model.build()
model.set_up_train()
model.restore(save_dir=SAVE_DIR)
model.prepare_test()
for activate_k in ACTIVATE_K_SET:
performance_th = model.test_th(activate_k, K_SET)
performance_vq = model.test_vq(activate_k, K_SET)
write_pkl({
'th': performance_th,
'vq': performance_vq
},
path=PKL_DIR + FILE_ID + '_{}.pkl'.format(activate_k))
cwrite = CsvWriter2(2)
key_set = [
'train_nmi', 'test_nmi', 'te_tr_suf', 'te_te_suf',
'te_tr_precision_at_k', 'te_te_precision_at_k',
'te_tr_recall_at_k', 'te_te_recall_at_k'
]
for key in key_set:
cwrite.add_header(0, str(key) + "_th")
cwrite.add_header(1, str(key) + "_vq")
content = ''
if 'suf' in str(key): content = listformat(performance_th[key])
elif 'at_k' in str(key): content = listformat(performance_th[key])
else: content = performance_th[key]
# load data
datasetmanager = DATASETMANAGER_DICT[args.dataset]
dm_train, dm_val, dm_test = datasetmanager(args.ltype,
nsclass=args.nsclass)
for v in [dm_train, dm_val, dm_test]:
v.print_shape()
model = DeepMetric(dm_train, dm_val, dm_test, LOG_DIR + FILE_ID + '.log',
args)
model.build()
model.set_up_train()
try:
model.restore(save_dir=SAVE_DIR)
except AttributeError:
model.initialize()
model.train(epoch=args.epoch, save_dir=SAVE_DIR, board_dir=BOARD_DIR)
model.restore(save_dir=SAVE_DIR)
model.prepare_test()
performance = model.test_metric(K_SET)
key_set = [
'te_tr_recall_at_k', 'te_tr_precision_at_k', 'te_te_recall_at_k',
'te_te_precision_at_k'
]
cwrite = CsvWriter2(1)
for key in key_set:
cwrite.add_header(0, str(key))
cwrite.add_content(0, listformat(performance[key]))
cwrite.write(CSV_DIR + FILE_ID + '.csv')
write_pkl(performance, path=PKL_DIR + FILE_ID + '.pkl')