def online():
# INIT
dr = Datareader(mode='online', only_load=True, verbose=False)
sb = Submitter(dr)
# LOAD AND COMBINE
eurm_lele = sparse.load_npz(
ROOT_DIR +
'/data/jess/ensembled_CLUSTERARTISTS_CREATIVA_cat3-4-5-8-10_online.npz'
)
eurm_std = sparse.load_npz(ROOT_DIR +
'/data/jess/ensembled_creativeFIRE_online.npz')
eurm_ens = combine_two_eurms(eurm_lele,
eurm_std,
cat_first=[3, 4, 5, 8, 10])
# LOAD MATRICES
# eurm_ens = sparse.load_npz(ROOT_DIR + '/data/ensembled_creativeFIRE_online.npz')
sim = sparse.load_npz(ROOT_DIR + '/data/sim_online.npz')
# HOLEBOOST
hb = HoleBoost(similarity=sim,
eurm=eurm_ens,
datareader=dr,
norm=norm_l1_row)
eurm_ens = hb.boost_eurm(categories=[8], k=300, gamma=1)
hb = HoleBoost(similarity=sim,
eurm=eurm_ens,
datareader=dr,
norm=norm_l1_row)
eurm_ens = hb.boost_eurm(categories=[10], k=150, gamma=1)
# TAILBOOST
tb = TailBoost(similarity=sim,
eurm=eurm_ens,
datareader=dr,
norm=norm_l2_row)
eurm_ens = tb.boost_eurm(categories=[9, 7, 6, 5],
last_tracks=[10, 3, 3, 3],
k=[100, 80, 100, 100],
gamma=[0.01, 0.01, 0.01, 0.01])
# ALBUMBOOST
ab = AlbumBoost(dr, eurm_ens)
eurm_ens = ab.boost_eurm(categories=[3, 4, 7, 9],
gamma=2,
top_k=[3, 3, 10, 40])
# MATCHBOOST
# mb = MatchBoost(datareader=dr, eurm=eurm_ens, top_k_alb=5000, top_k_art=10000)
# eurm_ens, pids = mb.boost_eurm(categories='all', k_art=20, k_alb=20, gamma_art=1.0, gamma_alb=1.0)
# SUBMISSION
rec_list = eurm_to_recommendation_list_submission(eurm_ens, datareader=dr)
sb.submit(rec_list, name='ens_30_june_jess+lele_boosts', track='creative')
def main(argv):
sbatch_cfg = {
# Account name
'account': 'rrg-whitem',
# Job name
'job-name': 'catcher',
# Job time
'time': '0-10:00:00',
# GPU/CPU type
'--cpus-per-task': 1,
# Memory
'mem-per-cpu': '2000M',
# Email address
'mail-user': '******'
}
# sbatch configs backup for different games
# sbatch_cfg['job-name'], sbatch_cfg['time'], sbatch_cfg['mem-per-cpu'] = 'catcher', '0-10:00:00', '2000M'
# sbatch_cfg['job-name'], sbatch_cfg['time'], sbatch_cfg['mem-per-cpu'] = 'copter', '0-05:00:00', '2000M'
# sbatch_cfg['job-name'], sbatch_cfg['time'], sbatch_cfg['mem-per-cpu'] = 'lunar', '0-07:00:00', '2000M'
# sbatch_cfg['job-name'], sbatch_cfg['time'], sbatch_cfg['mem-per-cpu'] = 'minatar', '1-08:00:00', '4000M'
general_cfg = {
# User name
'user': '******',
# Sbatch script path
'script-path': './sbatch.sh',
# Check time interval in minutes
'check-time-interval': 5,
# Clusters info: {name: capacity}
'clusters': {
'Cedar': 3000
},
# Job indexes list
'job-list': list(range(1, 30 + 1))
}
make_dir(f"output/{sbatch_cfg['job-name']}")
submitter = Submitter(general_cfg, sbatch_cfg)
submitter.submit()
def submission(boost, eurm_ens, sim, name):
"""
Function to create a submission from a eurm with or without boosts.
:param boost: apply boosts
:param eurm_ens: eurm from ensemble (10k x 2.2M)
:param sim: similarity matrix (tracks x tracks)
:param name: name of the submission
"""
# INIT
dr = Datareader(mode='online', only_load=True, verbose=False)
sb = Submitter(dr)
if boost:
# HOLEBOOST
hb = HoleBoost(similarity=sim,
eurm=eurm_ens,
datareader=dr,
norm=norm_l1_row)
eurm_ens = hb.boost_eurm(categories=[8, 10], k=300, gamma=5)
# TAILBOOST
tb = TailBoost(similarity=sim,
eurm=eurm_ens,
datareader=dr,
norm=norm_l2_row)
eurm_ens = tb.boost_eurm(categories=[9, 7, 6, 5],
last_tracks=[10, 3, 3, 3],
k=[100, 80, 100, 100],
gamma=[0.01, 0.01, 0.01, 0.01])
# ALBUMBOOST
ab = AlbumBoost(dr, eurm_ens)
eurm_ens = ab.boost_eurm(categories=[3, 4, 7, 9],
gamma=2,
top_k=[3, 3, 10, 40])
# SUBMISSION
rec_list = eurm_to_recommendation_list_submission(eurm_ens, datareader=dr)
sb.submit(rec_list, name=name)
urm = dr.get_urm()
pid = dr.get_test_pids()
#Fitting data
rec.fit(urm, pid)
#Computing similarity/model
rec.compute_model(top_k=knn,
sm_type=sm.TVERSKY,
shrink=200,
alpha=0.1,
beta=1,
binary=True,
verbose=True)
#Computing ratings
rec.compute_rating(top_k=topk, verbose=True, small=True)
#submission and saving
sps.save_npz(complete_name + ".npz", rec.eurm)
sb = Submitter(dr)
sb.submit(recommendation_list=eurm_to_recommendation_list_submission(
rec.eurm),
name=complete_name,
track="main",
verify=True,
gzipped=True)
else:
print("invalid mode.")
