is to write C++ code that maximizes the score on the given problem. The scoring is continuous (0-100) based on solution quality, not just correctness. Optimize for both correctness and performance. Focus on algorithmic improvements, not micro-optimizations.\n\n--- Problem Statement ---\nProblem: Magnets\n\nTime limit: 1 second\n\nMemory limit: 256 MB\n\nThis is an interactive problem.\n\nKochiya Sanae is playing with magnets.\nRealizing that some of those magnets are demagnetized, she is curious to find them out.\nThere are n magnets, which can be of the following 3 types:\n- N\n- S\n- - (these magnets are demagnetized)\n\nNote that you don\'t know the types of these magnets beforehand.\nYou have a machine which can measure the force between the magnets.\nYou can put some magnets to the left part of the machine and some to the right part of the machine, and launch the machine.\nObviously, you can put one magnet to at most one side (you don\'t have to put all magnets).\nYou can put the same magnet in different queries.\n\nThen the machine will tell the force these magnets produce.\nFormally, let n_1, s_1 be the number of N and S magnets correspondently on the left and n_2, s_2 on the right.\nThen the force between them would be n_1 * n_2 + s_1 * s_2 - n_1 * s_2 - n_2 * s_1.\nPlease note that the force is a signed value.\n\nHowever, when the absolute value of the force is strictly larger than 1, the machine will crash into pieces.\nYou need to find all magnets of type - (all demagnetized ones), without breaking the machine.\nNote that the interactor is not adaptive. The types of the magnets are fixed before the start of the interaction and do not change with queries.\nIt is guaranteed that there are at least 2 magnets whose type is not -, and at least 1 magnet of type -.\n\nInput\n\nThe first line contains a single integer t (1 <= t <= 100) -- the number of test cases.\n\nInteraction Protocol\n\nFor each test case you should start by reading an integer n (3 <= n <= 2000) -- the number of the magnets.\nIt is guaranteed that the total sum of all n over all test cases doesn\'t exceed 2000.\n\nAfter that you can put some magnets into the machine and make a query.\nYou have to print each query in three lines:\n1. In the first line print "? l r" (without quotes) where l and r (1 <= l, r < n; l + r <= n) respectively denote the number of the magnets you put to left and right.\n2. In the second line print l integers a_1, ..., a_l (1 <= a_i <= n, a_i != a_j if i != j) -- the indices of the magnets you put to left.\n3. In the third line print r integers b_1, ..., b_r (1 <= b_i <= n, b_i != b_j if i != j) -- the indices of the magnets you put to right.\nThe same magnet can\'t be put to both sides in the same query.\nFormally, you should guarantee that a_i != b_j for any i and j. However, you may leave some magnets unused.\nAfter printing a query do not forget to output end of line and flush the output.\nOtherwise, you will get Idleness limit exceeded. To do this, use:\n- fflush(stdout) or cout.flush() in C++;\n- System.out.flush() in Java;\n- flush(output) in Pascal;\n- stdout.flush() in Python;\n- see documentation for other languages.\nAfter this, you should read an integer F -- the force these magnets produce.\nNote that if your query is invalid (either the query limit exceeds, the machine crashes or the arguments are invalid), the interactor will terminate immediately.\nIn this case terminate your program to receive verdict Wrong Answer instead of arbitrary verdicts.\nIf you are confident about your answer, use the following format to report it:\n"! k A", where k is the number of magnets you found, and A is an array consisting of k different integers from 1 to n denoting the indices of the magnets of type - that you found.\nYou may print elements of A in arbitrary order.\n\nAfter that, if this is the last test case, you have to terminate your program;\notherwise you should immediately continue to deal with the next test case.\n\nScoring\n\nYour score is calculated independently for each test case and then averaged across all test cases. In each test case, the fewer queries you made, the higher score you have.\n\nExample Input:\n1\n4\n0\n1\n0\n0\n\nExample Output:\n? 1 2\n3\n4 2\n? 1 2\n1\n2 3\n? 1 1\n1\n4\n! 2 3 4', 'patch_types': ['diff', 'full', 'cross'], 'patch_type_probs': [0.6, 0.3, 0.1], 'num_generations': 50, 'max_parallel_jobs': 1, 'max_patch_resamples': 3, 'max_patch_attempts': 3, 'job_type': 'local', 'language': 'cpp', 'llm_models': ['native-gemini-3-flash-preview'], 'llm_dynamic_selection': 'ucb1', 'llm_dynamic_selection_kwargs': {'exploration_coef': 1.0}, 'llm_kwargs': {'temperatures': [0.0, 0.5, 1.0], 'max_tokens': 65536, 'reasoning_efforts': ['high']}, 'meta_rec_interval': 10, 'meta_llm_models': ['native-gemini-3-flash-preview'], 'meta_llm_kwargs': {'temperatures': [0.0], 'max_tokens': 32768}, 'meta_max_recommendations': 5, 'embedding_model': 'text-embedding-3-small', 'init_program_path': 'results/frontier_cs_algorithmic/agent_v4_candidate_g5_20260416_081236/p255/initial.cpp', 'results_dir': 'results/frontier_cs_algorithmic/agent_v4_candidate_g5_20260416_081236/p255', 'max_novelty_attempts': 3, 'code_embed_sim_threshold': 0.995, 'novelty_llm_models': ['native-gemini-3-flash-preview'], 'novelty_llm_kwargs': {'temperatures': [0.0], 'max_tokens': 32768}, 'use_text_feedback': True, 'eval_service_url': 'http://localhost:8763', 'use_eval_service': True, 'evaluator_module': 'tasks.frontier_cs_entry.evaluate_algorithmic', 'evaluator_function': 'main', 'evaluator_kwargs': {'problem_id': '255', 'judge_url': 'http://localhost:8081', 'frontier_cs_dir': '/home/tengxiao/pj/ShinkaEvolve/tasks/Frontier-CS'}, 'eval_service_trigger_mode': 'periodic', 'eval_service_trigger_interval': 5, 'enable_wandb': True, 'wandb_project': 'frontier-cs', 'wandb_entity': 'tengxiao', 'wandb_run_name': 'fcs_p255_frontier_cs_agentic_p255_g50_20260416_122727', 'wandb_tags': ['frontier_cs', 'agent', 'forked_g5', 'problem_255'], 'trajectory_log': True, 'trajectory_log_dir': 'llm_trajectories', 'edit_backend': 'single_shot_patch', 'openhands_model': None, 'openhands_max_iterations_per_run': 120, 'openhands_max_message_chars': 120000, 'openhands_log_completions': False, 'openhands_log_completions_dir': None, 'openhands_system_prompt_path': None, 'openhands_system_prompt_suffix_path': 'shinka/prompts/openhands_mutation_system_prompt.j2', 'openhands_ev2_prompt_path': 'eval_agent/ev2_prompt.j2', 'persistent_agents_enabled': False, 'persistent_context_refresh_interval': 10, 'persistent_context_max_recent_attempts': 12, 'persistent_context_max_recent_insights': 8, 'persistent_invalid_burst_threshold': 3, 'recent_attempts_k': 10, 'persistent_invalid_burst_window': 5}, 'database_config': {'db_path': 'evolution_db.sqlite', 'num_islands': 2, 'archive_size': 40, 'elite_selection_ratio': 0.3, 'num_archive_inspirations': 4, 'num_top_k_inspirations': 2, 'migration_interval': 10, 'migration_rate': 0.1, 'island_elitism': True, 'enforce_island_separation': True, 'parent_selection_strategy': 'weighted', 'exploitation_alpha': 1.0, 'exploitation_ratio': 0.2, 'parent_selection_lambda': 10.0, 'num_beams': 5, 'embedding_model': 'text-embedding-3-small'}, 'job_config': {'eval_program_path': 'tasks/frontier_cs_entry/evaluate_algorithmic.py', 'extra_cmd_args': {'problem-id': '255', 'judge-url': 'http://localhost:8081'}, 'time': None, 'conda_env': None}, 'results_dir': 'results/frontier_cs_algorithmic/agent_v4_candidate_g5_20260416_081236/p255', 'resuming_run': True, '_wandb': {}}
2026-04-16 12:27:27,972 INFO    MainThread:2561065 [wandb_init.py:init():892] starting backend
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2026-04-16 15:48:26,247 INFO    MainThread:2561065 [wandb_run.py:_finish():2295] finishing run tengxiao/frontier-cs/p255
2026-04-16 15:48:26,248 INFO    MainThread:2561065 [wandb_run.py:_atexit_cleanup():2494] got exitcode: 0
2026-04-16 15:48:26,249 INFO    MainThread:2561065 [wandb_run.py:_restore():2476] restore
2026-04-16 15:48:26,249 INFO    MainThread:2561065 [wandb_run.py:_restore():2482] restore done
2026-04-16 15:48:29,199 INFO    MainThread:2561065 [wandb_run.py:_footer_sync_info():3871] logging synced files