"learning_rate": 10.0,
"initial_weight": 1e3, # (pA)
"rho": 0.01, # (Hz)
"delta": 0.2, # (mV)
"E_L": -70.0, # (mV)
"record_stimuli_to_file": False,
"record_connections_to_file": False,
"record_input_to_file": False,
"record_output_to_file": False,
"file_name_input": "input-{generation}-{label}.npy",
"file_name_output": "output-{generation}-{label}.npy",
"file_name_stimuli": "stimuli-{generation}.npy",
"file_name_template": "connections-{generation}-{label}.npy",
}
sim_key = dicthash.generate_hash_from_dict(sim_params)
params = {
"sim_key": sim_key, # consistency check
# machine setup
"submit_command": "sbatch",
"jobfile_template": "slurm_template.jdf",
"jobname": <jobname>,
"wall_clock_limit": "12:00:00",
"n_processes": 8,
"n_threads": 8,
"n_nodes": 1,
"mail": <mail>,
"account": <account>,
"partition": <partition>,
"sim_script": "main.py",
results_folder = 'optimized_run_time_12h'
initial_seed_array = [
1234567810, 1234567820, 1234567830, 1234567840, 1234567850, 1234567860,
1234567870, 1234567880, 1234567890
]
for use_drxeot_init in [True]:
params['use_drxeot_init'] = use_drxeot_init
for initial_seed in initial_seed_array:
params['seeds'] = np.linspace(initial_seed, initial_seed + 3, 4)
key = dicthash.generate_hash_from_dict(params)
params['outputdir'] = os.path.join(os.getcwd(), results_folder,
key)
params['workingdir'] = os.getcwd()
submit_job = True
print('preparing job')
print(' ', params['outputdir'])
utils.mkdirp(params['outputdir'])
utils.write_pickle(
params, os.path.join(params['outputdir'], 'params.pickle'))
utils.create_jobfile(params)
utils.copy_file(params['sim_script'], params['outputdir'])
# evo parameters
"population_params": {"n_parents": 8, "mutation_rate": 0.05},
"ea_params": {"n_offsprings": 8, "n_breeding": 8, "tournament_size": 1},
"genome_params": {
"n_inputs": 2,
"n_outputs": 1,
"n_columns": 5,
"n_rows": 1,
"levels_back": None,
},
},
}
params["md5_hash_sim_script"] = utils.md5_file(params["machine_params"]["sim_script"])
key = dicthash.generate_hash_from_dict(params, blacklist=[("gp_params", "max_generations")])
params["machine_params"]["workingdir"] = os.getcwd()
params["machine_params"]["outputdir"] = os.path.join(params["machine_params"]["workingdir"], key)
print("preparing job")
print(" ", params["machine_params"]["outputdir"])
utils.mkdirp(params["machine_params"]["outputdir"])
utils.write_json(params, f"{params['machine_params']['outputdir']}/params.json")
utils.create_jobfile(params["machine_params"])
utils.copy_file(params["machine_params"]["sim_script"], params["machine_params"]["outputdir"])
for fn in ["write_job.py", "sim_utils.py", "primitive_utils.py"]:
utils.copy_file(fn, params["machine_params"]["outputdir"])
os.chdir(params["machine_params"]["outputdir"])