def test8_serialization(self):
opt = BPRMFOption().get_default_option()
opt.num_iters = 200
opt.d = 5
opt.validation = aux.Option({'topk': 10})
self._test8_serialization(BPRMF, opt)
def test05_validation(self):
np.random.seed(7)
opt = BPRMFOption().get_default_option()
opt.d = 5
opt.num_workers = 4
opt.num_iters = 500
opt.random_seed = 7
opt.validation = aux.Option({'topk': 10})
opt.tensorboard = aux.Option({'root': './tb', 'name': 'bpr'})
self._test5_validation(BPRMF, opt, ndcg=0.03, map=0.02)
def test12_gpu_train_ml_20m(self):
if not inited_CUBPR:
return
opt = BPRMFOption().get_default_option()
opt.accelerator = True
opt.d = 100
opt.verify_neg = False
opt.num_iters = 30
opt.evaluation_period = 5
opt.validation = aux.Option({'topk': 10})
self._test7_train_ml_20m(BPRMF, opt)
def test11_gpu_validation(self):
if not inited_CUBPR:
return
np.random.seed(7)
opt = BPRMFOption().get_default_option()
opt.d = 100
opt.verify_neg = False
opt.accelerator = True
opt.lr = 0.01
opt.reg_b = 10.0
opt.num_iters = 500
opt.evaluation_period = 50
opt.random_seed = 777
opt.validation = aux.Option({'topk': 10})
opt.tensorboard = aux.Option({'root': './tb', 'name': 'bpr'})
self._test5_validation(BPRMF, opt, ndcg=0.03, map=0.02)
def test07_topk_pool(self):
set_log_level(2)
data_opt = self.get_ml100k_mm_opt()
opt = BPRMFOption().get_default_option()
opt.d = 20
opt.num_workers = 1
model = BPRMF(opt, data_opt=data_opt)
model.initialize()
model.train()
par = ParBPRMF(model)
pool = np.array([i for i in range(5)], dtype=np.int32)
model.build_userid_map()
all_keys = model._idmanager.userids[::][:10]
naive = model.topk_recommendation(all_keys, topk=10, pool=pool)
qkeys1, topks1, scores1 = par.topk_recommendation(all_keys, topk=10, pool=pool, repr=True)
for q, t in zip(qkeys1, topks1):
self.assertEqual(naive[q], t)
def test03_most_similar(self):
set_log_level(1)
data_opt = self.get_ml100k_mm_opt()
opt = BPRMFOption().get_default_option()
opt.d = 20
opt.num_workers = 1
bpr = BPRMF(opt, data_opt=data_opt)
bpr.initialize()
bpr.train()
bpr.build_itemid_map()
parbpr = ParBPRMF(bpr)
all_keys = bpr._idmanager.itemids[::]
start_t = time.time()
[bpr.most_similar(k, topk=10) for k in all_keys]
naive_elapsed = time.time() - start_t
parbpr.num_workers = 4
start_t = time.time()
parbpr.most_similar(all_keys, topk=10, repr=True)
parbpr_elapsed = time.time() - start_t
self.assertTrue(naive_elapsed > parbpr_elapsed * 3.0)
def test10_fast_most_similar(self):
opt = BPRMFOption().get_default_option()
opt.d = 5
opt.validation = aux.Option({'topk': 10})
self._test10_fast_most_similar(BPRMF, opt)
def test4_train(self):
opt = BPRMFOption().get_default_option()
opt.d = 5
self._test4_train(BPRMF, opt)