target_list, target_index_list, target_nmr_list = new_read_database(
target_filename)
target_outdic = {'nmr': target_nmr_list[target_index]}
target_mol = target_list[target_index]
if __name__ == "__main__":
comm = MPI.COMM_WORLD
size = comm.size
rank = comm.rank
status = MPI.Status()
READY, START, DONE, EXIT = 0, 1, 2, 3
val = [
'\n', '&', 'O', 'c', '1', '(', ')', '=', 'C', 'N', '#', 'n', '2', 'o',
'3', '-', '4'
]
chem_model = loaded_model()
graph = tf.get_default_graph()
chemical_state = chemical()
ts_strategy = cnf.get('param', 'ts_strategy') #'uct', 'puct'
search_parameter = float(
cnf.get('param', 'search_parameter')
) #If ts_strategy=='uct', 0 < search_parameter < 1. If ts_strategy=='puct', default value is 5 (AlphaGo).
num_simulations = int(cnf.get(
'param', 'num_simulations')) # core - 1, max: 2560 (skylake)
gau_parallel = 1
num_rollout = int(cnf.get('param', 'num_rollout'))
simulation_time = 3600 * int(cnf.get(
'param', 'simulation_time')) # 3600*24 # max: 168h
trie = int(cnf.get('param', 'trie'))
random_trie = int(cnf.get('param', 'random_trie'))
alpha = 1 # alph*mean + (1 - alpha)*max + bais
all_com = []
all_score = []
val_score = []
load_bal = []
sim_time = []
lock = Lock()
stored_jobs = []
coll = []
exp_time = []
print("check all ranks:", rank)
"""
start distributing jobs to all ranks
"""
graph = tf.get_default_graph()
#graph.finalize()
model = loaded_model()
model._make_predict_function()
mem = np.zeros(1024 * 10 * 1024) #8192)
MPI.Attach_buffer(mem)
num_cores = 8
#q1=Queue()
num_job = num_cores
random.seed(1)
hsm = HashTable()
#hsm=comm.bcast(hsm,root=0)
if rank == 0:
_, rootdest = hsm.hashing(['&'])
#print ("rootdest:",rootdest)
for i in range(num_job):
comm.bsend(rootnode, dest=rootdest, tag=0)
