Dist_no_pri_run4_1.log

INFO:root:Namespace(Ks='[20, 40]', batch_size=64, data_path='./data/recommendation/', dataset='ml-1m', embed_size=64, epoch=10000, gpu=3, item_density_threshold=0.01, item_threshold=30, layer_size=[64, 64, 64], lmbda=1, local_batch_size=1, local_epoch=1, log_name='run4_1', log_path='/home/qhuaf/graph_pri/logs/', lr=0.001, mess_dropout=[0.1, 0.1, 0.1], model_name='two_side_graph.pkl', num_neighbor=30, num_process=4, pretrain_epoch=300, pri_epoch=200, privacy_protect=False, regs=[1e-05], report=0, save_flag=1, test_flag='part', user_batch_size=128, verbose=10, weights_path='model/')
INFO:root:Epoch 99 [11.3s + 11.8s]: train==[692.29901=692.27332 + 0.02511], recall=[0.00812, 0.01585], precision=[0.00314, 0.00299], hit=[0.05978, 0.10610], ndcg=[0.02165, 0.03201]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 199 [9.1s + 11.4s]: train==[691.54132=691.51550 + 0.02510], recall=[0.01148, 0.02071], precision=[0.00417, 0.00380], hit=[0.07810, 0.13393], ndcg=[0.03031, 0.04300]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 299 [9.3s + 11.4s]: train==[690.66284=690.63721 + 0.02511], recall=[0.01743, 0.02962], precision=[0.00594, 0.00513], hit=[0.10880, 0.17720], ndcg=[0.04293, 0.05851]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 399 [11.0s + 10.5s]: train==[689.80817=689.78320 + 0.02511], recall=[0.02746, 0.04309], precision=[0.00881, 0.00722], hit=[0.15583, 0.23483], ndcg=[0.06301, 0.08230]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 499 [9.4s + 11.6s]: train==[688.72418=688.69916 + 0.02511], recall=[0.04104, 0.06171], precision=[0.01305, 0.01000], hit=[0.21777, 0.30215], ndcg=[0.09019, 0.11264]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 599 [9.5s + 11.4s]: train==[687.65851=687.63300 + 0.02511], recall=[0.05790, 0.08324], precision=[0.01803, 0.01325], hit=[0.28169, 0.37307], ndcg=[0.12012, 0.14644]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 699 [9.5s + 11.5s]: train==[686.47797=686.45319 + 0.02511], recall=[0.07877, 0.10636], precision=[0.02400, 0.01698], hit=[0.35422, 0.43824], ndcg=[0.15131, 0.17993]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 799 [9.4s + 12.4s]: train==[685.26208=685.23724 + 0.02511], recall=[0.09629, 0.13045], precision=[0.03027, 0.02094], hit=[0.40952, 0.49713], ndcg=[0.17742, 0.20901]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 899 [11.4s + 11.5s]: train==[683.64197=683.61621 + 0.02511], recall=[0.11575, 0.15496], precision=[0.03653, 0.02485], hit=[0.46050, 0.55009], ndcg=[0.19896, 0.23358]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 999 [9.5s + 10.8s]: train==[681.95374=681.92798 + 0.02511], recall=[0.13324, 0.17835], precision=[0.04233, 0.02901], hit=[0.50395, 0.59354], ndcg=[0.21455, 0.25297]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 1099 [9.6s + 11.1s]: train==[680.05115=680.02509 + 0.02511], recall=[0.14499, 0.20229], precision=[0.04689, 0.03303], hit=[0.53016, 0.63662], ndcg=[0.22472, 0.27042]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 1199 [9.6s + 11.3s]: train==[677.89075=677.86615 + 0.02511], recall=[0.15568, 0.22125], precision=[0.05087, 0.03621], hit=[0.55099, 0.66032], ndcg=[0.23068, 0.28056]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 1299 [9.5s + 12.6s]: train==[675.40344=675.37848 + 0.02510], recall=[0.16262, 0.23466], precision=[0.05336, 0.03874], hit=[0.56373, 0.67684], ndcg=[0.23314, 0.28734]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 1399 [9.4s + 11.0s]: train==[672.71600=672.69141 + 0.02511], recall=[0.16753, 0.24328], precision=[0.05500, 0.04044], hit=[0.56786, 0.68815], ndcg=[0.23508, 0.29225]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 1499 [9.9s + 12.2s]: train==[669.64270=669.61829 + 0.02510], recall=[0.17106, 0.24959], precision=[0.05625, 0.04163], hit=[0.57289, 0.69551], ndcg=[0.23735, 0.29612]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 1599 [9.4s + 11.9s]: train==[666.25555=666.23047 + 0.02510], recall=[0.17408, 0.25419], precision=[0.05707, 0.04263], hit=[0.57917, 0.70090], ndcg=[0.23904, 0.29906]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 1699 [10.1s + 11.9s]: train==[662.62311=662.59851 + 0.02510], recall=[0.17594, 0.25654], precision=[0.05765, 0.04315], hit=[0.58205, 0.70431], ndcg=[0.23997, 0.30062]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 1799 [9.6s + 11.3s]: train==[658.74969=658.72449 + 0.02510], recall=[0.17735, 0.25849], precision=[0.05807, 0.04360], hit=[0.58546, 0.70682], ndcg=[0.24020, 0.30144]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 1899 [11.5s + 13.7s]: train==[654.33618=654.31128 + 0.02510], recall=[0.17776, 0.25988], precision=[0.05818, 0.04386], hit=[0.58348, 0.70969], ndcg=[0.24010, 0.30232]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 1999 [9.6s + 12.4s]: train==[650.15839=650.13324 + 0.02510], recall=[0.17948, 0.26052], precision=[0.05840, 0.04406], hit=[0.58707, 0.71023], ndcg=[0.24096, 0.30290]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 2099 [11.4s + 13.2s]: train==[645.33514=645.31036 + 0.02510], recall=[0.17963, 0.26161], precision=[0.05839, 0.04424], hit=[0.58779, 0.71041], ndcg=[0.24089, 0.30347]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 2199 [10.6s + 12.6s]: train==[640.68829=640.66315 + 0.02510], recall=[0.18020, 0.26185], precision=[0.05867, 0.04435], hit=[0.58923, 0.70987], ndcg=[0.24164, 0.30373]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 2299 [10.0s + 13.9s]: train==[635.07544=635.05011 + 0.02510], recall=[0.18077, 0.26213], precision=[0.05882, 0.04437], hit=[0.59120, 0.70987], ndcg=[0.24261, 0.30436]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 2399 [10.2s + 12.0s]: train==[630.06775=630.04297 + 0.02510], recall=[0.18130, 0.26156], precision=[0.05893, 0.04437], hit=[0.59210, 0.70862], ndcg=[0.24271, 0.30404]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 2499 [13.4s + 14.3s]: train==[624.19043=624.16492 + 0.02510], recall=[0.18136, 0.26298], precision=[0.05902, 0.04457], hit=[0.59174, 0.70987], ndcg=[0.24246, 0.30441]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 2599 [11.3s + 13.4s]: train==[618.95740=618.93146 + 0.02510], recall=[0.18156, 0.26351], precision=[0.05909, 0.04471], hit=[0.59210, 0.70969], ndcg=[0.24252, 0.30461]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 2699 [10.6s + 13.3s]: train==[613.17352=613.14874 + 0.02510], recall=[0.18185, 0.26339], precision=[0.05918, 0.04470], hit=[0.59336, 0.70898], ndcg=[0.24332, 0.30504]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 2799 [11.0s + 13.3s]: train==[606.61371=606.58960 + 0.02510], recall=[0.18234, 0.26395], precision=[0.05934, 0.04471], hit=[0.59515, 0.70916], ndcg=[0.24363, 0.30508]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 2899 [11.3s + 14.1s]: train==[600.35370=600.32874 + 0.02510], recall=[0.18235, 0.26452], precision=[0.05934, 0.04474], hit=[0.59425, 0.71023], ndcg=[0.24367, 0.30537]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 2999 [11.4s + 13.5s]: train==[593.71582=593.69189 + 0.02510], recall=[0.18256, 0.26408], precision=[0.05944, 0.04476], hit=[0.59461, 0.71077], ndcg=[0.24376, 0.30532]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 3099 [11.3s + 13.6s]: train==[586.49634=586.47089 + 0.02510], recall=[0.18272, 0.26450], precision=[0.05959, 0.04479], hit=[0.59569, 0.71113], ndcg=[0.24405, 0.30555]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 3199 [13.3s + 13.9s]: train==[580.86188=580.83716 + 0.02510], recall=[0.18281, 0.26539], precision=[0.05942, 0.04490], hit=[0.59479, 0.71293], ndcg=[0.24342, 0.30572]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 3299 [13.2s + 13.9s]: train==[574.01080=573.98529 + 0.02510], recall=[0.18296, 0.26522], precision=[0.05948, 0.04487], hit=[0.59497, 0.71329], ndcg=[0.24365, 0.30578]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 3399 [12.9s + 14.4s]: train==[566.81903=566.79358 + 0.02510], recall=[0.18237, 0.26550], precision=[0.05945, 0.04491], hit=[0.59461, 0.71311], ndcg=[0.24290, 0.30524]
INFO:root:Epoch 3499 [10.9s + 14.5s]: train==[560.06531=560.04004 + 0.02510], recall=[0.18266, 0.26628], precision=[0.05950, 0.04498], hit=[0.59515, 0.71400], ndcg=[0.24318, 0.30572]
INFO:root:Epoch 3599 [10.7s + 13.7s]: train==[552.82904=552.80371 + 0.02510], recall=[0.18282, 0.26529], precision=[0.05960, 0.04495], hit=[0.59605, 0.71221], ndcg=[0.24362, 0.30559]
INFO:root:Namespace(Ks='[20, 40]', batch_size=64, data_path='./data/recommendation/', dataset='ml-1m', embed_size=128, epoch=10000, gpu=0, item_density_threshold=0.01, item_threshold=30, layer_size=[128], lmbda=1, local_batch_size=128, local_epoch=10, log_name='run4_1', log_path='/home/qhuaf/graph_pri/logs/', lr=0.0001, mess_dropout=[0.1, 0.1, 0.1], model_name='two_side_graph.pkl', num_neighbor=30, num_process=4, pretrain_epoch=300, pri_epoch=200, privacy_protect=False, regs=[1e-05], report=0, save_flag=1, test_flag='part', user_batch_size=128, verbose=10, weights_path='model/')
INFO:root:Epoch 9 [19.6s + 12.5s]: train==[692.07312=692.05768 + 0.01521], recall=[0.00630, 0.01355], precision=[0.00246, 0.00261], hit=[0.04758, 0.09372], ndcg=[0.01595, 0.02618]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 19 [19.5s + 12.7s]: train==[691.50031=691.48431 + 0.01521], recall=[0.00787, 0.01682], precision=[0.00305, 0.00316], hit=[0.05871, 0.11364], ndcg=[0.02002, 0.03216]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 29 [20.0s + 12.8s]: train==[691.29987=691.28406 + 0.01521], recall=[0.00884, 0.01762], precision=[0.00328, 0.00333], hit=[0.06266, 0.11867], ndcg=[0.02162, 0.03408]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 39 [19.6s + 12.5s]: train==[691.00836=690.99310 + 0.01521], recall=[0.00938, 0.01887], precision=[0.00353, 0.00351], hit=[0.06715, 0.12442], ndcg=[0.02320, 0.03595]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 49 [19.6s + 13.1s]: train==[690.83234=690.81726 + 0.01521], recall=[0.01046, 0.01999], precision=[0.00387, 0.00368], hit=[0.07343, 0.13016], ndcg=[0.02548, 0.03827]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 59 [20.0s + 12.6s]: train==[690.57629=690.56030 + 0.01521], recall=[0.01158, 0.02162], precision=[0.00422, 0.00393], hit=[0.07953, 0.13806], ndcg=[0.02771, 0.04097]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 69 [19.8s + 12.5s]: train==[690.40491=690.39014 + 0.01521], recall=[0.01242, 0.02386], precision=[0.00456, 0.00429], hit=[0.08510, 0.14955], ndcg=[0.03019, 0.04475]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 79 [16.3s + 13.4s]: train==[690.09302=690.07806 + 0.01521], recall=[0.01404, 0.02657], precision=[0.00499, 0.00464], hit=[0.09318, 0.16158], ndcg=[0.03374, 0.04931]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 89 [19.7s + 13.4s]: train==[689.78320=689.76807 + 0.01521], recall=[0.01596, 0.02956], precision=[0.00554, 0.00511], hit=[0.10269, 0.17558], ndcg=[0.03753, 0.05427]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 99 [19.4s + 12.3s]: train==[689.47125=689.45636 + 0.01521], recall=[0.01704, 0.03138], precision=[0.00596, 0.00543], hit=[0.10969, 0.18492], ndcg=[0.04090, 0.05844]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 109 [19.9s + 12.9s]: train==[689.18909=689.17340 + 0.01521], recall=[0.01996, 0.03504], precision=[0.00676, 0.00596], hit=[0.12424, 0.20054], ndcg=[0.04642, 0.06463]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 119 [19.7s + 12.9s]: train==[688.73340=688.71838 + 0.01521], recall=[0.02379, 0.03951], precision=[0.00774, 0.00665], hit=[0.14039, 0.21849], ndcg=[0.05328, 0.07235]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 129 [20.2s + 13.4s]: train==[688.41833=688.40234 + 0.01521], recall=[0.02708, 0.04328], precision=[0.00870, 0.00732], hit=[0.15548, 0.23842], ndcg=[0.06033, 0.08066]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 139 [18.9s + 13.3s]: train==[687.88086=687.86621 + 0.01521], recall=[0.03057, 0.04894], precision=[0.00980, 0.00820], hit=[0.17181, 0.25961], ndcg=[0.06826, 0.09031]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 149 [19.6s + 13.2s]: train==[687.37933=687.36469 + 0.01521], recall=[0.03460, 0.05537], precision=[0.01122, 0.00923], hit=[0.19282, 0.28654], ndcg=[0.07793, 0.10191]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 159 [19.6s + 13.4s]: train==[686.94269=686.92719 + 0.01521], recall=[0.03989, 0.06232], precision=[0.01263, 0.01038], hit=[0.21454, 0.31329], ndcg=[0.08819, 0.11445]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 169 [20.3s + 12.8s]: train==[686.27753=686.26202 + 0.01521], recall=[0.04581, 0.07047], precision=[0.01464, 0.01161], hit=[0.24237, 0.34255], ndcg=[0.10032, 0.12767]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 179 [19.4s + 13.6s]: train==[685.76123=685.74506 + 0.01521], recall=[0.05185, 0.07956], precision=[0.01665, 0.01278], hit=[0.26894, 0.36804], ndcg=[0.11322, 0.14133]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 189 [20.5s + 13.7s]: train==[685.00177=684.98706 + 0.01521], recall=[0.05899, 0.08804], precision=[0.01873, 0.01407], hit=[0.29569, 0.39138], ndcg=[0.12639, 0.15511]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 199 [20.1s + 13.4s]: train==[684.17511=684.16046 + 0.01521], recall=[0.06607, 0.09648], precision=[0.02083, 0.01551], hit=[0.32136, 0.41688], ndcg=[0.13911, 0.16910]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 209 [19.8s + 13.3s]: train==[683.31036=683.29535 + 0.01521], recall=[0.07266, 0.10695], precision=[0.02300, 0.01726], hit=[0.34381, 0.44722], ndcg=[0.15065, 0.18381]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 219 [19.9s + 13.3s]: train==[682.56976=682.55426 + 0.01521], recall=[0.07956, 0.11618], precision=[0.02542, 0.01875], hit=[0.36553, 0.47145], ndcg=[0.16381, 0.19834]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 229 [19.8s + 13.4s]: train==[681.47498=681.45892 + 0.01521], recall=[0.08810, 0.12765], precision=[0.02825, 0.02064], hit=[0.39443, 0.49964], ndcg=[0.17460, 0.21071]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 239 [19.6s + 13.5s]: train==[680.46033=680.44531 + 0.01521], recall=[0.09554, 0.13784], precision=[0.03090, 0.02257], hit=[0.41706, 0.52711], ndcg=[0.18377, 0.22237]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 249 [19.7s + 13.3s]: train==[679.02313=679.00769 + 0.01521], recall=[0.10428, 0.14868], precision=[0.03349, 0.02444], hit=[0.43914, 0.55027], ndcg=[0.19207, 0.23246]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 259 [19.5s + 13.6s]: train==[677.85895=677.84381 + 0.01521], recall=[0.11187, 0.16001], precision=[0.03618, 0.02633], hit=[0.46104, 0.57343], ndcg=[0.19952, 0.24211]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 269 [16.1s + 12.8s]: train==[676.38403=676.36884 + 0.01521], recall=[0.12007, 0.17067], precision=[0.03890, 0.02826], hit=[0.48420, 0.59372], ndcg=[0.20696, 0.25110]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 279 [14.5s + 13.3s]: train==[674.83130=674.81525 + 0.01521], recall=[0.12713, 0.18207], precision=[0.04142, 0.03020], hit=[0.50233, 0.61131], ndcg=[0.21263, 0.25861]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 289 [13.7s + 12.6s]: train==[673.20227=673.18787 + 0.01521], recall=[0.13254, 0.19202], precision=[0.04353, 0.03200], hit=[0.51508, 0.62531], ndcg=[0.21612, 0.26472]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 299 [14.3s + 12.7s]: train==[671.27679=671.26086 + 0.01521], recall=[0.13878, 0.20336], precision=[0.04561, 0.03379], hit=[0.52819, 0.63950], ndcg=[0.21881, 0.26980]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 309 [14.2s + 12.5s]: train==[669.25195=669.23645 + 0.01521], recall=[0.14497, 0.21247], precision=[0.04772, 0.03549], hit=[0.54075, 0.65027], ndcg=[0.22195, 0.27456]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 319 [14.1s + 13.5s]: train==[667.15857=667.14380 + 0.01521], recall=[0.14973, 0.22019], precision=[0.04961, 0.03696], hit=[0.55009, 0.66104], ndcg=[0.22478, 0.27923]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 329 [14.1s + 13.1s]: train==[665.17322=665.15820 + 0.01521], recall=[0.15551, 0.22655], precision=[0.05154, 0.03807], hit=[0.55835, 0.66912], ndcg=[0.22824, 0.28297]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 339 [13.9s + 12.2s]: train==[662.61853=662.60339 + 0.01521], recall=[0.15923, 0.23253], precision=[0.05293, 0.03918], hit=[0.56553, 0.67702], ndcg=[0.22991, 0.28604]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 349 [13.9s + 13.6s]: train==[660.30969=660.29510 + 0.01521], recall=[0.16218, 0.23748], precision=[0.05425, 0.04008], hit=[0.56930, 0.68312], ndcg=[0.23134, 0.28841]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 359 [14.3s + 13.2s]: train==[657.76221=657.74725 + 0.01521], recall=[0.16543, 0.24200], precision=[0.05518, 0.04086], hit=[0.57235, 0.68869], ndcg=[0.23283, 0.29109]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 369 [13.7s + 12.4s]: train==[654.85510=654.84058 + 0.01521], recall=[0.16773, 0.24459], precision=[0.05601, 0.04137], hit=[0.57630, 0.69102], ndcg=[0.23469, 0.29295]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 379 [14.0s + 13.2s]: train==[651.76031=651.74512 + 0.01521], recall=[0.17010, 0.24798], precision=[0.05682, 0.04197], hit=[0.58061, 0.69551], ndcg=[0.23572, 0.29454]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 389 [13.9s + 13.2s]: train==[648.57941=648.56403 + 0.01521], recall=[0.17159, 0.24980], precision=[0.05732, 0.04243], hit=[0.58133, 0.69731], ndcg=[0.23623, 0.29556]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 399 [14.8s + 13.9s]: train==[645.61365=645.59857 + 0.01521], recall=[0.17332, 0.25196], precision=[0.05767, 0.04287], hit=[0.58366, 0.70018], ndcg=[0.23680, 0.29687]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 409 [15.3s + 12.1s]: train==[642.17651=642.16113 + 0.01521], recall=[0.17510, 0.25336], precision=[0.05817, 0.04323], hit=[0.58618, 0.70072], ndcg=[0.23769, 0.29759]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 419 [15.0s + 12.9s]: train==[638.76862=638.75366 + 0.01521], recall=[0.17600, 0.25513], precision=[0.05856, 0.04358], hit=[0.58779, 0.70215], ndcg=[0.23835, 0.29851]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 429 [14.5s + 13.2s]: train==[635.19458=635.17993 + 0.01521], recall=[0.17708, 0.25625], precision=[0.05884, 0.04379], hit=[0.58977, 0.70323], ndcg=[0.23905, 0.29912]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 439 [15.4s + 12.2s]: train==[631.15143=631.13635 + 0.01521], recall=[0.17751, 0.25686], precision=[0.05896, 0.04403], hit=[0.58977, 0.70233], ndcg=[0.23931, 0.29954]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 449 [14.5s + 12.4s]: train==[627.60413=627.58923 + 0.01521], recall=[0.17771, 0.25760], precision=[0.05913, 0.04420], hit=[0.59084, 0.70233], ndcg=[0.23960, 0.29990]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 459 [14.5s + 11.8s]: train==[623.39880=623.38330 + 0.01521], recall=[0.17813, 0.25856], precision=[0.05922, 0.04439], hit=[0.59120, 0.70413], ndcg=[0.24011, 0.30081]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 469 [13.8s + 12.1s]: train==[619.82935=619.81403 + 0.01521], recall=[0.17858, 0.25863], precision=[0.05936, 0.04443], hit=[0.59264, 0.70377], ndcg=[0.24068, 0.30109]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Namespace(Ks='[20, 40]', batch_size=64, data_path='./data/recommendation/', dataset='ml-1m', embed_size=128, epoch=10000, gpu=0, item_density_threshold=0.01, item_threshold=30, layer_size=[128], lmbda=1, local_batch_size=128, local_epoch=10, log_name='run4_1', log_path='/home/qhuaf/graph_pri/logs/', lr=0.0001, mess_dropout=[0.1, 0.1, 0.1], model_name='two_side_graph.pkl', num_neighbor=30, num_process=4, pretrain_epoch=300, pri_epoch=200, privacy_protect=False, regs=[1e-05], report=0, save_flag=1, test_flag='part', user_batch_size=128, verbose=10, weights_path='model/')
INFO:root:Epoch 9 [13.9s + 12.8s]: train==[692.01849=692.00409 + 0.01521], recall=[0.00798, 0.01549], precision=[0.00292, 0.00282], hit=[0.05458, 0.10233], ndcg=[0.01881, 0.02916]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 19 [14.3s + 13.8s]: train==[689.50537=689.49005 + 0.01521], recall=[0.01751, 0.03052], precision=[0.00592, 0.00535], hit=[0.10808, 0.18079], ndcg=[0.04095, 0.05801]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 29 [14.6s + 13.8s]: train==[683.40918=683.39362 + 0.01521], recall=[0.06799, 0.09649], precision=[0.02257, 0.01621], hit=[0.33501, 0.42837], ndcg=[0.14887, 0.17816]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 39 [13.6s + 12.9s]: train==[668.25677=668.24170 + 0.01521], recall=[0.13421, 0.19694], precision=[0.04443, 0.03345], hit=[0.51741, 0.63914], ndcg=[0.21927, 0.27220]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 49 [13.9s + 12.6s]: train==[639.88342=639.86786 + 0.01521], recall=[0.16895, 0.24104], precision=[0.05583, 0.04142], hit=[0.57971, 0.69246], ndcg=[0.23678, 0.29413]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 59 [13.5s + 12.1s]: train==[599.13684=599.12170 + 0.01522], recall=[0.17752, 0.25305], precision=[0.05856, 0.04361], hit=[0.59318, 0.70215], ndcg=[0.24131, 0.30024]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 69 [13.6s + 12.0s]: train==[557.46704=557.45142 + 0.01522], recall=[0.18040, 0.25642], precision=[0.05952, 0.04439], hit=[0.59785, 0.70413], ndcg=[0.24188, 0.30081]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 79 [13.7s + 12.0s]: train==[521.96954=521.95398 + 0.01523], recall=[0.18144, 0.25847], precision=[0.05989, 0.04472], hit=[0.59551, 0.70395], ndcg=[0.24016, 0.29962]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 89 [13.8s + 12.4s]: train==[489.56918=489.55347 + 0.01523], recall=[0.18143, 0.26129], precision=[0.06010, 0.04506], hit=[0.59533, 0.70664], ndcg=[0.23949, 0.30000]
INFO:root:Epoch 99 [13.7s + 12.1s]: train==[464.57944=464.56369 + 0.01524], recall=[0.17957, 0.26263], precision=[0.05981, 0.04522], hit=[0.59282, 0.70969], ndcg=[0.23541, 0.29756]
INFO:root:Namespace(Ks='[20, 40]', batch_size=64, data_path='./data/recommendation/', dataset='ml-1m', embed_size=128, epoch=10000, gpu=0, item_density_threshold=0.01, item_threshold=30, layer_size=[128], lmbda=1, local_batch_size=128, local_epoch=10, log_name='run4_1', log_path='/home/qhuaf/graph_pri/logs/', lr=0.0001, mess_dropout=[0.1, 0.1, 0.1], model_name='two_side_graph.pkl', num_neighbor=30, num_process=4, pretrain_epoch=300, pri_epoch=200, privacy_protect=False, regs=[1e-05], report=0, save_flag=1, test_flag='part', user_batch_size=1024, verbose=1, weights_path='model/')
INFO:root:Namespace(Ks='[20, 40]', batch_size=64, data_path='./data/recommendation/', dataset='ml-1m', embed_size=128, epoch=10000, gpu=0, item_density_threshold=0.01, item_threshold=30, layer_size=[128], lmbda=1, local_batch_size=128, local_epoch=10, log_name='run4_1', log_path='/home/qhuaf/graph_pri/logs/', lr=0.0001, mess_dropout=[0.1, 0.1, 0.1], model_name='two_side_graph.pkl', num_neighbor=30, num_process=4, pretrain_epoch=300, pri_epoch=200, privacy_protect=False, regs=[1e-05], report=0, save_flag=1, test_flag='part', user_batch_size=1024, verbose=1, weights_path='model/')
INFO:root:Namespace(Ks='[20, 40]', batch_size=64, data_path='./data/recommendation/', dataset='ml-1m', embed_size=128, epoch=10000, gpu=0, item_density_threshold=0.01, item_threshold=30, layer_size=[128], lmbda=1, local_batch_size=128, local_epoch=10, log_name='run4_1', log_path='/home/qhuaf/graph_pri/logs/', lr=0.0001, mess_dropout=[0.1, 0.1, 0.1], model_name='two_side_graph.pkl', num_neighbor=30, num_process=4, pretrain_epoch=300, pri_epoch=200, privacy_protect=False, regs=[1e-05], report=0, save_flag=1, test_flag='part', user_batch_size=512, verbose=1, weights_path='model/')
INFO:root:Epoch 0 [41.6s + 12.1s]: train==[693.09882=693.08337 + 0.01521], recall=[0.00561, 0.01039], precision=[0.00220, 0.00215], hit=[0.04237, 0.07953], ndcg=[0.01425, 0.02227]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 1 [34.5s + 11.9s]: train==[692.94189=692.92719 + 0.01521], recall=[0.00585, 0.01097], precision=[0.00229, 0.00221], hit=[0.04417, 0.08187], ndcg=[0.01491, 0.02301]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 2 [34.0s + 12.2s]: train==[692.78040=692.76489 + 0.01521], recall=[0.00587, 0.01118], precision=[0.00233, 0.00224], hit=[0.04470, 0.08276], ndcg=[0.01519, 0.02333]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 3 [34.3s + 12.1s]: train==[692.68500=692.66992 + 0.01521], recall=[0.00595, 0.01155], precision=[0.00237, 0.00232], hit=[0.04560, 0.08564], ndcg=[0.01562, 0.02424]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 4 [34.8s + 12.7s]: train==[692.48871=692.47382 + 0.01521], recall=[0.00607, 0.01169], precision=[0.00241, 0.00236], hit=[0.04632, 0.08654], ndcg=[0.01586, 0.02460]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 5 [34.5s + 12.4s]: train==[692.25446=692.23981 + 0.01521], recall=[0.00612, 0.01208], precision=[0.00243, 0.00242], hit=[0.04668, 0.08887], ndcg=[0.01605, 0.02520]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 6 [34.4s + 12.4s]: train==[692.11212=692.09619 + 0.01521], recall=[0.00661, 0.01238], precision=[0.00261, 0.00249], hit=[0.04973, 0.09048], ndcg=[0.01701, 0.02592]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 7 [34.6s + 12.7s]: train==[692.01208=691.99634 + 0.01521], recall=[0.00679, 0.01284], precision=[0.00269, 0.00260], hit=[0.05135, 0.09479], ndcg=[0.01764, 0.02709]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 8 [34.8s + 13.0s]: train==[691.79944=691.78424 + 0.01521], recall=[0.00708, 0.01360], precision=[0.00282, 0.00271], hit=[0.05386, 0.09785], ndcg=[0.01839, 0.02802]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 9 [35.9s + 12.9s]: train==[691.62830=691.61310 + 0.01521], recall=[0.00722, 0.01443], precision=[0.00294, 0.00285], hit=[0.05619, 0.10269], ndcg=[0.01914, 0.02937]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 10 [34.8s + 12.6s]: train==[691.41034=691.39581 + 0.01521], recall=[0.00748, 0.01521], precision=[0.00298, 0.00300], hit=[0.05709, 0.10772], ndcg=[0.01968, 0.03088]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 11 [34.3s + 12.8s]: train==[691.16943=691.15442 + 0.01521], recall=[0.00791, 0.01623], precision=[0.00317, 0.00312], hit=[0.06032, 0.11131], ndcg=[0.02087, 0.03220]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 12 [34.7s + 12.5s]: train==[691.08215=691.06726 + 0.01521], recall=[0.00843, 0.01736], precision=[0.00332, 0.00330], hit=[0.06302, 0.11706], ndcg=[0.02206, 0.03407]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 13 [34.4s + 12.6s]: train==[690.81311=690.79871 + 0.01521], recall=[0.00893, 0.01847], precision=[0.00346, 0.00350], hit=[0.06553, 0.12226], ndcg=[0.02313, 0.03589]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 14 [34.6s + 13.1s]: train==[690.60669=690.59137 + 0.01521], recall=[0.00981, 0.02001], precision=[0.00369, 0.00368], hit=[0.06930, 0.12873], ndcg=[0.02472, 0.03806]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 15 [35.0s + 12.6s]: train==[690.36060=690.34479 + 0.01521], recall=[0.01060, 0.02157], precision=[0.00398, 0.00393], hit=[0.07433, 0.13591], ndcg=[0.02664, 0.04067]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 16 [34.8s + 13.0s]: train==[690.15533=690.13977 + 0.01521], recall=[0.01225, 0.02308], precision=[0.00440, 0.00418], hit=[0.08169, 0.14399], ndcg=[0.02913, 0.04336]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 17 [34.7s + 12.7s]: train==[689.77264=689.75757 + 0.01521], recall=[0.01317, 0.02506], precision=[0.00462, 0.00447], hit=[0.08564, 0.15350], ndcg=[0.03108, 0.04661]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 18 [35.0s + 12.5s]: train==[689.45691=689.44220 + 0.01521], recall=[0.01512, 0.02703], precision=[0.00529, 0.00485], hit=[0.09713, 0.16661], ndcg=[0.03550, 0.05135]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 19 [35.1s + 12.9s]: train==[689.20441=689.18982 + 0.01521], recall=[0.01702, 0.03016], precision=[0.00577, 0.00528], hit=[0.10485, 0.17864], ndcg=[0.03887, 0.05597]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 20 [35.2s + 12.0s]: train==[688.93073=688.91571 + 0.01521], recall=[0.01885, 0.03274], precision=[0.00640, 0.00574], hit=[0.11526, 0.19210], ndcg=[0.04283, 0.06096]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 21 [34.9s + 12.8s]: train==[688.62219=688.60626 + 0.01521], recall=[0.02190, 0.03669], precision=[0.00731, 0.00636], hit=[0.13052, 0.20898], ndcg=[0.04867, 0.06760]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 22 [35.1s + 12.3s]: train==[688.15173=688.13623 + 0.01521], recall=[0.02420, 0.04042], precision=[0.00814, 0.00689], hit=[0.14381, 0.22190], ndcg=[0.05512, 0.07473]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 23 [35.2s + 12.7s]: train==[687.70502=687.68988 + 0.01521], recall=[0.02813, 0.04512], precision=[0.00933, 0.00763], hit=[0.16230, 0.24309], ndcg=[0.06262, 0.08299]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 24 [34.6s + 12.7s]: train==[687.27161=687.25653 + 0.01521], recall=[0.03144, 0.05030], precision=[0.01046, 0.00846], hit=[0.17846, 0.26481], ndcg=[0.07118, 0.09310]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 25 [35.0s + 12.7s]: train==[686.79895=686.78320 + 0.01521], recall=[0.03554, 0.05638], precision=[0.01180, 0.00946], hit=[0.19820, 0.28959], ndcg=[0.08005, 0.10372]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 26 [34.9s + 12.9s]: train==[686.09979=686.08392 + 0.01521], recall=[0.04112, 0.06281], precision=[0.01343, 0.01053], hit=[0.22136, 0.31454], ndcg=[0.09173, 0.11661]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 27 [35.0s + 12.9s]: train==[685.65240=685.63611 + 0.01521], recall=[0.04711, 0.06913], precision=[0.01534, 0.01161], hit=[0.24740, 0.33878], ndcg=[0.10422, 0.12936]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 28 [34.4s + 12.4s]: train==[684.93469=684.91907 + 0.01521], recall=[0.05246, 0.07690], precision=[0.01717, 0.01293], hit=[0.27163, 0.36499], ndcg=[0.11619, 0.14307]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 29 [34.8s + 12.7s]: train==[684.16290=684.14838 + 0.01521], recall=[0.05915, 0.08497], precision=[0.01924, 0.01429], hit=[0.29767, 0.39066], ndcg=[0.12948, 0.15757]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 30 [34.8s + 13.0s]: train==[683.36279=683.34729 + 0.01521], recall=[0.06557, 0.09371], precision=[0.02140, 0.01571], hit=[0.32370, 0.41616], ndcg=[0.14236, 0.17166]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 31 [35.0s + 12.5s]: train==[682.62195=682.60645 + 0.01521], recall=[0.07332, 0.10366], precision=[0.02414, 0.01734], hit=[0.35242, 0.44632], ndcg=[0.15598, 0.18622]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 32 [34.4s + 12.5s]: train==[681.65747=681.64166 + 0.01521], recall=[0.08071, 0.11361], precision=[0.02652, 0.01907], hit=[0.37882, 0.47451], ndcg=[0.16775, 0.20036]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 33 [34.6s + 12.8s]: train==[680.60773=680.59186 + 0.01521], recall=[0.08896, 0.12395], precision=[0.02929, 0.02074], hit=[0.40413, 0.50018], ndcg=[0.17974, 0.21349]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 34 [34.8s + 12.7s]: train==[679.35181=679.33679 + 0.01521], recall=[0.09824, 0.13379], precision=[0.03239, 0.02247], hit=[0.43321, 0.52352], ndcg=[0.19293, 0.22643]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 35 [35.0s + 12.8s]: train==[678.05957=678.04498 + 0.01521], recall=[0.10581, 0.14422], precision=[0.03474, 0.02433], hit=[0.45153, 0.54686], ndcg=[0.20132, 0.23753]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 36 [34.8s + 12.4s]: train==[676.74414=676.72821 + 0.01521], recall=[0.11392, 0.15508], precision=[0.03732, 0.02610], hit=[0.47163, 0.56697], ndcg=[0.21002, 0.24782]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 37 [35.0s + 13.1s]: train==[675.45404=675.43842 + 0.01521], recall=[0.12177, 0.16471], precision=[0.03984, 0.02789], hit=[0.48833, 0.58528], ndcg=[0.21671, 0.25643]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 38 [35.3s + 12.5s]: train==[673.76477=673.74976 + 0.01521], recall=[0.12768, 0.17590], precision=[0.04226, 0.02960], hit=[0.50323, 0.60305], ndcg=[0.22227, 0.26402]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 39 [35.1s + 12.7s]: train==[672.20026=672.18512 + 0.01521], recall=[0.13334, 0.18588], precision=[0.04445, 0.03128], hit=[0.51670, 0.61903], ndcg=[0.22587, 0.26976]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 40 [35.8s + 13.0s]: train==[670.41986=670.40454 + 0.01521], recall=[0.13956, 0.19489], precision=[0.04649, 0.03271], hit=[0.52926, 0.63214], ndcg=[0.22991, 0.27512]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 41 [34.9s + 12.9s]: train==[668.43121=668.41583 + 0.01521], recall=[0.14385, 0.20357], precision=[0.04808, 0.03416], hit=[0.53842, 0.64434], ndcg=[0.23234, 0.27987]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 42 [35.4s + 12.7s]: train==[666.37384=666.35889 + 0.01521], recall=[0.15014, 0.21117], precision=[0.04993, 0.03545], hit=[0.54955, 0.65458], ndcg=[0.23529, 0.28375]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 43 [34.3s + 13.2s]: train==[664.18463=664.16998 + 0.01521], recall=[0.15575, 0.21865], precision=[0.05166, 0.03654], hit=[0.55961, 0.66517], ndcg=[0.23756, 0.28686]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 44 [35.3s + 12.6s]: train==[661.68384=661.66876 + 0.01521], recall=[0.16043, 0.22440], precision=[0.05326, 0.03752], hit=[0.56715, 0.67235], ndcg=[0.23991, 0.28962]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 45 [35.1s + 12.3s]: train==[659.10791=659.09308 + 0.01521], recall=[0.16457, 0.22992], precision=[0.05469, 0.03834], hit=[0.57487, 0.67899], ndcg=[0.24232, 0.29202]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 46 [36.5s + 12.6s]: train==[656.25671=656.24249 + 0.01521], recall=[0.16763, 0.23342], precision=[0.05557, 0.03909], hit=[0.57828, 0.68276], ndcg=[0.24332, 0.29389]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 47 [34.6s + 12.4s]: train==[653.22034=653.20435 + 0.01522], recall=[0.17059, 0.23650], precision=[0.05649, 0.03968], hit=[0.58330, 0.68600], ndcg=[0.24503, 0.29559]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 48 [35.1s + 12.6s]: train==[650.44855=650.43317 + 0.01522], recall=[0.17275, 0.23967], precision=[0.05724, 0.04030], hit=[0.58761, 0.68869], ndcg=[0.24579, 0.29688]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 49 [34.5s + 12.6s]: train==[647.19135=647.17554 + 0.01522], recall=[0.17471, 0.24141], precision=[0.05776, 0.04072], hit=[0.58887, 0.69138], ndcg=[0.24616, 0.29778]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 50 [35.3s + 12.8s]: train==[643.51404=643.49866 + 0.01522], recall=[0.17596, 0.24367], precision=[0.05803, 0.04112], hit=[0.59013, 0.69443], ndcg=[0.24658, 0.29898]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 51 [35.0s + 13.0s]: train==[640.15564=640.13977 + 0.01522], recall=[0.17767, 0.24448], precision=[0.05844, 0.04139], hit=[0.59318, 0.69461], ndcg=[0.24725, 0.29937]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 52 [34.7s + 12.8s]: train==[636.87988=636.86444 + 0.01522], recall=[0.17856, 0.24622], precision=[0.05864, 0.04171], hit=[0.59425, 0.69767], ndcg=[0.24725, 0.30026]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 53 [35.1s + 12.2s]: train==[632.71234=632.69745 + 0.01522], recall=[0.17918, 0.24795], precision=[0.05893, 0.04203], hit=[0.59497, 0.69856], ndcg=[0.24719, 0.30056]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 54 [35.1s + 12.9s]: train==[629.27808=629.26263 + 0.01522], recall=[0.17967, 0.24852], precision=[0.05910, 0.04219], hit=[0.59425, 0.69874], ndcg=[0.24730, 0.30078]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 55 [34.6s + 12.2s]: train==[625.71173=625.69580 + 0.01522], recall=[0.17987, 0.24928], precision=[0.05924, 0.04238], hit=[0.59461, 0.70072], ndcg=[0.24736, 0.30135]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 56 [35.6s + 13.3s]: train==[620.77252=620.75769 + 0.01522], recall=[0.18074, 0.25028], precision=[0.05937, 0.04259], hit=[0.59623, 0.70126], ndcg=[0.24758, 0.30170]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 57 [35.8s + 11.8s]: train==[617.31738=617.30182 + 0.01522], recall=[0.18083, 0.25109], precision=[0.05944, 0.04280], hit=[0.59587, 0.70108], ndcg=[0.24745, 0.30195]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 58 [36.0s + 12.8s]: train==[612.69165=612.67682 + 0.01522], recall=[0.18100, 0.25171], precision=[0.05961, 0.04302], hit=[0.59605, 0.70197], ndcg=[0.24742, 0.30226]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 59 [36.5s + 13.6s]: train==[609.10114=609.08618 + 0.01522], recall=[0.18068, 0.25250], precision=[0.05961, 0.04320], hit=[0.59623, 0.70269], ndcg=[0.24676, 0.30227]
INFO:root:Epoch 60 [35.2s + 12.4s]: train==[603.93591=603.92065 + 0.01522], recall=[0.18095, 0.25288], precision=[0.05969, 0.04333], hit=[0.59713, 0.70269], ndcg=[0.24700, 0.30251]
INFO:root:Epoch 61 [36.6s + 13.5s]: train==[600.21838=600.20288 + 0.01522], recall=[0.18104, 0.25350], precision=[0.05978, 0.04349], hit=[0.59677, 0.70269], ndcg=[0.24685, 0.30259]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 62 [35.2s + 13.5s]: train==[595.17230=595.15747 + 0.01522], recall=[0.18175, 0.25417], precision=[0.05996, 0.04362], hit=[0.59820, 0.70359], ndcg=[0.24695, 0.30280]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 63 [35.6s + 13.0s]: train==[591.63086=591.61511 + 0.01522], recall=[0.18165, 0.25489], precision=[0.05996, 0.04375], hit=[0.59820, 0.70449], ndcg=[0.24709, 0.30333]
INFO:root:Epoch 64 [36.3s + 13.1s]: train==[587.64624=587.63068 + 0.01522], recall=[0.18210, 0.25526], precision=[0.06000, 0.04386], hit=[0.59874, 0.70449], ndcg=[0.24673, 0.30311]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 65 [36.2s + 13.1s]: train==[582.34027=582.32526 + 0.01522], recall=[0.18203, 0.25551], precision=[0.06003, 0.04393], hit=[0.59803, 0.70431], ndcg=[0.24705, 0.30370]
INFO:root:Epoch 66 [35.2s + 12.5s]: train==[578.85388=578.83887 + 0.01522], recall=[0.18221, 0.25712], precision=[0.06009, 0.04413], hit=[0.59785, 0.70628], ndcg=[0.24693, 0.30421]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 67 [36.5s + 13.0s]: train==[574.13043=574.11493 + 0.01523], recall=[0.18210, 0.25730], precision=[0.06014, 0.04422], hit=[0.59749, 0.70628], ndcg=[0.24701, 0.30450]
INFO:root:Epoch 68 [35.0s + 13.6s]: train==[570.83411=570.81873 + 0.01523], recall=[0.18170, 0.25733], precision=[0.06013, 0.04426], hit=[0.59713, 0.70539], ndcg=[0.24661, 0.30420]
INFO:root:Epoch 69 [35.4s + 12.2s]: train==[566.23761=566.22314 + 0.01523], recall=[0.18191, 0.25778], precision=[0.06016, 0.04439], hit=[0.59749, 0.70610], ndcg=[0.24658, 0.30451]
INFO:root:Epoch 70 [36.0s + 12.6s]: train==[562.39252=562.37762 + 0.01523], recall=[0.18175, 0.25753], precision=[0.06013, 0.04444], hit=[0.59749, 0.70664], ndcg=[0.24626, 0.30450]
INFO:root:Epoch 71 [35.3s + 12.5s]: train==[558.49158=558.47614 + 0.01523], recall=[0.18163, 0.25803], precision=[0.06021, 0.04452], hit=[0.59731, 0.70664], ndcg=[0.24660, 0.30490]
INFO:root:Best Iter=[66]@[3450.1]	recall=[0.18221	0.25712], precision=[0.06009	0.04413], hit=[0.59785	0.70628], ndcg=[0.24693	0.30421]
INFO:root:Namespace(Ks='[20, 40]', batch_size=64, data_path='./data/recommendation/', dataset='ml-1m', embed_size=128, epoch=10000, gpu=0, item_density_threshold=0.01, item_threshold=30, layer_size=[128], lmbda=1, local_batch_size=128, local_epoch=10, log_name='run4_1', log_path='/home/qhuaf/graph_pri/logs/', lr=0.0001, mess_dropout=[0.1, 0.1, 0.1], model_name='two_side_graph.pkl', num_neighbor=30, num_process=4, pretrain_epoch=300, pri_epoch=200, privacy_protect=False, regs=[1e-05], report=0, save_flag=1, test_flag='part', user_batch_size=512, verbose=1, weights_path='model/')
INFO:root:Namespace(Ks='[10]', batch_size=64, data_path='./data/recommendation/', dataset='ml-1m', embed_size=128, epoch=10000, gpu=0, item_density_threshold=0.01, item_threshold=30, layer_size=[128], lmbda=1, local_batch_size=128, local_epoch=10, log_name='run4_1', log_path='/home/qhuaf/graph_pri/logs/', lr=0.0001, mess_dropout=[0.1, 0.1, 0.1], model_name='two_side_graph.pkl', num_neighbor=30, num_process=4, pretrain_epoch=300, pri_epoch=200, privacy_protect=False, regs=[1e-05], report=0, save_flag=1, test_flag='part', user_batch_size=512, verbose=1, weights_path='model/')
INFO:root:Namespace(Ks='[10]', batch_size=64, data_path='./data/recommendation/', dataset='ml-1m', embed_size=128, epoch=10000, gpu=0, item_density_threshold=0.01, item_threshold=30, layer_size=[128], lmbda=1, local_batch_size=128, local_epoch=10, log_name='run4_1', log_path='/home/qhuaf/graph_pri/logs/', lr=0.0001, mess_dropout=[0.1, 0.1, 0.1], model_name='two_side_graph.pkl', num_neighbor=30, num_process=4, pretrain_epoch=300, pri_epoch=200, privacy_protect=False, regs=[1e-05], report=0, save_flag=1, test_flag='part', user_batch_size=512, verbose=1, weights_path='model/')
INFO:root:Epoch 0 [675.8s + 29.5s]: train==[691.98474=691.96893 + 0.01522], recall=[0.00315, 0.00315], precision=[0.00031, 0.00031], hit=[0.00315, 0.00315], ndcg=[0.00130, 0.00130]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Namespace(Ks='[10]', batch_size=64, data_path='./data/recommendation/', dataset='ml-1m', embed_size=128, epoch=10000, gpu=0, item_density_threshold=0.01, item_threshold=30, layer_size=[128], lmbda=1, local_batch_size=128, local_epoch=10, log_name='run4_1', log_path='/home/qhuaf/graph_pri/logs/', lr=0.0001, mess_dropout=[0.1, 0.1, 0.1], model_name='two_side_graph.pkl', num_neighbor=30, num_process=4, pretrain_epoch=300, pri_epoch=200, privacy_protect=False, regs=[1e-05], report=0, save_flag=1, test_flag='part', user_batch_size=512, verbose=1, weights_path='model/')
INFO:root:Epoch 0 [44.8s + 30.6s]: train==[693.05658=693.04193 + 0.01521], recall=[0.00348, 0.00348], precision=[0.00035, 0.00035], hit=[0.00348, 0.00348], ndcg=[0.00151, 0.00151]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 1 [38.3s + 31.7s]: train==[693.00073=692.98621 + 0.01521], recall=[0.00364, 0.00364], precision=[0.00036, 0.00036], hit=[0.00364, 0.00364], ndcg=[0.00156, 0.00156]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 2 [38.5s + 31.6s]: train==[692.83502=692.82001 + 0.01521], recall=[0.00381, 0.00381], precision=[0.00038, 0.00038], hit=[0.00381, 0.00381], ndcg=[0.00162, 0.00162]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 3 [38.1s + 31.2s]: train==[692.71246=692.69690 + 0.01521], recall=[0.00381, 0.00381], precision=[0.00038, 0.00038], hit=[0.00381, 0.00381], ndcg=[0.00163, 0.00163]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 4 [38.4s + 31.1s]: train==[692.54047=692.52563 + 0.01521], recall=[0.00381, 0.00381], precision=[0.00038, 0.00038], hit=[0.00381, 0.00381], ndcg=[0.00164, 0.00164]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 5 [39.4s + 31.7s]: train==[692.44476=692.42896 + 0.01521], recall=[0.00364, 0.00364], precision=[0.00036, 0.00036], hit=[0.00364, 0.00364], ndcg=[0.00161, 0.00161]
INFO:root:Epoch 6 [38.7s + 31.1s]: train==[692.26324=692.24762 + 0.01521], recall=[0.00348, 0.00348], precision=[0.00035, 0.00035], hit=[0.00348, 0.00348], ndcg=[0.00156, 0.00156]
INFO:root:Epoch 7 [42.5s + 50.2s]: train==[692.14343=692.12921 + 0.01521], recall=[0.00364, 0.00364], precision=[0.00036, 0.00036], hit=[0.00364, 0.00364], ndcg=[0.00161, 0.00161]
INFO:root:Epoch 8 [40.5s + 32.1s]: train==[692.02686=692.01172 + 0.01521], recall=[0.00414, 0.00414], precision=[0.00041, 0.00041], hit=[0.00414, 0.00414], ndcg=[0.00180, 0.00180]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 9 [38.4s + 30.6s]: train==[691.80365=691.78918 + 0.01521], recall=[0.00431, 0.00431], precision=[0.00043, 0.00043], hit=[0.00431, 0.00431], ndcg=[0.00187, 0.00187]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 10 [38.5s + 30.5s]: train==[691.61322=691.59784 + 0.01521], recall=[0.00464, 0.00464], precision=[0.00046, 0.00046], hit=[0.00464, 0.00464], ndcg=[0.00206, 0.00206]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 11 [37.9s + 30.9s]: train==[691.45538=691.43958 + 0.01521], recall=[0.00497, 0.00497], precision=[0.00050, 0.00050], hit=[0.00497, 0.00497], ndcg=[0.00213, 0.00213]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 12 [37.9s + 30.9s]: train==[691.15460=691.13873 + 0.01521], recall=[0.00563, 0.00563], precision=[0.00056, 0.00056], hit=[0.00563, 0.00563], ndcg=[0.00235, 0.00235]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 13 [38.5s + 31.1s]: train==[690.97528=690.96027 + 0.01521], recall=[0.00580, 0.00580], precision=[0.00058, 0.00058], hit=[0.00580, 0.00580], ndcg=[0.00250, 0.00250]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 14 [38.0s + 30.9s]: train==[690.58691=690.57166 + 0.01521], recall=[0.00646, 0.00646], precision=[0.00065, 0.00065], hit=[0.00646, 0.00646], ndcg=[0.00282, 0.00282]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 15 [39.0s + 31.6s]: train==[690.23602=690.22003 + 0.01521], recall=[0.00646, 0.00646], precision=[0.00065, 0.00065], hit=[0.00646, 0.00646], ndcg=[0.00296, 0.00296]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 16 [37.6s + 31.6s]: train==[689.76971=689.75439 + 0.01521], recall=[0.00795, 0.00795], precision=[0.00079, 0.00079], hit=[0.00795, 0.00795], ndcg=[0.00353, 0.00353]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 17 [38.1s + 30.4s]: train==[689.31189=689.29694 + 0.01521], recall=[0.00861, 0.00861], precision=[0.00086, 0.00086], hit=[0.00861, 0.00861], ndcg=[0.00416, 0.00416]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 18 [38.1s + 31.5s]: train==[688.85156=688.83649 + 0.01521], recall=[0.01010, 0.01010], precision=[0.00101, 0.00101], hit=[0.01010, 0.01010], ndcg=[0.00482, 0.00482]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 19 [38.1s + 35.2s]: train==[688.30133=688.28625 + 0.01521], recall=[0.01209, 0.01209], precision=[0.00121, 0.00121], hit=[0.01209, 0.01209], ndcg=[0.00582, 0.00582]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 20 [39.4s + 31.7s]: train==[687.64691=687.63135 + 0.01521], recall=[0.01507, 0.01507], precision=[0.00151, 0.00151], hit=[0.01507, 0.01507], ndcg=[0.00716, 0.00716]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 21 [39.3s + 32.1s]: train==[686.73267=686.71790 + 0.01521], recall=[0.01672, 0.01672], precision=[0.00167, 0.00167], hit=[0.01672, 0.01672], ndcg=[0.00813, 0.00813]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 22 [39.0s + 31.8s]: train==[685.98273=685.96759 + 0.01521], recall=[0.02004, 0.02004], precision=[0.00200, 0.00200], hit=[0.02004, 0.02004], ndcg=[0.00961, 0.00961]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 23 [38.3s + 29.7s]: train==[684.91119=684.89624 + 0.01521], recall=[0.02169, 0.02169], precision=[0.00217, 0.00217], hit=[0.02169, 0.02169], ndcg=[0.01046, 0.01046]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 24 [38.0s + 29.9s]: train==[683.68433=683.66980 + 0.01521], recall=[0.02302, 0.02302], precision=[0.00230, 0.00230], hit=[0.02302, 0.02302], ndcg=[0.01134, 0.01134]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 25 [38.5s + 30.2s]: train==[682.60291=682.58850 + 0.01521], recall=[0.02534, 0.02534], precision=[0.00253, 0.00253], hit=[0.02534, 0.02534], ndcg=[0.01209, 0.01209]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 26 [38.6s + 31.1s]: train==[681.19031=681.17578 + 0.01521], recall=[0.02666, 0.02666], precision=[0.00267, 0.00267], hit=[0.02666, 0.02666], ndcg=[0.01282, 0.01282]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 27 [50.6s + 38.3s]: train==[679.62744=679.61243 + 0.01521], recall=[0.02848, 0.02848], precision=[0.00285, 0.00285], hit=[0.02848, 0.02848], ndcg=[0.01346, 0.01346]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 28 [40.8s + 36.7s]: train==[677.64764=677.63220 + 0.01521], recall=[0.02832, 0.02832], precision=[0.00283, 0.00283], hit=[0.02832, 0.02832], ndcg=[0.01372, 0.01372]
INFO:root:Epoch 29 [39.3s + 30.2s]: train==[675.63391=675.61859 + 0.01521], recall=[0.02865, 0.02865], precision=[0.00286, 0.00286], hit=[0.02865, 0.02865], ndcg=[0.01391, 0.01391]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 30 [38.9s + 31.1s]: train==[673.38037=673.36554 + 0.01521], recall=[0.02848, 0.02848], precision=[0.00285, 0.00285], hit=[0.02848, 0.02848], ndcg=[0.01407, 0.01407]
INFO:root:Epoch 31 [38.1s + 31.1s]: train==[670.91815=670.90387 + 0.01521], recall=[0.02914, 0.02914], precision=[0.00291, 0.00291], hit=[0.02914, 0.02914], ndcg=[0.01446, 0.01446]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 32 [38.1s + 31.1s]: train==[668.11658=668.10187 + 0.01521], recall=[0.02931, 0.02931], precision=[0.00293, 0.00293], hit=[0.02931, 0.02931], ndcg=[0.01448, 0.01448]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 33 [37.9s + 31.9s]: train==[665.10675=665.09088 + 0.01521], recall=[0.03163, 0.03163], precision=[0.00316, 0.00316], hit=[0.03163, 0.03163], ndcg=[0.01513, 0.01513]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 34 [38.1s + 30.6s]: train==[662.27124=662.25500 + 0.01521], recall=[0.03312, 0.03312], precision=[0.00331, 0.00331], hit=[0.03312, 0.03312], ndcg=[0.01545, 0.01545]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 35 [37.8s + 32.2s]: train==[658.58289=658.56824 + 0.01521], recall=[0.03295, 0.03295], precision=[0.00330, 0.00330], hit=[0.03295, 0.03295], ndcg=[0.01557, 0.01557]
INFO:root:Epoch 36 [38.2s + 30.4s]: train==[655.40198=655.38702 + 0.01521], recall=[0.03328, 0.03328], precision=[0.00333, 0.00333], hit=[0.03328, 0.03328], ndcg=[0.01586, 0.01586]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 37 [38.3s + 30.6s]: train==[651.38245=651.36737 + 0.01521], recall=[0.03345, 0.03345], precision=[0.00334, 0.00334], hit=[0.03345, 0.03345], ndcg=[0.01593, 0.01593]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 38 [38.5s + 31.0s]: train==[646.73792=646.72296 + 0.01520], recall=[0.03395, 0.03395], precision=[0.00339, 0.00339], hit=[0.03395, 0.03395], ndcg=[0.01619, 0.01619]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 39 [38.7s + 29.9s]: train==[643.00305=642.98816 + 0.01520], recall=[0.03444, 0.03444], precision=[0.00344, 0.00344], hit=[0.03444, 0.03444], ndcg=[0.01649, 0.01649]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 40 [37.8s + 30.2s]: train==[638.04126=638.02594 + 0.01520], recall=[0.03428, 0.03428], precision=[0.00343, 0.00343], hit=[0.03428, 0.03428], ndcg=[0.01657, 0.01657]
INFO:root:Epoch 41 [38.1s + 30.9s]: train==[633.22284=633.20825 + 0.01520], recall=[0.03461, 0.03461], precision=[0.00346, 0.00346], hit=[0.03461, 0.03461], ndcg=[0.01663, 0.01663]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 42 [38.6s + 31.7s]: train==[627.96606=627.95081 + 0.01520], recall=[0.03494, 0.03494], precision=[0.00349, 0.00349], hit=[0.03494, 0.03494], ndcg=[0.01680, 0.01680]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 43 [39.1s + 31.3s]: train==[623.20099=623.18634 + 0.01520], recall=[0.03544, 0.03544], precision=[0.00354, 0.00354], hit=[0.03544, 0.03544], ndcg=[0.01696, 0.01696]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 44 [37.9s + 36.8s]: train==[617.76697=617.75305 + 0.01520], recall=[0.03577, 0.03577], precision=[0.00358, 0.00358], hit=[0.03577, 0.03577], ndcg=[0.01709, 0.01709]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 45 [38.2s + 29.6s]: train==[612.68243=612.66669 + 0.01520], recall=[0.03544, 0.03544], precision=[0.00354, 0.00354], hit=[0.03544, 0.03544], ndcg=[0.01704, 0.01704]
INFO:root:Epoch 46 [38.9s + 30.3s]: train==[606.83350=606.81842 + 0.01520], recall=[0.03593, 0.03593], precision=[0.00359, 0.00359], hit=[0.03593, 0.03593], ndcg=[0.01719, 0.01719]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 47 [39.9s + 35.9s]: train==[601.22418=601.20868 + 0.01520], recall=[0.03560, 0.03560], precision=[0.00356, 0.00356], hit=[0.03560, 0.03560], ndcg=[0.01707, 0.01707]
INFO:root:Epoch 48 [47.2s + 39.4s]: train==[595.16089=595.14581 + 0.01520], recall=[0.03560, 0.03560], precision=[0.00356, 0.00356], hit=[0.03560, 0.03560], ndcg=[0.01697, 0.01697]
INFO:root:Epoch 49 [38.8s + 32.1s]: train==[590.67407=590.65912 + 0.01520], recall=[0.03577, 0.03577], precision=[0.00358, 0.00358], hit=[0.03577, 0.03577], ndcg=[0.01706, 0.01706]
INFO:root:Epoch 50 [38.2s + 30.7s]: train==[584.82336=584.80823 + 0.01520], recall=[0.03626, 0.03626], precision=[0.00363, 0.00363], hit=[0.03626, 0.03626], ndcg=[0.01724, 0.01724]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 51 [37.9s + 31.7s]: train==[579.13007=579.11475 + 0.01520], recall=[0.03610, 0.03610], precision=[0.00361, 0.00361], hit=[0.03610, 0.03610], ndcg=[0.01698, 0.01698]
INFO:root:Epoch 52 [39.0s + 30.0s]: train==[573.52515=573.50983 + 0.01520], recall=[0.03643, 0.03643], precision=[0.00364, 0.00364], hit=[0.03643, 0.03643], ndcg=[0.01721, 0.01721]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 53 [38.5s + 32.0s]: train==[568.95325=568.93787 + 0.01520], recall=[0.03626, 0.03626], precision=[0.00363, 0.00363], hit=[0.03626, 0.03626], ndcg=[0.01745, 0.01745]
INFO:root:Epoch 54 [38.4s + 31.8s]: train==[562.93201=562.91693 + 0.01520], recall=[0.03593, 0.03593], precision=[0.00359, 0.00359], hit=[0.03593, 0.03593], ndcg=[0.01734, 0.01734]
INFO:root:Epoch 55 [38.3s + 29.6s]: train==[557.80316=557.78827 + 0.01520], recall=[0.03660, 0.03660], precision=[0.00366, 0.00366], hit=[0.03660, 0.03660], ndcg=[0.01755, 0.01755]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 56 [38.1s + 29.7s]: train==[553.14734=553.13190 + 0.01520], recall=[0.03660, 0.03660], precision=[0.00366, 0.00366], hit=[0.03660, 0.03660], ndcg=[0.01749, 0.01749]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 57 [37.5s + 30.9s]: train==[549.19037=549.17529 + 0.01520], recall=[0.03676, 0.03676], precision=[0.00368, 0.00368], hit=[0.03676, 0.03676], ndcg=[0.01762, 0.01762]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 58 [38.0s + 31.2s]: train==[544.33447=544.31934 + 0.01520], recall=[0.03709, 0.03709], precision=[0.00371, 0.00371], hit=[0.03709, 0.03709], ndcg=[0.01767, 0.01767]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 59 [38.7s + 30.4s]: train==[539.55334=539.53864 + 0.01520], recall=[0.03726, 0.03726], precision=[0.00373, 0.00373], hit=[0.03726, 0.03726], ndcg=[0.01751, 0.01751]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 60 [38.1s + 30.3s]: train==[535.04596=535.03101 + 0.01520], recall=[0.03809, 0.03809], precision=[0.00381, 0.00381], hit=[0.03809, 0.03809], ndcg=[0.01782, 0.01782]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 61 [37.9s + 30.6s]: train==[531.54193=531.52631 + 0.01520], recall=[0.03858, 0.03858], precision=[0.00386, 0.00386], hit=[0.03858, 0.03858], ndcg=[0.01789, 0.01789]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 62 [38.9s + 30.2s]: train==[526.16809=526.15271 + 0.01520], recall=[0.03875, 0.03875], precision=[0.00387, 0.00387], hit=[0.03875, 0.03875], ndcg=[0.01788, 0.01788]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 63 [38.0s + 39.5s]: train==[523.29205=523.27692 + 0.01520], recall=[0.03809, 0.03809], precision=[0.00381, 0.00381], hit=[0.03809, 0.03809], ndcg=[0.01785, 0.01785]
INFO:root:Epoch 64 [38.7s + 30.8s]: train==[519.25604=519.24078 + 0.01520], recall=[0.03742, 0.03742], precision=[0.00374, 0.00374], hit=[0.03742, 0.03742], ndcg=[0.01755, 0.01755]
INFO:root:Epoch 65 [38.1s + 32.1s]: train==[517.35327=517.33807 + 0.01520], recall=[0.03759, 0.03759], precision=[0.00376, 0.00376], hit=[0.03759, 0.03759], ndcg=[0.01764, 0.01764]
INFO:root:Epoch 66 [38.6s + 31.2s]: train==[511.52115=511.50565 + 0.01520], recall=[0.03676, 0.03676], precision=[0.00368, 0.00368], hit=[0.03676, 0.03676], ndcg=[0.01739, 0.01739]
INFO:root:Epoch 67 [41.2s + 32.1s]: train==[508.96829=508.95251 + 0.01520], recall=[0.03709, 0.03709], precision=[0.00371, 0.00371], hit=[0.03709, 0.03709], ndcg=[0.01746, 0.01746]
INFO:root:Best Iter=[62]@[4825.1]	recall=[0.03875], precision=[0.00387], hit=[0.03875], ndcg=[0.01788]
INFO:root:Namespace(Ks='[10]', batch_size=64, data_path='./data/recommendation/', dataset='ml-1m', embed_size=128, epoch=10000, gpu=0, item_density_threshold=0.01, item_threshold=30, layer_size=[128], lmbda=1, local_batch_size=128, local_epoch=1, log_name='run4_1', log_path='/home/qhuaf/graph_pri/logs/', lr=0.0001, mess_dropout=[0.1, 0.1, 0.1], model_name='two_side_graph.pkl', num_neighbor=30, num_process=4, pretrain_epoch=300, pri_epoch=200, privacy_protect=False, regs=[1e-05], report=0, save_flag=1, test_flag='part', user_batch_size=512, verbose=1, weights_path='model/')
INFO:root:Namespace(Ks='[10]', batch_size=64, data_path='./data/recommendation/', dataset='ml-1m', embed_size=128, epoch=1000, gpu=0, item_density_threshold=0.01, item_threshold=30, layer_size=[128], lmbda=1, local_batch_size=256, local_epoch=1, log_name='run4_1', log_path='/home/qhuaf/graph_pri/logs/', lr=0.0001, mess_dropout=[0.1, 0.1, 0.1], model_name='two_side_graph.pkl', num_neighbor=30, num_process=4, pretrain_epoch=300, pri_epoch=200, privacy_protect=False, regs=[1e-05], report=0, save_flag=1, test_flag='part', user_batch_size=512, verbose=1, weights_path='model/')
INFO:root:Namespace(Ks='[10]', batch_size=64, data_path='./data/recommendation/', dataset='ml-1m', embed_size=128, epoch=1000, gpu=1, item_density_threshold=0.01, item_threshold=30, layer_size=[128], lmbda=1, local_batch_size=256, local_epoch=1, log_name='run4_1', log_path='/home/qhuaf/graph_pri/logs/', lr=0.0001, mess_dropout=[0.1, 0.1, 0.1], model_name='two_side_graph.pkl', num_neighbor=30, num_process=4, pretrain_epoch=300, pri_epoch=200, privacy_protect=False, regs=[1e-05], report=0, save_flag=1, test_flag='part', user_batch_size=512, verbose=1, weights_path='model/')
INFO:root:Namespace(Ks='[10]', batch_size=64, data_path='./data/recommendation/', dataset='ml-1m', embed_size=128, epoch=1000, gpu=1, item_density_threshold=0.01, item_threshold=30, layer_size=[128], lmbda=1, local_batch_size=256, local_epoch=1, log_name='run4_1', log_path='/home/qhuaf/graph_pri/logs/', lr=0.0001, mess_dropout=[0.1, 0.1, 0.1], model_name='two_side_graph.pkl', num_neighbor=30, num_process=4, pretrain_epoch=300, pri_epoch=200, privacy_protect=False, regs=[1e-05], report=0, save_flag=1, test_flag='part', user_batch_size=512, verbose=1, weights_path='model/')
INFO:root:Namespace(Ks='[10]', batch_size=64, data_path='./data/recommendation/', dataset='ml-1m', embed_size=128, epoch=1000, gpu=1, item_density_threshold=0.01, item_threshold=30, layer_size=[128], lmbda=1, local_batch_size=256, local_epoch=1, log_name='run4_1', log_path='/home/qhuaf/graph_pri/logs/', lr=0.0001, mess_dropout=[0.1, 0.1, 0.1], model_name='two_side_graph.pkl', num_neighbor=30, num_process=4, pretrain_epoch=300, pri_epoch=200, privacy_protect=False, regs=[1e-05], report=0, save_flag=1, test_flag='part', user_batch_size=512, verbose=1, weights_path='model/')
INFO:root:Namespace(Ks='[10]', batch_size=64, data_path='./data/recommendation/', dataset='ml-1m', embed_size=128, epoch=1000, gpu=1, item_density_threshold=0.01, item_threshold=30, layer_size=[128], lmbda=1, local_batch_size=256, local_epoch=1, log_name='run4_1', log_path='/home/qhuaf/graph_pri/logs/', lr=0.0001, mess_dropout=[0.1, 0.1, 0.1], model_name='two_side_graph.pkl', num_neighbor=30, num_process=4, pretrain_epoch=300, pri_epoch=200, privacy_protect=False, regs=[1e-05], report=0, save_flag=1, test_flag='part', user_batch_size=512, verbose=1, weights_path='model/')
INFO:root:Epoch 9 [44.8s + 29.9s]: train==[692.83496=692.81903 + 0.01583], recall=[0.21129, 0.21129], precision=[0.02113, 0.02113], hit=[0.21129, 0.21129], ndcg=[0.09765, 0.09765]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 19 [42.3s + 29.1s]: train==[692.32886=692.31287 + 0.01580], recall=[0.24590, 0.24590], precision=[0.02459, 0.02459], hit=[0.24590, 0.24590], ndcg=[0.11735, 0.11735]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 29 [45.4s + 29.9s]: train==[692.38281=692.36755 + 0.01578], recall=[0.26494, 0.26494], precision=[0.02649, 0.02649], hit=[0.26494, 0.26494], ndcg=[0.12797, 0.12797]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 39 [42.2s + 28.3s]: train==[692.44476=692.42859 + 0.01575], recall=[0.26809, 0.26809], precision=[0.02681, 0.02681], hit=[0.26809, 0.26809], ndcg=[0.13276, 0.13276]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 49 [45.7s + 32.2s]: train==[692.52374=692.50793 + 0.01573], recall=[0.26958, 0.26958], precision=[0.02696, 0.02696], hit=[0.26958, 0.26958], ndcg=[0.13239, 0.13239]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 59 [42.8s + 29.7s]: train==[692.59680=692.58124 + 0.01572], recall=[0.26097, 0.26097], precision=[0.02610, 0.02610], hit=[0.26097, 0.26097], ndcg=[0.12963, 0.12963]
INFO:root:Epoch 69 [46.3s + 27.7s]: train==[692.63446=692.61951 + 0.01571], recall=[0.26064, 0.26064], precision=[0.02606, 0.02606], hit=[0.26064, 0.26064], ndcg=[0.12786, 0.12786]
INFO:root:Epoch 79 [42.8s + 28.1s]: train==[692.66376=692.64844 + 0.01571], recall=[0.25484, 0.25484], precision=[0.02548, 0.02548], hit=[0.25484, 0.25484], ndcg=[0.12413, 0.12413]
INFO:root:Epoch 89 [46.0s + 29.2s]: train==[692.65533=692.64038 + 0.01571], recall=[0.25435, 0.25435], precision=[0.02543, 0.02543], hit=[0.25435, 0.25435], ndcg=[0.12474, 0.12474]
INFO:root:Epoch 99 [43.3s + 28.6s]: train==[692.63000=692.61377 + 0.01571], recall=[0.25700, 0.25700], precision=[0.02570, 0.02570], hit=[0.25700, 0.25700], ndcg=[0.12670, 0.12670]
INFO:root:Best Iter=[4]@[4015.9]	recall=[0.26958], precision=[0.02696], hit=[0.26958], ndcg=[0.13239]
INFO:root:Namespace(Ks='[10]', batch_size=64, data_path='./data/recommendation/', dataset='ml-1m', embed_size=128, epoch=1000, gpu=1, item_density_threshold=0.01, item_threshold=30, layer_size=[128], lmbda=1, local_batch_size=256, local_epoch=1, log_name='run4_1', log_path='/home/qhuaf/graph_pri/logs/', lr=0.0001, mess_dropout=[0.1, 0.1, 0.1], model_name='two_side_graph.pkl', num_neighbor=30, num_process=4, pretrain_epoch=300, pri_epoch=200, privacy_protect=False, regs=[1e-05], report=0, save_flag=1, test_flag='part', user_batch_size=512, verbose=1, weights_path='model/')
INFO:root:Epoch 9 [41.0s + 29.6s]: train==[692.96063=692.94519 + 0.01583], recall=[0.20136, 0.20136], precision=[0.02014, 0.02014], hit=[0.20136, 0.20136], ndcg=[0.09303, 0.09303]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 19 [40.5s + 30.8s]: train==[692.21899=692.20349 + 0.01580], recall=[0.25551, 0.25551], precision=[0.02555, 0.02555], hit=[0.25551, 0.25551], ndcg=[0.11859, 0.11859]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 29 [42.0s + 28.0s]: train==[692.28137=692.26526 + 0.01577], recall=[0.27422, 0.27422], precision=[0.02742, 0.02742], hit=[0.27422, 0.27422], ndcg=[0.13403, 0.13403]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 39 [40.4s + 29.7s]: train==[692.31818=692.30231 + 0.01575], recall=[0.28664, 0.28664], precision=[0.02866, 0.02866], hit=[0.28664, 0.28664], ndcg=[0.14419, 0.14419]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 49 [40.2s + 28.4s]: train==[692.42004=692.40381 + 0.01573], recall=[0.28167, 0.28167], precision=[0.02817, 0.02817], hit=[0.28167, 0.28167], ndcg=[0.14093, 0.14093]
INFO:root:Epoch 59 [40.8s + 31.0s]: train==[692.52997=692.51398 + 0.01572], recall=[0.27356, 0.27356], precision=[0.02736, 0.02736], hit=[0.27356, 0.27356], ndcg=[0.13653, 0.13653]
INFO:root:Epoch 69 [40.3s + 30.3s]: train==[692.60175=692.58521 + 0.01571], recall=[0.26196, 0.26196], precision=[0.02620, 0.02620], hit=[0.26196, 0.26196], ndcg=[0.13030, 0.13030]
INFO:root:Epoch 79 [41.6s + 29.6s]: train==[692.64233=692.62604 + 0.01570], recall=[0.26180, 0.26180], precision=[0.02618, 0.02618], hit=[0.26180, 0.26180], ndcg=[0.12813, 0.12813]
INFO:root:Epoch 89 [41.4s + 29.8s]: train==[692.62140=692.60486 + 0.01570], recall=[0.25501, 0.25501], precision=[0.02550, 0.02550], hit=[0.25501, 0.25501], ndcg=[0.12700, 0.12700]
INFO:root:Epoch 99 [41.1s + 28.5s]: train==[692.60382=692.58826 + 0.01571], recall=[0.26047, 0.26047], precision=[0.02605, 0.02605], hit=[0.26047, 0.26047], ndcg=[0.12816, 0.12816]
INFO:root:Epoch 109 [41.3s + 29.5s]: train==[692.53522=692.52002 + 0.01571], recall=[0.26213, 0.26213], precision=[0.02621, 0.02621], hit=[0.26213, 0.26213], ndcg=[0.13108, 0.13108]
INFO:root:Epoch 119 [46.2s + 34.3s]: train==[692.46069=692.44446 + 0.01572], recall=[0.27256, 0.27256], precision=[0.02726, 0.02726], hit=[0.27256, 0.27256], ndcg=[0.13781, 0.13781]
INFO:root:Epoch 129 [43.9s + 29.1s]: train==[692.29474=692.27972 + 0.01574], recall=[0.28746, 0.28746], precision=[0.02875, 0.02875], hit=[0.28746, 0.28746], ndcg=[0.14708, 0.14708]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 139 [43.6s + 28.7s]: train==[692.11517=692.10046 + 0.01576], recall=[0.30286, 0.30286], precision=[0.03029, 0.03029], hit=[0.30286, 0.30286], ndcg=[0.15691, 0.15691]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 149 [44.4s + 30.4s]: train==[691.93079=691.91528 + 0.01578], recall=[0.32721, 0.32721], precision=[0.03272, 0.03272], hit=[0.32721, 0.32721], ndcg=[0.17329, 0.17329]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 159 [44.9s + 30.4s]: train==[691.62634=691.60980 + 0.01581], recall=[0.35966, 0.35966], precision=[0.03597, 0.03597], hit=[0.35966, 0.35966], ndcg=[0.19471, 0.19471]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 169 [43.1s + 29.8s]: train==[691.26587=691.24945 + 0.01586], recall=[0.38732, 0.38732], precision=[0.03873, 0.03873], hit=[0.38732, 0.38732], ndcg=[0.21552, 0.21552]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 179 [44.8s + 31.7s]: train==[690.86530=690.85022 + 0.01590], recall=[0.41894, 0.41894], precision=[0.04189, 0.04189], hit=[0.41894, 0.41894], ndcg=[0.23748, 0.23748]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 189 [44.4s + 31.6s]: train==[690.31195=690.29614 + 0.01597], recall=[0.45388, 0.45388], precision=[0.04539, 0.04539], hit=[0.45388, 0.45388], ndcg=[0.26191, 0.26191]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 199 [46.5s + 32.2s]: train==[689.71387=689.69794 + 0.01604], recall=[0.48352, 0.48352], precision=[0.04835, 0.04835], hit=[0.48352, 0.48352], ndcg=[0.28210, 0.28210]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 209 [45.4s + 31.4s]: train==[689.02710=689.01202 + 0.01613], recall=[0.51051, 0.51051], precision=[0.05105, 0.05105], hit=[0.51051, 0.51051], ndcg=[0.30106, 0.30106]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 219 [46.3s + 31.4s]: train==[688.24683=688.23126 + 0.01623], recall=[0.53933, 0.53933], precision=[0.05393, 0.05393], hit=[0.53933, 0.53933], ndcg=[0.31822, 0.31822]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 229 [46.5s + 32.9s]: train==[687.34540=687.32977 + 0.01635], recall=[0.55804, 0.55804], precision=[0.05580, 0.05580], hit=[0.55804, 0.55804], ndcg=[0.32850, 0.32850]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 239 [45.9s + 32.1s]: train==[686.21527=686.19873 + 0.01649], recall=[0.57824, 0.57824], precision=[0.05782, 0.05782], hit=[0.57824, 0.57824], ndcg=[0.34365, 0.34365]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 249 [45.2s + 32.1s]: train==[685.11151=685.09351 + 0.01665], recall=[0.58967, 0.58967], precision=[0.05897, 0.05897], hit=[0.58967, 0.58967], ndcg=[0.34635, 0.34635]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 259 [44.9s + 32.1s]: train==[683.86359=683.84686 + 0.01683], recall=[0.60440, 0.60440], precision=[0.06044, 0.06044], hit=[0.60440, 0.60440], ndcg=[0.35348, 0.35348]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 269 [44.0s + 32.9s]: train==[682.46075=682.44342 + 0.01703], recall=[0.61566, 0.61566], precision=[0.06157, 0.06157], hit=[0.61566, 0.61566], ndcg=[0.35930, 0.35930]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 279 [43.9s + 33.0s]: train==[680.71045=680.69281 + 0.01726], recall=[0.61997, 0.61997], precision=[0.06200, 0.06200], hit=[0.61997, 0.61997], ndcg=[0.36273, 0.36273]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 289 [46.5s + 33.8s]: train==[678.95648=678.93896 + 0.01751], recall=[0.62676, 0.62676], precision=[0.06268, 0.06268], hit=[0.62676, 0.62676], ndcg=[0.36188, 0.36188]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 299 [47.1s + 35.4s]: train==[676.94507=676.92737 + 0.01778], recall=[0.62891, 0.62891], precision=[0.06289, 0.06289], hit=[0.62891, 0.62891], ndcg=[0.36773, 0.36773]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 309 [43.8s + 33.0s]: train==[674.89917=674.88074 + 0.01807], recall=[0.63703, 0.63703], precision=[0.06370, 0.06370], hit=[0.63703, 0.63703], ndcg=[0.36909, 0.36909]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 319 [45.9s + 31.3s]: train==[672.63055=672.61218 + 0.01840], recall=[0.64431, 0.64431], precision=[0.06443, 0.06443], hit=[0.64431, 0.64431], ndcg=[0.37310, 0.37310]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 329 [46.4s + 31.7s]: train==[670.31494=670.29553 + 0.01874], recall=[0.63951, 0.63951], precision=[0.06395, 0.06395], hit=[0.63951, 0.63951], ndcg=[0.37221, 0.37221]
INFO:root:Epoch 339 [45.7s + 32.0s]: train==[667.75818=667.73999 + 0.01911], recall=[0.64597, 0.64597], precision=[0.06460, 0.06460], hit=[0.64597, 0.64597], ndcg=[0.37385, 0.37385]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 349 [45.1s + 31.4s]: train==[665.61292=665.59326 + 0.01952], recall=[0.64911, 0.64911], precision=[0.06491, 0.06491], hit=[0.64911, 0.64911], ndcg=[0.37310, 0.37310]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 359 [43.9s + 31.6s]: train==[663.02576=663.00555 + 0.01993], recall=[0.64829, 0.64829], precision=[0.06483, 0.06483], hit=[0.64829, 0.64829], ndcg=[0.37556, 0.37556]
INFO:root:Epoch 369 [44.9s + 31.9s]: train==[660.36542=660.34552 + 0.02037], recall=[0.64978, 0.64978], precision=[0.06498, 0.06498], hit=[0.64978, 0.64978], ndcg=[0.37680, 0.37680]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 379 [44.2s + 32.1s]: train==[657.69055=657.66925 + 0.02086], recall=[0.64978, 0.64978], precision=[0.06498, 0.06498], hit=[0.64978, 0.64978], ndcg=[0.37735, 0.37735]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 389 [44.5s + 31.8s]: train==[655.28870=655.26709 + 0.02134], recall=[0.64762, 0.64762], precision=[0.06476, 0.06476], hit=[0.64762, 0.64762], ndcg=[0.37711, 0.37711]
INFO:root:Epoch 399 [45.1s + 31.9s]: train==[653.15234=653.13104 + 0.02188], recall=[0.64928, 0.64928], precision=[0.06493, 0.06493], hit=[0.64928, 0.64928], ndcg=[0.37756, 0.37756]
INFO:root:Epoch 409 [46.0s + 33.7s]: train==[650.15564=650.13403 + 0.02242], recall=[0.64464, 0.64464], precision=[0.06446, 0.06446], hit=[0.64464, 0.64464], ndcg=[0.37502, 0.37502]
INFO:root:Epoch 419 [46.2s + 31.9s]: train==[646.84802=646.82520 + 0.02299], recall=[0.65243, 0.65243], precision=[0.06524, 0.06524], hit=[0.65243, 0.65243], ndcg=[0.37671, 0.37671]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 429 [41.6s + 30.8s]: train==[643.90497=643.88165 + 0.02359], recall=[0.65060, 0.65060], precision=[0.06506, 0.06506], hit=[0.65060, 0.65060], ndcg=[0.37675, 0.37675]
INFO:root:Epoch 439 [42.3s + 30.1s]: train==[641.17163=641.14771 + 0.02422], recall=[0.65027, 0.65027], precision=[0.06503, 0.06503], hit=[0.65027, 0.65027], ndcg=[0.37912, 0.37912]
INFO:root:Epoch 449 [45.0s + 30.6s]: train==[638.06329=638.03796 + 0.02488], recall=[0.65193, 0.65193], precision=[0.06519, 0.06519], hit=[0.65193, 0.65193], ndcg=[0.37937, 0.37937]
INFO:root:Epoch 459 [43.0s + 29.5s]: train==[635.64343=635.61884 + 0.02555], recall=[0.65557, 0.65557], precision=[0.06556, 0.06556], hit=[0.65557, 0.65557], ndcg=[0.37825, 0.37825]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 469 [46.5s + 31.6s]: train==[631.99078=631.96484 + 0.02624], recall=[0.65590, 0.65590], precision=[0.06559, 0.06559], hit=[0.65590, 0.65590], ndcg=[0.37690, 0.37690]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 479 [42.9s + 30.1s]: train==[627.82123=627.79456 + 0.02697], recall=[0.65524, 0.65524], precision=[0.06552, 0.06552], hit=[0.65524, 0.65524], ndcg=[0.38098, 0.38098]
INFO:root:Epoch 489 [42.6s + 29.5s]: train==[624.56268=624.53503 + 0.02770], recall=[0.65723, 0.65723], precision=[0.06572, 0.06572], hit=[0.65723, 0.65723], ndcg=[0.37924, 0.37924]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 499 [41.9s + 31.1s]: train==[622.05682=622.02875 + 0.02848], recall=[0.65425, 0.65425], precision=[0.06542, 0.06542], hit=[0.65425, 0.65425], ndcg=[0.37656, 0.37656]
INFO:root:Epoch 509 [42.8s + 30.5s]: train==[618.28400=618.25427 + 0.02926], recall=[0.65441, 0.65441], precision=[0.06544, 0.06544], hit=[0.65441, 0.65441], ndcg=[0.37824, 0.37824]
INFO:root:Epoch 519 [41.1s + 30.8s]: train==[614.88916=614.85907 + 0.03008], recall=[0.65623, 0.65623], precision=[0.06562, 0.06562], hit=[0.65623, 0.65623], ndcg=[0.38189, 0.38189]
INFO:root:Epoch 529 [44.8s + 31.3s]: train==[610.57819=610.54700 + 0.03092], recall=[0.66087, 0.66087], precision=[0.06609, 0.06609], hit=[0.66087, 0.66087], ndcg=[0.38050, 0.38050]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 539 [42.8s + 30.7s]: train==[607.08716=607.05511 + 0.03180], recall=[0.65955, 0.65955], precision=[0.06595, 0.06595], hit=[0.65955, 0.65955], ndcg=[0.37922, 0.37922]
INFO:root:Epoch 549 [42.1s + 30.0s]: train==[603.35016=603.31732 + 0.03269], recall=[0.65822, 0.65822], precision=[0.06582, 0.06582], hit=[0.65822, 0.65822], ndcg=[0.38139, 0.38139]
INFO:root:Epoch 559 [42.3s + 28.6s]: train==[600.25336=600.21960 + 0.03362], recall=[0.65309, 0.65309], precision=[0.06531, 0.06531], hit=[0.65309, 0.65309], ndcg=[0.38157, 0.38157]
INFO:root:Epoch 569 [42.0s + 30.2s]: train==[595.80505=595.77026 + 0.03458], recall=[0.66087, 0.66087], precision=[0.06609, 0.06609], hit=[0.66087, 0.66087], ndcg=[0.38156, 0.38156]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 579 [45.4s + 30.5s]: train==[593.02789=592.99249 + 0.03556], recall=[0.65392, 0.65392], precision=[0.06539, 0.06539], hit=[0.65392, 0.65392], ndcg=[0.37911, 0.37911]
INFO:root:Epoch 589 [42.6s + 30.7s]: train==[589.41010=589.37347 + 0.03654], recall=[0.65756, 0.65756], precision=[0.06576, 0.06576], hit=[0.65756, 0.65756], ndcg=[0.38061, 0.38061]
INFO:root:Epoch 599 [45.4s + 28.2s]: train==[585.31903=585.28198 + 0.03753], recall=[0.65839, 0.65839], precision=[0.06584, 0.06584], hit=[0.65839, 0.65839], ndcg=[0.38124, 0.38124]
INFO:root:Epoch 609 [43.5s + 30.8s]: train==[580.87646=580.83777 + 0.03859], recall=[0.65508, 0.65508], precision=[0.06551, 0.06551], hit=[0.65508, 0.65508], ndcg=[0.37765, 0.37765]
INFO:root:Epoch 619 [41.7s + 30.7s]: train==[578.19061=578.15082 + 0.03965], recall=[0.65623, 0.65623], precision=[0.06562, 0.06562], hit=[0.65623, 0.65623], ndcg=[0.38244, 0.38244]
INFO:root:Epoch 629 [41.1s + 29.2s]: train==[573.69055=573.64954 + 0.04073], recall=[0.66269, 0.66269], precision=[0.06627, 0.06627], hit=[0.66269, 0.66269], ndcg=[0.38270, 0.38270]
INFO:root:save the weights in path: model/two_side_graph.pkl
INFO:root:Epoch 639 [42.2s + 30.1s]: train==[570.70807=570.66595 + 0.04189], recall=[0.65623, 0.65623], precision=[0.06562, 0.06562], hit=[0.65623, 0.65623], ndcg=[0.37983, 0.37983]
INFO:root:Epoch 649 [43.2s + 30.5s]: train==[567.01141=566.96844 + 0.04302], recall=[0.65988, 0.65988], precision=[0.06599, 0.06599], hit=[0.65988, 0.65988], ndcg=[0.38173, 0.38173]
INFO:root:Epoch 659 [41.7s + 30.0s]: train==[561.80640=561.76239 + 0.04416], recall=[0.65723, 0.65723], precision=[0.06572, 0.06572], hit=[0.65723, 0.65723], ndcg=[0.38007, 0.38007]
INFO:root:Epoch 669 [42.1s + 32.3s]: train==[557.91290=557.86713 + 0.04535], recall=[0.65408, 0.65408], precision=[0.06541, 0.06541], hit=[0.65408, 0.65408], ndcg=[0.37931, 0.37931]
INFO:root:Epoch 679 [43.7s + 31.5s]: train==[554.92188=554.87555 + 0.04658], recall=[0.65276, 0.65276], precision=[0.06528, 0.06528], hit=[0.65276, 0.65276], ndcg=[0.37994, 0.37994]
INFO:root:Epoch 689 [43.4s + 30.9s]: train==[550.53284=550.48499 + 0.04779], recall=[0.65839, 0.65839], precision=[0.06584, 0.06584], hit=[0.65839, 0.65839], ndcg=[0.38010, 0.38010]
INFO:root:Epoch 699 [42.7s + 30.7s]: train==[547.77917=547.73077 + 0.04905], recall=[0.65690, 0.65690], precision=[0.06569, 0.06569], hit=[0.65690, 0.65690], ndcg=[0.38048, 0.38048]
INFO:root:Epoch 709 [46.9s + 32.8s]: train==[544.86804=544.81750 + 0.05037], recall=[0.65607, 0.65607], precision=[0.06561, 0.06561], hit=[0.65607, 0.65607], ndcg=[0.37919, 0.37919]
INFO:root:Epoch 719 [41.3s + 29.0s]: train==[539.77783=539.72620 + 0.05158], recall=[0.65806, 0.65806], precision=[0.06581, 0.06581], hit=[0.65806, 0.65806], ndcg=[0.37994, 0.37994]
INFO:root:Epoch 729 [43.6s + 31.3s]: train==[537.16064=537.10712 + 0.05299], recall=[0.65806, 0.65806], precision=[0.06581, 0.06581], hit=[0.65806, 0.65806], ndcg=[0.37560, 0.37560]
INFO:root:Best Iter=[62]@[29857.1]	recall=[0.66269], precision=[0.06627], hit=[0.66269], ndcg=[0.38270]
INFO:root:Namespace(Ks='[10]', batch_size=64, data_path='./data/recommendation/', dataset='ml-1m', embed_size=128, epoch=2000, gpu=2, item_density_threshold=0.01, item_threshold=30, layer_size=[128], lmbda=1, local_batch_size=256, local_epoch=1, log_name='run4_1', log_path='/home/qhuaf/graph_pri/logs/', lr=0.0001, mess_dropout=[0.1, 0.1, 0.1], model_name='two_side_graph_run4_1.pkl', num_neighbor=30, num_process=4, pretrain_epoch=300, pri_epoch=200, privacy_protect=False, regs=[1e-05], report=0, save_flag=1, test_flag='part', user_batch_size=512, verbose=1, weights_path='model/')
INFO:root:Namespace(Ks='[10]', batch_size=64, data_path='./data/recommendation/', dataset='ml-1m', embed_size=128, epoch=2000, gpu=2, item_density_threshold=0.01, item_threshold=30, layer_size=[128], lmbda=1, local_batch_size=256, local_epoch=1, log_name='run4_1', log_path='/home/qhuaf/graph_pri/logs/', lr=0.0001, mess_dropout=[0.1, 0.1, 0.1], model_name='two_side_graph_run4_1.pkl', num_neighbor=30, num_process=4, pretrain_epoch=300, pri_epoch=200, privacy_protect=False, regs=[1e-05], report=0, save_flag=1, test_flag='part', user_batch_size=512, verbose=1, weights_path='model/')
INFO:root:Namespace(Ks='[10]', batch_size=64, data_path='./data/recommendation/', dataset='ml-1m', embed_size=128, epoch=2000, gpu=2, item_density_threshold=0.01, item_threshold=30, layer_size=[128], lmbda=1, local_batch_size=256, local_epoch=1, log_name='run4_1', log_path='/home/qhuaf/graph_pri/logs/', lr=0.0001, mess_dropout=[0.1, 0.1, 0.1], model_name='two_side_graph_run4_1.pkl', num_neighbor=30, num_process=4, pretrain_epoch=300, pri_epoch=200, privacy_protect=False, regs=[1e-05], report=0, save_flag=1, test_flag='part', user_batch_size=512, verbose=1, weights_path='model/')
INFO:root:Epoch 9 [15.2s + 33.8s]: train==[692.87769=692.86194 + 0.01583], recall=[0.21258, 0.21258], precision=[0.02126, 0.02126], hit=[0.21258, 0.21258], ndcg=[0.09727, 0.09727]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 19 [14.5s + 33.3s]: train==[692.58710=692.57153 + 0.01583], recall=[0.21556, 0.21556], precision=[0.02156, 0.02156], hit=[0.21556, 0.21556], ndcg=[0.09896, 0.09896]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 29 [15.9s + 32.6s]: train==[692.11774=692.10199 + 0.01584], recall=[0.22368, 0.22368], precision=[0.02237, 0.02237], hit=[0.22368, 0.22368], ndcg=[0.10166, 0.10166]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Namespace(Ks='[10]', batch_size=64, data_path='./data/recommendation/', dataset='ml-1m', embed_size=128, epoch=2000, gpu=2, item_density_threshold=0.01, item_threshold=30, layer_size=[128], lmbda=1, local_batch_size=256, local_epoch=1, log_name='run4_1', log_path='/home/qhuaf/graph_pri/logs/', lr=0.0001, mess_dropout=[0.1, 0.1, 0.1], model_name='two_side_graph_run4_1.pkl', num_neighbor=30, num_process=4, pretrain_epoch=300, pri_epoch=200, privacy_protect=False, regs=[1e-05], report=0, save_flag=1, test_flag='part', user_batch_size=512, verbose=1, weights_path='model/')
INFO:root:Epoch 9 [44.2s + 31.8s]: train==[692.91248=692.89722 + 0.01582], recall=[0.20480, 0.20480], precision=[0.02048, 0.02048], hit=[0.20480, 0.20480], ndcg=[0.09516, 0.09516]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 19 [43.9s + 32.3s]: train==[692.22699=692.21155 + 0.01580], recall=[0.24238, 0.24238], precision=[0.02424, 0.02424], hit=[0.24238, 0.24238], ndcg=[0.11442, 0.11442]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 29 [43.7s + 31.4s]: train==[692.24927=692.23328 + 0.01577], recall=[0.26921, 0.26921], precision=[0.02692, 0.02692], hit=[0.26921, 0.26921], ndcg=[0.12856, 0.12856]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 39 [44.6s + 31.4s]: train==[692.29883=692.28265 + 0.01574], recall=[0.28311, 0.28311], precision=[0.02831, 0.02831], hit=[0.28311, 0.28311], ndcg=[0.13939, 0.13939]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 49 [45.1s + 31.3s]: train==[692.44373=692.42725 + 0.01572], recall=[0.27848, 0.27848], precision=[0.02785, 0.02785], hit=[0.27848, 0.27848], ndcg=[0.13902, 0.13902]
INFO:root:Epoch 59 [42.9s + 31.4s]: train==[692.51917=692.50427 + 0.01571], recall=[0.26970, 0.26970], precision=[0.02697, 0.02697], hit=[0.26970, 0.26970], ndcg=[0.13356, 0.13356]
INFO:root:Epoch 69 [44.4s + 31.6s]: train==[692.60382=692.58838 + 0.01570], recall=[0.26556, 0.26556], precision=[0.02656, 0.02656], hit=[0.26556, 0.26556], ndcg=[0.12896, 0.12896]
INFO:root:Epoch 79 [43.9s + 31.6s]: train==[692.64368=692.62769 + 0.01570], recall=[0.25844, 0.25844], precision=[0.02584, 0.02584], hit=[0.25844, 0.25844], ndcg=[0.12600, 0.12600]
INFO:root:Epoch 89 [44.0s + 31.4s]: train==[692.67950=692.66425 + 0.01570], recall=[0.25811, 0.25811], precision=[0.02581, 0.02581], hit=[0.25811, 0.25811], ndcg=[0.12377, 0.12377]
INFO:root:Epoch 99 [45.5s + 32.0s]: train==[692.66772=692.65179 + 0.01570], recall=[0.25911, 0.25911], precision=[0.02591, 0.02591], hit=[0.25911, 0.25911], ndcg=[0.12718, 0.12718]
INFO:root:Epoch 109 [44.6s + 32.4s]: train==[692.60712=692.59210 + 0.01570], recall=[0.26358, 0.26358], precision=[0.02636, 0.02636], hit=[0.26358, 0.26358], ndcg=[0.12850, 0.12850]
INFO:root:Epoch 119 [44.6s + 30.4s]: train==[692.52252=692.50629 + 0.01571], recall=[0.27533, 0.27533], precision=[0.02753, 0.02753], hit=[0.27533, 0.27533], ndcg=[0.13601, 0.13601]
INFO:root:Epoch 129 [41.8s + 30.0s]: train==[692.40900=692.39264 + 0.01572], recall=[0.28940, 0.28940], precision=[0.02894, 0.02894], hit=[0.28940, 0.28940], ndcg=[0.14536, 0.14536]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 139 [41.8s + 28.5s]: train==[692.25653=692.24152 + 0.01574], recall=[0.30480, 0.30480], precision=[0.03048, 0.03048], hit=[0.30480, 0.30480], ndcg=[0.15650, 0.15650]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 149 [41.5s + 30.7s]: train==[692.07220=692.05676 + 0.01576], recall=[0.32103, 0.32103], precision=[0.03210, 0.03210], hit=[0.32103, 0.32103], ndcg=[0.16808, 0.16808]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 159 [42.0s + 31.1s]: train==[691.81604=691.80096 + 0.01579], recall=[0.35480, 0.35480], precision=[0.03548, 0.03548], hit=[0.35480, 0.35480], ndcg=[0.18660, 0.18660]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 169 [42.2s + 27.7s]: train==[691.55701=691.54065 + 0.01582], recall=[0.38129, 0.38129], precision=[0.03813, 0.03813], hit=[0.38129, 0.38129], ndcg=[0.20905, 0.20905]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 179 [41.5s + 29.6s]: train==[691.16705=691.15009 + 0.01587], recall=[0.40894, 0.40894], precision=[0.04089, 0.04089], hit=[0.40894, 0.40894], ndcg=[0.22904, 0.22904]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 189 [42.2s + 31.5s]: train==[690.74988=690.73438 + 0.01592], recall=[0.44123, 0.44123], precision=[0.04412, 0.04412], hit=[0.44123, 0.44123], ndcg=[0.25160, 0.25160]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 199 [42.1s + 29.6s]: train==[690.24188=690.22552 + 0.01599], recall=[0.47351, 0.47351], precision=[0.04735, 0.04735], hit=[0.47351, 0.47351], ndcg=[0.27637, 0.27637]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 209 [41.2s + 29.5s]: train==[689.71033=689.69440 + 0.01606], recall=[0.49619, 0.49619], precision=[0.04962, 0.04962], hit=[0.49619, 0.49619], ndcg=[0.28946, 0.28946]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 219 [41.8s + 30.2s]: train==[689.00684=688.99109 + 0.01615], recall=[0.52517, 0.52517], precision=[0.05252, 0.05252], hit=[0.52517, 0.52517], ndcg=[0.31115, 0.31115]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 229 [42.8s + 28.7s]: train==[688.26697=688.25018 + 0.01626], recall=[0.54603, 0.54603], precision=[0.05460, 0.05460], hit=[0.54603, 0.54603], ndcg=[0.32079, 0.32079]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 239 [42.4s + 29.3s]: train==[687.39764=687.38123 + 0.01639], recall=[0.56192, 0.56192], precision=[0.05619, 0.05619], hit=[0.56192, 0.56192], ndcg=[0.33090, 0.33090]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 249 [42.0s + 29.5s]: train==[686.44806=686.43176 + 0.01653], recall=[0.58195, 0.58195], precision=[0.05820, 0.05820], hit=[0.58195, 0.58195], ndcg=[0.34351, 0.34351]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 259 [42.9s + 31.7s]: train==[685.34503=685.32776 + 0.01669], recall=[0.59387, 0.59387], precision=[0.05939, 0.05939], hit=[0.59387, 0.59387], ndcg=[0.35017, 0.35017]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 269 [42.5s + 28.5s]: train==[684.08185=684.06494 + 0.01687], recall=[0.60298, 0.60298], precision=[0.06030, 0.06030], hit=[0.60298, 0.60298], ndcg=[0.35455, 0.35455]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 279 [41.7s + 30.2s]: train==[682.80872=682.79175 + 0.01708], recall=[0.60911, 0.60911], precision=[0.06091, 0.06091], hit=[0.60911, 0.60911], ndcg=[0.35614, 0.35614]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 289 [42.0s + 30.2s]: train==[681.42029=681.40326 + 0.01731], recall=[0.61970, 0.61970], precision=[0.06197, 0.06197], hit=[0.61970, 0.61970], ndcg=[0.36419, 0.36419]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 299 [42.8s + 29.5s]: train==[679.80811=679.78955 + 0.01756], recall=[0.62368, 0.62368], precision=[0.06237, 0.06237], hit=[0.62368, 0.62368], ndcg=[0.36268, 0.36268]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 309 [48.4s + 55.1s]: train==[678.20587=678.18829 + 0.01783], recall=[0.63113, 0.63113], precision=[0.06311, 0.06311], hit=[0.63113, 0.63113], ndcg=[0.37046, 0.37046]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 319 [46.1s + 46.2s]: train==[676.32446=676.30609 + 0.01812], recall=[0.63493, 0.63493], precision=[0.06349, 0.06349], hit=[0.63493, 0.63493], ndcg=[0.37144, 0.37144]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 329 [42.2s + 31.8s]: train==[674.46460=674.44678 + 0.01845], recall=[0.64139, 0.64139], precision=[0.06414, 0.06414], hit=[0.64139, 0.64139], ndcg=[0.37510, 0.37510]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 339 [41.5s + 30.3s]: train==[672.44617=672.42755 + 0.01879], recall=[0.64901, 0.64901], precision=[0.06490, 0.06490], hit=[0.64901, 0.64901], ndcg=[0.37553, 0.37553]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 349 [42.8s + 31.2s]: train==[670.10974=670.09076 + 0.01916], recall=[0.64007, 0.64007], precision=[0.06401, 0.06401], hit=[0.64007, 0.64007], ndcg=[0.37593, 0.37593]
INFO:root:Epoch 359 [41.0s + 30.7s]: train==[667.86572=667.84631 + 0.01956], recall=[0.64603, 0.64603], precision=[0.06460, 0.06460], hit=[0.64603, 0.64603], ndcg=[0.37790, 0.37790]
INFO:root:Epoch 369 [41.6s + 31.6s]: train==[665.40112=665.38190 + 0.01998], recall=[0.64851, 0.64851], precision=[0.06485, 0.06485], hit=[0.64851, 0.64851], ndcg=[0.37944, 0.37944]
INFO:root:Epoch 379 [41.3s + 29.9s]: train==[662.45984=662.43915 + 0.02042], recall=[0.65017, 0.65017], precision=[0.06502, 0.06502], hit=[0.65017, 0.65017], ndcg=[0.37819, 0.37819]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 389 [41.2s + 28.3s]: train==[659.72137=659.70044 + 0.02089], recall=[0.65083, 0.65083], precision=[0.06508, 0.06508], hit=[0.65083, 0.65083], ndcg=[0.37648, 0.37648]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 399 [42.4s + 28.2s]: train==[657.26843=657.24695 + 0.02139], recall=[0.65579, 0.65579], precision=[0.06558, 0.06558], hit=[0.65579, 0.65579], ndcg=[0.37896, 0.37896]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 409 [41.7s + 29.5s]: train==[654.13641=654.11523 + 0.02191], recall=[0.65149, 0.65149], precision=[0.06515, 0.06515], hit=[0.65149, 0.65149], ndcg=[0.37753, 0.37753]
INFO:root:Epoch 419 [41.5s + 29.0s]: train==[651.70245=651.68054 + 0.02245], recall=[0.64967, 0.64967], precision=[0.06497, 0.06497], hit=[0.64967, 0.64967], ndcg=[0.37861, 0.37861]
INFO:root:Epoch 429 [42.1s + 29.2s]: train==[647.88916=647.86676 + 0.02301], recall=[0.65199, 0.65199], precision=[0.06520, 0.06520], hit=[0.65199, 0.65199], ndcg=[0.37901, 0.37901]
INFO:root:Epoch 439 [40.9s + 31.6s]: train==[645.84485=645.82202 + 0.02361], recall=[0.65530, 0.65530], precision=[0.06553, 0.06553], hit=[0.65530, 0.65530], ndcg=[0.37966, 0.37966]
INFO:root:Epoch 449 [41.7s + 29.0s]: train==[642.87695=642.85229 + 0.02423], recall=[0.65579, 0.65579], precision=[0.06558, 0.06558], hit=[0.65579, 0.65579], ndcg=[0.37979, 0.37979]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 459 [40.9s + 28.8s]: train==[639.60132=639.57672 + 0.02488], recall=[0.65811, 0.65811], precision=[0.06581, 0.06581], hit=[0.65811, 0.65811], ndcg=[0.37973, 0.37973]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 469 [41.2s + 31.1s]: train==[636.42609=636.40045 + 0.02555], recall=[0.65877, 0.65877], precision=[0.06588, 0.06588], hit=[0.65877, 0.65877], ndcg=[0.38069, 0.38069]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 479 [40.2s + 30.6s]: train==[633.18616=633.15948 + 0.02623], recall=[0.65944, 0.65944], precision=[0.06594, 0.06594], hit=[0.65944, 0.65944], ndcg=[0.37918, 0.37918]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 489 [40.3s + 29.5s]: train==[629.68671=629.65894 + 0.02695], recall=[0.65646, 0.65646], precision=[0.06565, 0.06565], hit=[0.65646, 0.65646], ndcg=[0.38154, 0.38154]
INFO:root:Epoch 499 [41.3s + 28.3s]: train==[627.15167=627.12384 + 0.02770], recall=[0.65596, 0.65596], precision=[0.06560, 0.06560], hit=[0.65596, 0.65596], ndcg=[0.38015, 0.38015]
INFO:root:Epoch 509 [41.3s + 29.4s]: train==[623.69061=623.66125 + 0.02844], recall=[0.65397, 0.65397], precision=[0.06540, 0.06540], hit=[0.65397, 0.65397], ndcg=[0.38160, 0.38160]
INFO:root:Epoch 519 [40.8s + 29.7s]: train==[620.39984=620.36993 + 0.02925], recall=[0.65596, 0.65596], precision=[0.06560, 0.06560], hit=[0.65596, 0.65596], ndcg=[0.37737, 0.37737]
INFO:root:Epoch 529 [40.3s + 28.3s]: train==[616.61884=616.58893 + 0.03008], recall=[0.65546, 0.65546], precision=[0.06555, 0.06555], hit=[0.65546, 0.65546], ndcg=[0.38016, 0.38016]
INFO:root:Epoch 539 [41.4s + 31.7s]: train==[613.06860=613.03741 + 0.03091], recall=[0.65877, 0.65877], precision=[0.06588, 0.06588], hit=[0.65877, 0.65877], ndcg=[0.38374, 0.38374]
INFO:root:Epoch 549 [41.6s + 30.4s]: train==[608.87488=608.84283 + 0.03177], recall=[0.65894, 0.65894], precision=[0.06589, 0.06589], hit=[0.65894, 0.65894], ndcg=[0.37968, 0.37968]
INFO:root:Epoch 559 [41.0s + 30.5s]: train==[606.10468=606.07202 + 0.03267], recall=[0.66523, 0.66523], precision=[0.06652, 0.06652], hit=[0.66523, 0.66523], ndcg=[0.38118, 0.38118]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 569 [40.7s + 27.6s]: train==[602.44788=602.41425 + 0.03361], recall=[0.66242, 0.66242], precision=[0.06624, 0.06624], hit=[0.66242, 0.66242], ndcg=[0.38165, 0.38165]
INFO:root:Epoch 579 [41.3s + 29.1s]: train==[597.98920=597.95502 + 0.03454], recall=[0.65513, 0.65513], precision=[0.06551, 0.06551], hit=[0.65513, 0.65513], ndcg=[0.37861, 0.37861]
INFO:root:Epoch 589 [41.0s + 30.5s]: train==[594.17468=594.13861 + 0.03548], recall=[0.65414, 0.65414], precision=[0.06541, 0.06541], hit=[0.65414, 0.65414], ndcg=[0.38012, 0.38012]
INFO:root:Epoch 599 [41.6s + 29.5s]: train==[591.13116=591.09424 + 0.03649], recall=[0.66275, 0.66275], precision=[0.06627, 0.06627], hit=[0.66275, 0.66275], ndcg=[0.38375, 0.38375]
INFO:root:Epoch 609 [41.0s + 27.7s]: train==[587.27679=587.23907 + 0.03752], recall=[0.65877, 0.65877], precision=[0.06588, 0.06588], hit=[0.65877, 0.65877], ndcg=[0.38239, 0.38239]
INFO:root:Epoch 619 [41.1s + 28.3s]: train==[583.25153=583.21277 + 0.03858], recall=[0.65944, 0.65944], precision=[0.06594, 0.06594], hit=[0.65944, 0.65944], ndcg=[0.38237, 0.38237]
INFO:root:Epoch 629 [41.5s + 27.3s]: train==[579.71741=579.67773 + 0.03962], recall=[0.65960, 0.65960], precision=[0.06596, 0.06596], hit=[0.65960, 0.65960], ndcg=[0.38140, 0.38140]
INFO:root:Epoch 639 [41.6s + 29.2s]: train==[574.54138=574.50043 + 0.04071], recall=[0.65828, 0.65828], precision=[0.06583, 0.06583], hit=[0.65828, 0.65828], ndcg=[0.38540, 0.38540]
INFO:root:Epoch 649 [42.6s + 30.5s]: train==[571.00623=570.96423 + 0.04183], recall=[0.66043, 0.66043], precision=[0.06604, 0.06604], hit=[0.66043, 0.66043], ndcg=[0.37900, 0.37900]
INFO:root:Epoch 659 [40.6s + 30.8s]: train==[567.71198=567.66925 + 0.04297], recall=[0.65811, 0.65811], precision=[0.06581, 0.06581], hit=[0.65811, 0.65811], ndcg=[0.38049, 0.38049]
INFO:root:Best Iter=[55]@[26221.6]	recall=[0.66523], precision=[0.06652], hit=[0.66523], ndcg=[0.38118]
INFO:root:Namespace(Ks='[10]', batch_size=64, data_path='./data/recommendation/', dataset='ml-1m', embed_size=128, epoch=2000, gpu=2, item_density_threshold=0.01, item_threshold=30, layer_size=[128], lmbda=1, local_batch_size=512, local_epoch=1, log_name='run4_1', log_path='/home/qhuaf/graph_pri/logs/', lr=0.0001, mess_dropout=[0.1, 0.1, 0.1], model_name='two_side_graph_run4_1.pkl', num_neighbor=30, num_process=4, pretrain_epoch=300, pri_epoch=200, privacy_protect=False, regs=[1e-05], report=0, save_flag=1, test_flag='part', user_batch_size=512, verbose=1, weights_path='model/')
INFO:root:Epoch 9 [30.3s + 30.6s]: train==[693.08124=693.06488 + 0.01583], recall=[0.19520, 0.19520], precision=[0.01952, 0.01952], hit=[0.19520, 0.19520], ndcg=[0.09097, 0.09097]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 19 [31.3s + 30.0s]: train==[692.61731=692.60187 + 0.01582], recall=[0.22268, 0.22268], precision=[0.02227, 0.02227], hit=[0.22268, 0.22268], ndcg=[0.10605, 0.10605]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 29 [31.6s + 29.9s]: train==[691.73993=691.72375 + 0.01581], recall=[0.25695, 0.25695], precision=[0.02570, 0.02570], hit=[0.25695, 0.25695], ndcg=[0.12656, 0.12656]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 39 [31.1s + 31.0s]: train==[691.19458=691.17859 + 0.01580], recall=[0.29288, 0.29288], precision=[0.02929, 0.02929], hit=[0.29288, 0.29288], ndcg=[0.15066, 0.15066]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 49 [30.0s + 32.2s]: train==[691.39233=691.37732 + 0.01578], recall=[0.31937, 0.31937], precision=[0.03194, 0.03194], hit=[0.31937, 0.31937], ndcg=[0.16813, 0.16813]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 59 [32.3s + 29.3s]: train==[691.61639=691.60138 + 0.01576], recall=[0.32119, 0.32119], precision=[0.03212, 0.03212], hit=[0.32119, 0.32119], ndcg=[0.17342, 0.17342]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 69 [30.7s + 31.2s]: train==[691.75354=691.73822 + 0.01575], recall=[0.31921, 0.31921], precision=[0.03192, 0.03192], hit=[0.31921, 0.31921], ndcg=[0.17292, 0.17292]
INFO:root:Epoch 79 [31.1s + 28.7s]: train==[691.91656=691.90131 + 0.01573], recall=[0.31970, 0.31970], precision=[0.03197, 0.03197], hit=[0.31970, 0.31970], ndcg=[0.17400, 0.17400]
INFO:root:Epoch 89 [30.9s + 28.9s]: train==[692.07721=692.06116 + 0.01572], recall=[0.30911, 0.30911], precision=[0.03091, 0.03091], hit=[0.30911, 0.30911], ndcg=[0.16843, 0.16843]
INFO:root:Epoch 99 [31.2s + 30.3s]: train==[692.15521=692.13971 + 0.01571], recall=[0.30199, 0.30199], precision=[0.03020, 0.03020], hit=[0.30199, 0.30199], ndcg=[0.16185, 0.16185]
INFO:root:Epoch 109 [31.4s + 32.5s]: train==[692.28943=692.27399 + 0.01571], recall=[0.29570, 0.29570], precision=[0.02957, 0.02957], hit=[0.29570, 0.29570], ndcg=[0.15635, 0.15635]
INFO:root:Epoch 119 [30.4s + 31.1s]: train==[692.35223=692.33704 + 0.01570], recall=[0.28311, 0.28311], precision=[0.02831, 0.02831], hit=[0.28311, 0.28311], ndcg=[0.14953, 0.14953]
INFO:root:Epoch 129 [31.1s + 29.7s]: train==[692.43402=692.41895 + 0.01570], recall=[0.28063, 0.28063], precision=[0.02806, 0.02806], hit=[0.28063, 0.28063], ndcg=[0.14415, 0.14415]
INFO:root:Epoch 139 [31.2s + 31.4s]: train==[692.45276=692.43671 + 0.01570], recall=[0.27334, 0.27334], precision=[0.02733, 0.02733], hit=[0.27334, 0.27334], ndcg=[0.13821, 0.13821]
INFO:root:Epoch 149 [31.0s + 32.3s]: train==[692.48816=692.47327 + 0.01570], recall=[0.27334, 0.27334], precision=[0.02733, 0.02733], hit=[0.27334, 0.27334], ndcg=[0.13802, 0.13802]
INFO:root:Epoch 159 [31.2s + 29.5s]: train==[692.50391=692.48779 + 0.01570], recall=[0.26788, 0.26788], precision=[0.02679, 0.02679], hit=[0.26788, 0.26788], ndcg=[0.13354, 0.13354]
INFO:root:Epoch 169 [31.6s + 29.0s]: train==[692.49365=692.47729 + 0.01570], recall=[0.26722, 0.26722], precision=[0.02672, 0.02672], hit=[0.26722, 0.26722], ndcg=[0.13362, 0.13362]
INFO:root:Epoch 179 [30.7s + 30.6s]: train==[692.47845=692.46332 + 0.01570], recall=[0.26970, 0.26970], precision=[0.02697, 0.02697], hit=[0.26970, 0.26970], ndcg=[0.13488, 0.13488]
INFO:root:Epoch 189 [31.3s + 30.3s]: train==[692.42712=692.41095 + 0.01570], recall=[0.27235, 0.27235], precision=[0.02724, 0.02724], hit=[0.27235, 0.27235], ndcg=[0.13648, 0.13648]
INFO:root:Epoch 199 [31.2s + 30.9s]: train==[692.38043=692.36438 + 0.01571], recall=[0.27384, 0.27384], precision=[0.02738, 0.02738], hit=[0.27384, 0.27384], ndcg=[0.13750, 0.13750]
INFO:root:Epoch 209 [30.5s + 29.9s]: train==[692.36115=692.34515 + 0.01572], recall=[0.28146, 0.28146], precision=[0.02815, 0.02815], hit=[0.28146, 0.28146], ndcg=[0.14078, 0.14078]
INFO:root:Epoch 219 [30.8s + 30.3s]: train==[692.26453=692.24841 + 0.01573], recall=[0.28576, 0.28576], precision=[0.02858, 0.02858], hit=[0.28576, 0.28576], ndcg=[0.14609, 0.14609]
INFO:root:Epoch 229 [30.4s + 31.0s]: train==[692.19244=692.17603 + 0.01574], recall=[0.29652, 0.29652], precision=[0.02965, 0.02965], hit=[0.29652, 0.29652], ndcg=[0.15175, 0.15175]
INFO:root:Epoch 239 [30.5s + 30.8s]: train==[692.11932=692.10364 + 0.01575], recall=[0.30712, 0.30712], precision=[0.03071, 0.03071], hit=[0.30712, 0.30712], ndcg=[0.15988, 0.15988]
INFO:root:Epoch 249 [31.1s + 31.5s]: train==[691.98322=691.96802 + 0.01577], recall=[0.31755, 0.31755], precision=[0.03175, 0.03175], hit=[0.31755, 0.31755], ndcg=[0.16527, 0.16527]
INFO:root:Epoch 259 [30.9s + 30.7s]: train==[691.89850=691.88251 + 0.01579], recall=[0.33146, 0.33146], precision=[0.03315, 0.03315], hit=[0.33146, 0.33146], ndcg=[0.17618, 0.17618]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 269 [30.5s + 31.9s]: train==[691.73645=691.72064 + 0.01581], recall=[0.34354, 0.34354], precision=[0.03435, 0.03435], hit=[0.34354, 0.34354], ndcg=[0.18575, 0.18575]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 279 [31.0s + 30.4s]: train==[691.53564=691.52075 + 0.01583], recall=[0.35877, 0.35877], precision=[0.03588, 0.03588], hit=[0.35877, 0.35877], ndcg=[0.19639, 0.19639]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 289 [31.9s + 29.1s]: train==[691.35980=691.34332 + 0.01586], recall=[0.37848, 0.37848], precision=[0.03785, 0.03785], hit=[0.37848, 0.37848], ndcg=[0.21167, 0.21167]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 299 [30.6s + 31.0s]: train==[691.18799=691.17188 + 0.01589], recall=[0.39719, 0.39719], precision=[0.03972, 0.03972], hit=[0.39719, 0.39719], ndcg=[0.22205, 0.22205]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 309 [33.8s + 31.3s]: train==[690.93262=690.91705 + 0.01593], recall=[0.41225, 0.41225], precision=[0.04123, 0.04123], hit=[0.41225, 0.41225], ndcg=[0.23356, 0.23356]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 319 [31.2s + 30.2s]: train==[690.68170=690.66522 + 0.01596], recall=[0.42798, 0.42798], precision=[0.04280, 0.04280], hit=[0.42798, 0.42798], ndcg=[0.24677, 0.24677]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 329 [31.4s + 31.1s]: train==[690.45367=690.43835 + 0.01601], recall=[0.44950, 0.44950], precision=[0.04495, 0.04495], hit=[0.44950, 0.44950], ndcg=[0.25974, 0.25974]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 339 [31.4s + 29.3s]: train==[690.11908=690.10309 + 0.01606], recall=[0.46904, 0.46904], precision=[0.04690, 0.04690], hit=[0.46904, 0.46904], ndcg=[0.27504, 0.27504]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 349 [32.0s + 30.8s]: train==[689.79346=689.77771 + 0.01611], recall=[0.48444, 0.48444], precision=[0.04844, 0.04844], hit=[0.48444, 0.48444], ndcg=[0.28380, 0.28380]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 359 [30.8s + 29.5s]: train==[689.42206=689.40558 + 0.01617], recall=[0.49884, 0.49884], precision=[0.04988, 0.04988], hit=[0.49884, 0.49884], ndcg=[0.29465, 0.29465]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 369 [31.2s + 30.1s]: train==[689.04010=689.02423 + 0.01623], recall=[0.51772, 0.51772], precision=[0.05177, 0.05177], hit=[0.51772, 0.51772], ndcg=[0.30648, 0.30648]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 379 [32.0s + 30.6s]: train==[688.58148=688.56592 + 0.01631], recall=[0.52450, 0.52450], precision=[0.05245, 0.05245], hit=[0.52450, 0.52450], ndcg=[0.31136, 0.31136]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 389 [30.3s + 30.3s]: train==[688.18262=688.16681 + 0.01639], recall=[0.53891, 0.53891], precision=[0.05389, 0.05389], hit=[0.53891, 0.53891], ndcg=[0.32015, 0.32015]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 399 [30.8s + 30.1s]: train==[687.64050=687.62372 + 0.01647], recall=[0.55430, 0.55430], precision=[0.05543, 0.05543], hit=[0.55430, 0.55430], ndcg=[0.32832, 0.32832]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 409 [31.7s + 30.3s]: train==[687.12128=687.10394 + 0.01657], recall=[0.55745, 0.55745], precision=[0.05575, 0.05575], hit=[0.55745, 0.55745], ndcg=[0.33491, 0.33491]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 419 [31.0s + 30.5s]: train==[686.62500=686.60773 + 0.01667], recall=[0.57517, 0.57517], precision=[0.05752, 0.05752], hit=[0.57517, 0.57517], ndcg=[0.34112, 0.34112]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 429 [31.1s + 31.5s]: train==[685.91522=685.89844 + 0.01677], recall=[0.57997, 0.57997], precision=[0.05800, 0.05800], hit=[0.57997, 0.57997], ndcg=[0.34331, 0.34331]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 439 [30.8s + 30.9s]: train==[685.30249=685.28589 + 0.01690], recall=[0.59321, 0.59321], precision=[0.05932, 0.05932], hit=[0.59321, 0.59321], ndcg=[0.34885, 0.34885]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 449 [31.8s + 28.5s]: train==[684.62714=684.61035 + 0.01703], recall=[0.59818, 0.59818], precision=[0.05982, 0.05982], hit=[0.59818, 0.59818], ndcg=[0.35377, 0.35377]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 459 [30.6s + 27.6s]: train==[683.81903=683.80048 + 0.01717], recall=[0.60348, 0.60348], precision=[0.06035, 0.06035], hit=[0.60348, 0.60348], ndcg=[0.35470, 0.35470]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 469 [32.3s + 30.8s]: train==[683.18274=683.16602 + 0.01732], recall=[0.60596, 0.60596], precision=[0.06060, 0.06060], hit=[0.60596, 0.60596], ndcg=[0.36027, 0.36027]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 479 [31.1s + 30.0s]: train==[682.18530=682.16827 + 0.01747], recall=[0.61705, 0.61705], precision=[0.06171, 0.06171], hit=[0.61705, 0.61705], ndcg=[0.36301, 0.36301]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 489 [32.9s + 30.3s]: train==[681.15942=681.14178 + 0.01765], recall=[0.62152, 0.62152], precision=[0.06215, 0.06215], hit=[0.62152, 0.62152], ndcg=[0.36441, 0.36441]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 499 [33.1s + 30.3s]: train==[680.36310=680.34540 + 0.01783], recall=[0.62434, 0.62434], precision=[0.06243, 0.06243], hit=[0.62434, 0.62434], ndcg=[0.36778, 0.36778]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 509 [32.7s + 29.8s]: train==[679.27734=679.25934 + 0.01803], recall=[0.62268, 0.62268], precision=[0.06227, 0.06227], hit=[0.62268, 0.62268], ndcg=[0.36671, 0.36671]
INFO:root:Epoch 519 [32.0s + 30.2s]: train==[678.19275=678.17450 + 0.01823], recall=[0.62781, 0.62781], precision=[0.06278, 0.06278], hit=[0.62781, 0.62781], ndcg=[0.37061, 0.37061]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 529 [31.4s + 28.3s]: train==[676.92572=676.90631 + 0.01845], recall=[0.62848, 0.62848], precision=[0.06285, 0.06285], hit=[0.62848, 0.62848], ndcg=[0.36888, 0.36888]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 539 [32.0s + 30.9s]: train==[675.68903=675.66986 + 0.01867], recall=[0.62980, 0.62980], precision=[0.06298, 0.06298], hit=[0.62980, 0.62980], ndcg=[0.36861, 0.36861]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 549 [32.2s + 30.7s]: train==[674.47308=674.45428 + 0.01892], recall=[0.63924, 0.63924], precision=[0.06392, 0.06392], hit=[0.63924, 0.63924], ndcg=[0.37294, 0.37294]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 559 [31.6s + 28.9s]: train==[673.13965=673.12012 + 0.01916], recall=[0.64056, 0.64056], precision=[0.06406, 0.06406], hit=[0.64056, 0.64056], ndcg=[0.37099, 0.37099]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 569 [30.7s + 30.1s]: train==[671.57129=671.55206 + 0.01943], recall=[0.64023, 0.64023], precision=[0.06402, 0.06402], hit=[0.64023, 0.64023], ndcg=[0.37239, 0.37239]
INFO:root:Epoch 579 [30.4s + 30.9s]: train==[670.19470=670.17419 + 0.01971], recall=[0.63709, 0.63709], precision=[0.06371, 0.06371], hit=[0.63709, 0.63709], ndcg=[0.37288, 0.37288]
INFO:root:Epoch 589 [32.0s + 29.5s]: train==[668.81158=668.79169 + 0.01999], recall=[0.63907, 0.63907], precision=[0.06391, 0.06391], hit=[0.63907, 0.63907], ndcg=[0.37359, 0.37359]
INFO:root:Epoch 599 [33.7s + 30.1s]: train==[667.69275=667.67249 + 0.02029], recall=[0.64222, 0.64222], precision=[0.06422, 0.06422], hit=[0.64222, 0.64222], ndcg=[0.37467, 0.37467]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 609 [32.0s + 31.2s]: train==[666.76318=666.74268 + 0.02061], recall=[0.64520, 0.64520], precision=[0.06452, 0.06452], hit=[0.64520, 0.64520], ndcg=[0.37476, 0.37476]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 619 [32.2s + 31.2s]: train==[665.32751=665.30750 + 0.02094], recall=[0.64719, 0.64719], precision=[0.06472, 0.06472], hit=[0.64719, 0.64719], ndcg=[0.37794, 0.37794]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 629 [32.5s + 31.9s]: train==[663.26190=663.23999 + 0.02126], recall=[0.64238, 0.64238], precision=[0.06424, 0.06424], hit=[0.64238, 0.64238], ndcg=[0.37572, 0.37572]
INFO:root:Epoch 639 [31.2s + 31.5s]: train==[661.97015=661.94873 + 0.02161], recall=[0.64205, 0.64205], precision=[0.06421, 0.06421], hit=[0.64205, 0.64205], ndcg=[0.37398, 0.37398]
INFO:root:Epoch 649 [31.0s + 29.9s]: train==[660.78552=660.76373 + 0.02197], recall=[0.64222, 0.64222], precision=[0.06422, 0.06422], hit=[0.64222, 0.64222], ndcg=[0.37848, 0.37848]
INFO:root:Epoch 659 [32.1s + 29.0s]: train==[659.78632=659.76428 + 0.02234], recall=[0.64735, 0.64735], precision=[0.06474, 0.06474], hit=[0.64735, 0.64735], ndcg=[0.37620, 0.37620]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 669 [31.0s + 30.6s]: train==[658.50848=658.48621 + 0.02272], recall=[0.64603, 0.64603], precision=[0.06460, 0.06460], hit=[0.64603, 0.64603], ndcg=[0.37618, 0.37618]
INFO:root:Epoch 679 [33.2s + 31.6s]: train==[656.44800=656.42401 + 0.02312], recall=[0.64702, 0.64702], precision=[0.06470, 0.06470], hit=[0.64702, 0.64702], ndcg=[0.37641, 0.37641]
INFO:root:Epoch 689 [34.6s + 31.6s]: train==[655.32898=655.30591 + 0.02353], recall=[0.65116, 0.65116], precision=[0.06512, 0.06512], hit=[0.65116, 0.65116], ndcg=[0.37680, 0.37680]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 699 [35.4s + 33.8s]: train==[653.89832=653.87451 + 0.02394], recall=[0.64967, 0.64967], precision=[0.06497, 0.06497], hit=[0.64967, 0.64967], ndcg=[0.37893, 0.37893]
INFO:root:Epoch 709 [34.6s + 32.5s]: train==[652.77527=652.75110 + 0.02438], recall=[0.65381, 0.65381], precision=[0.06538, 0.06538], hit=[0.65381, 0.65381], ndcg=[0.38085, 0.38085]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 719 [33.7s + 33.9s]: train==[650.59363=650.56940 + 0.02481], recall=[0.64901, 0.64901], precision=[0.06490, 0.06490], hit=[0.64901, 0.64901], ndcg=[0.37796, 0.37796]
INFO:root:Epoch 729 [34.0s + 32.8s]: train==[649.38171=649.35583 + 0.02528], recall=[0.64338, 0.64338], precision=[0.06434, 0.06434], hit=[0.64338, 0.64338], ndcg=[0.37538, 0.37538]
INFO:root:Epoch 739 [35.7s + 34.4s]: train==[647.65405=647.62854 + 0.02575], recall=[0.65099, 0.65099], precision=[0.06510, 0.06510], hit=[0.65099, 0.65099], ndcg=[0.37846, 0.37846]
INFO:root:Epoch 749 [34.6s + 32.1s]: train==[645.73041=645.70331 + 0.02622], recall=[0.64818, 0.64818], precision=[0.06482, 0.06482], hit=[0.64818, 0.64818], ndcg=[0.37861, 0.37861]
INFO:root:Epoch 759 [34.0s + 31.8s]: train==[644.28094=644.25311 + 0.02671], recall=[0.65149, 0.65149], precision=[0.06515, 0.06515], hit=[0.65149, 0.65149], ndcg=[0.37751, 0.37751]
INFO:root:Epoch 769 [35.3s + 29.9s]: train==[642.30035=642.27460 + 0.02720], recall=[0.65281, 0.65281], precision=[0.06528, 0.06528], hit=[0.65281, 0.65281], ndcg=[0.38172, 0.38172]
INFO:root:Epoch 779 [32.1s + 34.2s]: train==[640.55286=640.52515 + 0.02771], recall=[0.65513, 0.65513], precision=[0.06551, 0.06551], hit=[0.65513, 0.65513], ndcg=[0.38086, 0.38086]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 789 [32.3s + 32.9s]: train==[638.91943=638.89056 + 0.02825], recall=[0.65099, 0.65099], precision=[0.06510, 0.06510], hit=[0.65099, 0.65099], ndcg=[0.37855, 0.37855]
INFO:root:Epoch 799 [36.1s + 32.4s]: train==[637.73279=637.70416 + 0.02880], recall=[0.65497, 0.65497], precision=[0.06550, 0.06550], hit=[0.65497, 0.65497], ndcg=[0.38079, 0.38079]
INFO:root:Epoch 809 [34.3s + 32.1s]: train==[634.80591=634.77698 + 0.02932], recall=[0.64834, 0.64834], precision=[0.06483, 0.06483], hit=[0.64834, 0.64834], ndcg=[0.37960, 0.37960]
INFO:root:Epoch 819 [34.1s + 31.4s]: train==[633.30585=633.27637 + 0.02989], recall=[0.65182, 0.65182], precision=[0.06518, 0.06518], hit=[0.65182, 0.65182], ndcg=[0.37895, 0.37895]
INFO:root:Epoch 829 [34.2s + 32.0s]: train==[631.67035=631.64093 + 0.03046], recall=[0.65464, 0.65464], precision=[0.06546, 0.06546], hit=[0.65464, 0.65464], ndcg=[0.38103, 0.38103]
INFO:root:Epoch 839 [34.0s + 31.3s]: train==[630.13660=630.10596 + 0.03106], recall=[0.65530, 0.65530], precision=[0.06553, 0.06553], hit=[0.65530, 0.65530], ndcg=[0.38056, 0.38056]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 849 [35.5s + 31.8s]: train==[628.56226=628.53064 + 0.03166], recall=[0.65712, 0.65712], precision=[0.06571, 0.06571], hit=[0.65712, 0.65712], ndcg=[0.38224, 0.38224]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 859 [35.7s + 32.4s]: train==[626.38678=626.35382 + 0.03226], recall=[0.65248, 0.65248], precision=[0.06525, 0.06525], hit=[0.65248, 0.65248], ndcg=[0.37993, 0.37993]
INFO:root:Epoch 869 [34.8s + 31.4s]: train==[624.63086=624.59839 + 0.03289], recall=[0.65579, 0.65579], precision=[0.06558, 0.06558], hit=[0.65579, 0.65579], ndcg=[0.38009, 0.38009]
INFO:root:Epoch 879 [35.3s + 33.2s]: train==[622.33057=622.29712 + 0.03351], recall=[0.65364, 0.65364], precision=[0.06536, 0.06536], hit=[0.65364, 0.65364], ndcg=[0.37980, 0.37980]
INFO:root:Epoch 889 [35.1s + 32.1s]: train==[620.38495=620.35022 + 0.03414], recall=[0.65447, 0.65447], precision=[0.06545, 0.06545], hit=[0.65447, 0.65447], ndcg=[0.37995, 0.37995]
INFO:root:Epoch 899 [35.2s + 31.5s]: train==[618.30408=618.26910 + 0.03480], recall=[0.65861, 0.65861], precision=[0.06586, 0.06586], hit=[0.65861, 0.65861], ndcg=[0.38331, 0.38331]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 909 [34.8s + 29.4s]: train==[616.61920=616.58441 + 0.03550], recall=[0.65182, 0.65182], precision=[0.06518, 0.06518], hit=[0.65182, 0.65182], ndcg=[0.38015, 0.38015]
INFO:root:Epoch 919 [31.9s + 31.5s]: train==[614.34247=614.30646 + 0.03616], recall=[0.65199, 0.65199], precision=[0.06520, 0.06520], hit=[0.65199, 0.65199], ndcg=[0.37965, 0.37965]
INFO:root:Epoch 929 [34.4s + 32.2s]: train==[611.44214=611.40540 + 0.03685], recall=[0.65281, 0.65281], precision=[0.06528, 0.06528], hit=[0.65281, 0.65281], ndcg=[0.38098, 0.38098]
INFO:root:Epoch 939 [34.5s + 32.4s]: train==[610.25995=610.22247 + 0.03756], recall=[0.65066, 0.65066], precision=[0.06507, 0.06507], hit=[0.65066, 0.65066], ndcg=[0.37575, 0.37575]
INFO:root:Epoch 949 [32.7s + 31.7s]: train==[607.78558=607.74707 + 0.03828], recall=[0.65083, 0.65083], precision=[0.06508, 0.06508], hit=[0.65083, 0.65083], ndcg=[0.38039, 0.38039]
INFO:root:Epoch 959 [34.4s + 32.0s]: train==[605.95081=605.91180 + 0.03901], recall=[0.65298, 0.65298], precision=[0.06530, 0.06530], hit=[0.65298, 0.65298], ndcg=[0.37920, 0.37920]
INFO:root:Epoch 969 [33.7s + 31.7s]: train==[603.50848=603.46832 + 0.03974], recall=[0.65646, 0.65646], precision=[0.06565, 0.06565], hit=[0.65646, 0.65646], ndcg=[0.38115, 0.38115]
INFO:root:Epoch 979 [31.7s + 29.8s]: train==[601.23969=601.19891 + 0.04050], recall=[0.65430, 0.65430], precision=[0.06543, 0.06543], hit=[0.65430, 0.65430], ndcg=[0.37966, 0.37966]
INFO:root:Epoch 989 [31.8s + 30.7s]: train==[599.47595=599.43433 + 0.04127], recall=[0.65811, 0.65811], precision=[0.06581, 0.06581], hit=[0.65811, 0.65811], ndcg=[0.38339, 0.38339]
INFO:root:Epoch 999 [33.1s + 30.9s]: train==[597.71942=597.67804 + 0.04205], recall=[0.65348, 0.65348], precision=[0.06535, 0.06535], hit=[0.65348, 0.65348], ndcg=[0.37771, 0.37771]
INFO:root:Epoch 1009 [31.7s + 30.7s]: train==[595.17920=595.13727 + 0.04285], recall=[0.65745, 0.65745], precision=[0.06575, 0.06575], hit=[0.65745, 0.65745], ndcg=[0.38196, 0.38196]
INFO:root:Epoch 1019 [35.8s + 33.1s]: train==[592.49371=592.44940 + 0.04361], recall=[0.65563, 0.65563], precision=[0.06556, 0.06556], hit=[0.65563, 0.65563], ndcg=[0.38059, 0.38059]
INFO:root:Epoch 1029 [33.9s + 32.5s]: train==[591.02002=590.97595 + 0.04442], recall=[0.66126, 0.66126], precision=[0.06613, 0.06613], hit=[0.66126, 0.66126], ndcg=[0.38315, 0.38315]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1039 [34.6s + 33.1s]: train==[588.59546=588.54944 + 0.04526], recall=[0.65762, 0.65762], precision=[0.06576, 0.06576], hit=[0.65762, 0.65762], ndcg=[0.38248, 0.38248]
INFO:root:Epoch 1049 [33.6s + 32.6s]: train==[586.16833=586.12201 + 0.04607], recall=[0.65331, 0.65331], precision=[0.06533, 0.06533], hit=[0.65331, 0.65331], ndcg=[0.37698, 0.37698]
INFO:root:Epoch 1059 [34.0s + 32.6s]: train==[584.31573=584.26801 + 0.04694], recall=[0.65646, 0.65646], precision=[0.06565, 0.06565], hit=[0.65646, 0.65646], ndcg=[0.38028, 0.38028]
INFO:root:Epoch 1069 [33.9s + 32.8s]: train==[581.82196=581.77429 + 0.04779], recall=[0.65927, 0.65927], precision=[0.06593, 0.06593], hit=[0.65927, 0.65927], ndcg=[0.37859, 0.37859]
INFO:root:Epoch 1079 [34.6s + 32.6s]: train==[579.39154=579.34283 + 0.04863], recall=[0.65563, 0.65563], precision=[0.06556, 0.06556], hit=[0.65563, 0.65563], ndcg=[0.38080, 0.38080]
INFO:root:Epoch 1089 [34.0s + 31.4s]: train==[577.83246=577.78339 + 0.04953], recall=[0.66291, 0.66291], precision=[0.06629, 0.06629], hit=[0.66291, 0.66291], ndcg=[0.38266, 0.38266]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1099 [34.1s + 29.6s]: train==[575.50214=575.45172 + 0.05046], recall=[0.65662, 0.65662], precision=[0.06566, 0.06566], hit=[0.65662, 0.65662], ndcg=[0.37816, 0.37816]
INFO:root:Epoch 1109 [34.0s + 30.1s]: train==[573.37506=573.32379 + 0.05137], recall=[0.65613, 0.65613], precision=[0.06561, 0.06561], hit=[0.65613, 0.65613], ndcg=[0.37987, 0.37987]
INFO:root:Epoch 1119 [33.0s + 31.4s]: train==[570.78833=570.73669 + 0.05226], recall=[0.65762, 0.65762], precision=[0.06576, 0.06576], hit=[0.65762, 0.65762], ndcg=[0.37904, 0.37904]
INFO:root:Epoch 1129 [33.6s + 31.8s]: train==[568.35010=568.29663 + 0.05319], recall=[0.64950, 0.64950], precision=[0.06495, 0.06495], hit=[0.64950, 0.64950], ndcg=[0.37839, 0.37839]
INFO:root:Epoch 1139 [34.8s + 33.0s]: train==[567.19696=567.14258 + 0.05421], recall=[0.65662, 0.65662], precision=[0.06566, 0.06566], hit=[0.65662, 0.65662], ndcg=[0.38204, 0.38204]
INFO:root:Epoch 1149 [36.3s + 32.4s]: train==[563.68091=563.62640 + 0.05505], recall=[0.66291, 0.66291], precision=[0.06629, 0.06629], hit=[0.66291, 0.66291], ndcg=[0.38227, 0.38227]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1159 [35.6s + 32.6s]: train==[561.61682=561.56073 + 0.05605], recall=[0.65927, 0.65927], precision=[0.06593, 0.06593], hit=[0.65927, 0.65927], ndcg=[0.38075, 0.38075]
INFO:root:Epoch 1169 [34.7s + 32.5s]: train==[559.70154=559.64459 + 0.05699], recall=[0.65728, 0.65728], precision=[0.06573, 0.06573], hit=[0.65728, 0.65728], ndcg=[0.37782, 0.37782]
INFO:root:Epoch 1179 [34.7s + 33.1s]: train==[557.11542=557.05768 + 0.05797], recall=[0.66159, 0.66159], precision=[0.06616, 0.06616], hit=[0.66159, 0.66159], ndcg=[0.38270, 0.38270]
INFO:root:Epoch 1189 [33.4s + 32.3s]: train==[554.35767=554.29852 + 0.05895], recall=[0.66076, 0.66076], precision=[0.06608, 0.06608], hit=[0.66076, 0.66076], ndcg=[0.38048, 0.38048]
INFO:root:Epoch 1199 [35.2s + 32.7s]: train==[552.55438=552.49445 + 0.05995], recall=[0.65745, 0.65745], precision=[0.06575, 0.06575], hit=[0.65745, 0.65745], ndcg=[0.38262, 0.38262]
INFO:root:Epoch 1209 [34.3s + 32.3s]: train==[550.18347=550.12244 + 0.06102], recall=[0.65513, 0.65513], precision=[0.06551, 0.06551], hit=[0.65513, 0.65513], ndcg=[0.38046, 0.38046]
INFO:root:Epoch 1219 [34.6s + 33.5s]: train==[548.34180=548.27985 + 0.06200], recall=[0.66175, 0.66175], precision=[0.06618, 0.06618], hit=[0.66175, 0.66175], ndcg=[0.38395, 0.38395]
INFO:root:Epoch 1229 [33.9s + 33.6s]: train==[546.69269=546.62946 + 0.06308], recall=[0.65480, 0.65480], precision=[0.06548, 0.06548], hit=[0.65480, 0.65480], ndcg=[0.37995, 0.37995]
INFO:root:Epoch 1239 [34.2s + 32.4s]: train==[544.98987=544.92590 + 0.06409], recall=[0.65828, 0.65828], precision=[0.06583, 0.06583], hit=[0.65828, 0.65828], ndcg=[0.38410, 0.38410]
INFO:root:Epoch 1249 [33.9s + 33.3s]: train==[543.21472=543.14948 + 0.06520], recall=[0.65811, 0.65811], precision=[0.06581, 0.06581], hit=[0.65811, 0.65811], ndcg=[0.38368, 0.38368]
INFO:root:Epoch 1259 [33.5s + 33.8s]: train==[540.72998=540.66370 + 0.06629], recall=[0.65993, 0.65993], precision=[0.06599, 0.06599], hit=[0.65993, 0.65993], ndcg=[0.38261, 0.38261]
INFO:root:Epoch 1269 [34.5s + 32.9s]: train==[538.56982=538.50256 + 0.06742], recall=[0.65497, 0.65497], precision=[0.06550, 0.06550], hit=[0.65497, 0.65497], ndcg=[0.37672, 0.37672]
INFO:root:Epoch 1279 [34.2s + 33.3s]: train==[536.25842=536.19031 + 0.06841], recall=[0.65795, 0.65795], precision=[0.06579, 0.06579], hit=[0.65795, 0.65795], ndcg=[0.38188, 0.38188]
INFO:root:Epoch 1289 [33.1s + 32.4s]: train==[533.37268=533.30304 + 0.06953], recall=[0.65844, 0.65844], precision=[0.06584, 0.06584], hit=[0.65844, 0.65844], ndcg=[0.38082, 0.38082]
INFO:root:Epoch 1299 [35.9s + 33.0s]: train==[532.15857=532.08820 + 0.07064], recall=[0.65894, 0.65894], precision=[0.06589, 0.06589], hit=[0.65894, 0.65894], ndcg=[0.38414, 0.38414]
INFO:root:Epoch 1309 [34.6s + 32.9s]: train==[529.70758=529.63580 + 0.07175], recall=[0.66043, 0.66043], precision=[0.06604, 0.06604], hit=[0.66043, 0.66043], ndcg=[0.38232, 0.38232]
INFO:root:Epoch 1319 [33.6s + 33.2s]: train==[527.28564=527.21234 + 0.07284], recall=[0.65695, 0.65695], precision=[0.06570, 0.06570], hit=[0.65695, 0.65695], ndcg=[0.38189, 0.38189]
INFO:root:Epoch 1329 [35.1s + 32.3s]: train==[526.17505=526.10065 + 0.07406], recall=[0.66225, 0.66225], precision=[0.06623, 0.06623], hit=[0.66225, 0.66225], ndcg=[0.38371, 0.38371]
INFO:root:Epoch 1339 [34.9s + 31.6s]: train==[523.93646=523.86163 + 0.07520], recall=[0.66109, 0.66109], precision=[0.06611, 0.06611], hit=[0.66109, 0.66109], ndcg=[0.38246, 0.38246]
INFO:root:Epoch 1349 [34.4s + 32.2s]: train==[522.75000=522.67334 + 0.07639], recall=[0.65745, 0.65745], precision=[0.06575, 0.06575], hit=[0.65745, 0.65745], ndcg=[0.38003, 0.38003]
INFO:root:Best Iter=[108]@[40683.3]	recall=[0.66291], precision=[0.06629], hit=[0.66291], ndcg=[0.38266]
INFO:root:Namespace(Ks='[10]', batch_size=64, data_path='./data/recommendation/', dataset='ml-1m', embed_size=128, epoch=2000, gpu=2, item_density_threshold=0.01, item_threshold=30, layer_size=[128], lmbda=1, local_batch_size=512, local_epoch=1, log_name='run4_1', log_path='/home/qhuaf/graph_pri/logs/', lr=0.0001, mess_dropout=[0.1, 0.1, 0.1], model_name='two_side_graph_run4_1.pkl', num_neighbor=10, num_process=4, pretrain_epoch=300, pri_epoch=200, privacy_protect=False, regs=[1e-05], report=0, save_flag=1, test_flag='part', user_batch_size=512, verbose=1, weights_path='model/')
INFO:root:Namespace(Ks='[10]', batch_size=64, data_path='./data/recommendation/', dataset='ml-1m', embed_size=128, epoch=2000, gpu=2, item_density_threshold=0.01, item_threshold=30, layer_size=[128], lmbda=1, local_batch_size=512, local_epoch=1, log_name='run4_1', log_path='/home/qhuaf/graph_pri/logs/', lr=0.0001, mess_dropout=[0.1, 0.1, 0.1], model_name='two_side_graph_run4_1.pkl', num_neighbor=10, num_process=4, pretrain_epoch=300, pri_epoch=200, privacy_protect=False, regs=[1e-05], report=0, save_flag=1, test_flag='part', user_batch_size=512, verbose=1, weights_path='model/')
INFO:root:Epoch 9 [109.4s + 31.3s]: train==[693.02966=693.01434 + 0.01583], recall=[0.21589, 0.21589], precision=[0.02159, 0.02159], hit=[0.21589, 0.21589], ndcg=[0.09896, 0.09896]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 19 [109.3s + 28.8s]: train==[692.60126=692.58557 + 0.01582], recall=[0.23825, 0.23825], precision=[0.02382, 0.02382], hit=[0.23825, 0.23825], ndcg=[0.11065, 0.11065]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 29 [108.5s + 28.7s]: train==[691.82983=691.81433 + 0.01581], recall=[0.28427, 0.28427], precision=[0.02843, 0.02843], hit=[0.28427, 0.28427], ndcg=[0.13612, 0.13612]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 39 [110.2s + 28.7s]: train==[690.79187=690.77600 + 0.01580], recall=[0.31954, 0.31954], precision=[0.03195, 0.03195], hit=[0.31954, 0.31954], ndcg=[0.16520, 0.16520]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 49 [109.9s + 29.8s]: train==[690.31891=690.30383 + 0.01579], recall=[0.34851, 0.34851], precision=[0.03485, 0.03485], hit=[0.34851, 0.34851], ndcg=[0.18844, 0.18844]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 59 [112.3s + 29.6s]: train==[690.17401=690.15912 + 0.01577], recall=[0.37053, 0.37053], precision=[0.03705, 0.03705], hit=[0.37053, 0.37053], ndcg=[0.20799, 0.20799]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 69 [108.3s + 30.9s]: train==[690.26617=690.24988 + 0.01576], recall=[0.38543, 0.38543], precision=[0.03854, 0.03854], hit=[0.38543, 0.38543], ndcg=[0.22021, 0.22021]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 79 [109.4s + 27.7s]: train==[690.34143=690.32556 + 0.01575], recall=[0.39785, 0.39785], precision=[0.03978, 0.03978], hit=[0.39785, 0.39785], ndcg=[0.22945, 0.22945]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 89 [109.2s + 30.1s]: train==[690.41339=690.39703 + 0.01574], recall=[0.40430, 0.40430], precision=[0.04043, 0.04043], hit=[0.40430, 0.40430], ndcg=[0.23493, 0.23493]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 99 [108.7s + 28.7s]: train==[690.47607=690.46069 + 0.01573], recall=[0.40132, 0.40132], precision=[0.04013, 0.04013], hit=[0.40132, 0.40132], ndcg=[0.23616, 0.23616]
INFO:root:Epoch 109 [108.7s + 30.9s]: train==[690.60730=690.59192 + 0.01572], recall=[0.39570, 0.39570], precision=[0.03957, 0.03957], hit=[0.39570, 0.39570], ndcg=[0.23217, 0.23217]
INFO:root:Epoch 119 [110.0s + 28.6s]: train==[690.69867=690.68335 + 0.01572], recall=[0.39040, 0.39040], precision=[0.03904, 0.03904], hit=[0.39040, 0.39040], ndcg=[0.23031, 0.23031]
INFO:root:Epoch 129 [111.0s + 29.2s]: train==[690.82721=690.81177 + 0.01572], recall=[0.38146, 0.38146], precision=[0.03815, 0.03815], hit=[0.38146, 0.38146], ndcg=[0.22265, 0.22265]
INFO:root:Epoch 139 [110.7s + 29.4s]: train==[690.95593=690.94110 + 0.01571], recall=[0.37301, 0.37301], precision=[0.03730, 0.03730], hit=[0.37301, 0.37301], ndcg=[0.21818, 0.21818]
INFO:root:Epoch 149 [109.9s + 28.3s]: train==[691.05719=691.04126 + 0.01571], recall=[0.36556, 0.36556], precision=[0.03656, 0.03656], hit=[0.36556, 0.36556], ndcg=[0.21101, 0.21101]
INFO:root:Epoch 159 [110.7s + 27.6s]: train==[691.15338=691.13721 + 0.01571], recall=[0.35861, 0.35861], precision=[0.03586, 0.03586], hit=[0.35861, 0.35861], ndcg=[0.20787, 0.20787]
INFO:root:Epoch 169 [109.5s + 29.6s]: train==[691.23975=691.22522 + 0.01572], recall=[0.34272, 0.34272], precision=[0.03427, 0.03427], hit=[0.34272, 0.34272], ndcg=[0.19732, 0.19732]
INFO:root:Epoch 179 [109.2s + 30.7s]: train==[691.26611=691.25006 + 0.01572], recall=[0.33957, 0.33957], precision=[0.03396, 0.03396], hit=[0.33957, 0.33957], ndcg=[0.19438, 0.19438]
INFO:root:Epoch 189 [109.9s + 28.9s]: train==[691.32001=691.30377 + 0.01572], recall=[0.33344, 0.33344], precision=[0.03334, 0.03334], hit=[0.33344, 0.33344], ndcg=[0.18869, 0.18869]
INFO:root:Epoch 199 [109.5s + 29.5s]: train==[691.40356=691.38800 + 0.01573], recall=[0.33377, 0.33377], precision=[0.03338, 0.03338], hit=[0.33377, 0.33377], ndcg=[0.18825, 0.18825]
INFO:root:Epoch 209 [110.5s + 28.8s]: train==[691.41046=691.39526 + 0.01574], recall=[0.32732, 0.32732], precision=[0.03273, 0.03273], hit=[0.32732, 0.32732], ndcg=[0.18623, 0.18623]
INFO:root:Epoch 219 [110.2s + 29.3s]: train==[691.35620=691.34076 + 0.01574], recall=[0.32219, 0.32219], precision=[0.03222, 0.03222], hit=[0.32219, 0.32219], ndcg=[0.18242, 0.18242]
INFO:root:Epoch 229 [109.0s + 29.3s]: train==[691.35846=691.34277 + 0.01575], recall=[0.32798, 0.32798], precision=[0.03280, 0.03280], hit=[0.32798, 0.32798], ndcg=[0.18444, 0.18444]
INFO:root:Epoch 239 [109.1s + 28.0s]: train==[691.34204=691.32605 + 0.01576], recall=[0.33013, 0.33013], precision=[0.03301, 0.03301], hit=[0.33013, 0.33013], ndcg=[0.18571, 0.18571]
INFO:root:Epoch 249 [110.9s + 29.2s]: train==[691.21832=691.20221 + 0.01578], recall=[0.32599, 0.32599], precision=[0.03260, 0.03260], hit=[0.32599, 0.32599], ndcg=[0.18384, 0.18384]
INFO:root:Epoch 259 [109.7s + 29.0s]: train==[691.22784=691.21216 + 0.01579], recall=[0.33146, 0.33146], precision=[0.03315, 0.03315], hit=[0.33146, 0.33146], ndcg=[0.18674, 0.18674]
INFO:root:Epoch 269 [110.1s + 30.8s]: train==[691.04492=691.02838 + 0.01581], recall=[0.33775, 0.33775], precision=[0.03377, 0.03377], hit=[0.33775, 0.33775], ndcg=[0.18798, 0.18798]
INFO:root:Epoch 279 [109.4s + 29.8s]: train==[691.04309=691.02734 + 0.01583], recall=[0.33907, 0.33907], precision=[0.03391, 0.03391], hit=[0.33907, 0.33907], ndcg=[0.19225, 0.19225]
INFO:root:Epoch 289 [109.2s + 28.8s]: train==[690.93469=690.91937 + 0.01586], recall=[0.34205, 0.34205], precision=[0.03421, 0.03421], hit=[0.34205, 0.34205], ndcg=[0.19495, 0.19495]
INFO:root:Best Iter=[8]@[30974.2]	recall=[0.40430], precision=[0.04043], hit=[0.40430], ndcg=[0.23493]
INFO:root:Namespace(Ks='[10]', batch_size=64, data_path='./data/recommendation/', dataset='ml-1m', embed_size=128, epoch=2000, gpu=2, item_density_threshold=0.01, item_threshold=30, layer_size=[128], lmbda=1, local_batch_size=512, local_epoch=1, log_name='run4_1', log_path='/home/qhuaf/graph_pri/logs/', lr=0.0001, mess_dropout=[0.1, 0.1, 0.1], model_name='two_side_graph_run4_1.pkl', num_neighbor=10, num_process=4, pretrain_epoch=300, pri_epoch=200, privacy_protect=False, regs=[1e-05], report=0, save_flag=1, test_flag='part', user_batch_size=512, verbose=1, weights_path='model/')
INFO:root:Epoch 9 [108.1s + 31.3s]: train==[692.90387=692.88800 + 0.01583], recall=[0.21656, 0.21656], precision=[0.02166, 0.02166], hit=[0.21656, 0.21656], ndcg=[0.09676, 0.09676]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 19 [107.6s + 31.4s]: train==[692.17023=692.15454 + 0.01582], recall=[0.24454, 0.24454], precision=[0.02445, 0.02445], hit=[0.24454, 0.24454], ndcg=[0.11712, 0.11712]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 29 [108.5s + 31.0s]: train==[690.45520=690.44019 + 0.01581], recall=[0.29570, 0.29570], precision=[0.02957, 0.02957], hit=[0.29570, 0.29570], ndcg=[0.14817, 0.14817]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 39 [109.7s + 30.5s]: train==[688.80579=688.78986 + 0.01580], recall=[0.35215, 0.35215], precision=[0.03522, 0.03522], hit=[0.35215, 0.35215], ndcg=[0.18496, 0.18496]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 49 [107.4s + 32.3s]: train==[688.51703=688.50220 + 0.01579], recall=[0.38825, 0.38825], precision=[0.03882, 0.03882], hit=[0.38825, 0.38825], ndcg=[0.21333, 0.21333]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 59 [107.8s + 30.2s]: train==[688.87195=688.85651 + 0.01577], recall=[0.40563, 0.40563], precision=[0.04056, 0.04056], hit=[0.40563, 0.40563], ndcg=[0.22945, 0.22945]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 69 [108.4s + 31.4s]: train==[689.21625=689.20105 + 0.01575], recall=[0.42351, 0.42351], precision=[0.04235, 0.04235], hit=[0.42351, 0.42351], ndcg=[0.24481, 0.24481]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 79 [108.0s + 31.4s]: train==[689.56714=689.55115 + 0.01573], recall=[0.42550, 0.42550], precision=[0.04255, 0.04255], hit=[0.42550, 0.42550], ndcg=[0.25040, 0.25040]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 89 [107.7s + 31.7s]: train==[689.91840=689.90308 + 0.01572], recall=[0.41573, 0.41573], precision=[0.04157, 0.04157], hit=[0.41573, 0.41573], ndcg=[0.24656, 0.24656]
INFO:root:Epoch 99 [107.3s + 31.8s]: train==[690.30859=690.29266 + 0.01571], recall=[0.40099, 0.40099], precision=[0.04010, 0.04010], hit=[0.40099, 0.40099], ndcg=[0.24021, 0.24021]
INFO:root:Epoch 109 [109.0s + 30.2s]: train==[690.64331=690.62799 + 0.01570], recall=[0.38096, 0.38096], precision=[0.03810, 0.03810], hit=[0.38096, 0.38096], ndcg=[0.22744, 0.22744]
INFO:root:Epoch 119 [108.3s + 30.9s]: train==[690.93121=690.91602 + 0.01569], recall=[0.36656, 0.36656], precision=[0.03666, 0.03666], hit=[0.36656, 0.36656], ndcg=[0.21832, 0.21832]
INFO:root:Epoch 129 [108.7s + 30.7s]: train==[691.19171=691.17572 + 0.01569], recall=[0.35017, 0.35017], precision=[0.03502, 0.03502], hit=[0.35017, 0.35017], ndcg=[0.20501, 0.20501]
INFO:root:Epoch 139 [108.4s + 31.3s]: train==[691.41083=691.39520 + 0.01569], recall=[0.33560, 0.33560], precision=[0.03356, 0.03356], hit=[0.33560, 0.33560], ndcg=[0.19360, 0.19360]
INFO:root:Epoch 149 [108.9s + 32.2s]: train==[691.54047=691.52478 + 0.01568], recall=[0.32583, 0.32583], precision=[0.03258, 0.03258], hit=[0.32583, 0.32583], ndcg=[0.18488, 0.18488]
INFO:root:Epoch 159 [107.7s + 31.4s]: train==[691.68024=691.66479 + 0.01568], recall=[0.31573, 0.31573], precision=[0.03157, 0.03157], hit=[0.31573, 0.31573], ndcg=[0.17791, 0.17791]
INFO:root:Epoch 169 [107.9s + 30.9s]: train==[691.77216=691.75684 + 0.01568], recall=[0.30348, 0.30348], precision=[0.03035, 0.03035], hit=[0.30348, 0.30348], ndcg=[0.16998, 0.16998]
INFO:root:Epoch 179 [107.8s + 31.5s]: train==[691.88464=691.86926 + 0.01568], recall=[0.29917, 0.29917], precision=[0.02992, 0.02992], hit=[0.29917, 0.29917], ndcg=[0.16611, 0.16611]
INFO:root:Epoch 189 [108.3s + 31.3s]: train==[691.93323=691.91705 + 0.01569], recall=[0.29354, 0.29354], precision=[0.02935, 0.02935], hit=[0.29354, 0.29354], ndcg=[0.16050, 0.16050]
INFO:root:Epoch 199 [108.1s + 30.6s]: train==[691.95490=691.93878 + 0.01569], recall=[0.29238, 0.29238], precision=[0.02924, 0.02924], hit=[0.29238, 0.29238], ndcg=[0.15807, 0.15807]
INFO:root:Epoch 209 [109.1s + 29.7s]: train==[691.96130=691.94519 + 0.01570], recall=[0.28841, 0.28841], precision=[0.02884, 0.02884], hit=[0.28841, 0.28841], ndcg=[0.15508, 0.15508]
INFO:root:Epoch 219 [108.1s + 31.1s]: train==[691.99677=691.98145 + 0.01571], recall=[0.28775, 0.28775], precision=[0.02877, 0.02877], hit=[0.28775, 0.28775], ndcg=[0.15599, 0.15599]
INFO:root:Epoch 229 [108.3s + 31.4s]: train==[691.94861=691.93237 + 0.01572], recall=[0.28891, 0.28891], precision=[0.02889, 0.02889], hit=[0.28891, 0.28891], ndcg=[0.15496, 0.15496]
INFO:root:Epoch 239 [107.8s + 33.0s]: train==[691.90302=691.88763 + 0.01573], recall=[0.29321, 0.29321], precision=[0.02932, 0.02932], hit=[0.29321, 0.29321], ndcg=[0.15813, 0.15813]
INFO:root:Epoch 249 [108.4s + 30.1s]: train==[691.88428=691.86914 + 0.01575], recall=[0.29967, 0.29967], precision=[0.02997, 0.02997], hit=[0.29967, 0.29967], ndcg=[0.16089, 0.16089]
INFO:root:Epoch 259 [108.0s + 32.1s]: train==[691.78033=691.76495 + 0.01577], recall=[0.31043, 0.31043], precision=[0.03104, 0.03104], hit=[0.31043, 0.31043], ndcg=[0.16664, 0.16664]
INFO:root:Epoch 269 [107.9s + 31.0s]: train==[691.67322=691.65717 + 0.01579], recall=[0.31838, 0.31838], precision=[0.03184, 0.03184], hit=[0.31838, 0.31838], ndcg=[0.17349, 0.17349]
INFO:root:Epoch 279 [109.1s + 30.6s]: train==[691.58917=691.57281 + 0.01581], recall=[0.33030, 0.33030], precision=[0.03303, 0.03303], hit=[0.33030, 0.33030], ndcg=[0.18239, 0.18239]
INFO:root:Best Iter=[7]@[29555.0]	recall=[0.42550], precision=[0.04255], hit=[0.42550], ndcg=[0.25040]
INFO:root:Namespace(Ks='[10]', batch_size=64, data_path='./data/recommendation/', dataset='ml-1m', embed_size=128, epoch=2000, gpu=2, item_density_threshold=0.01, item_threshold=30, layer_size=[128], lmbda=1, local_batch_size=512, local_epoch=1, log_name='run4_1', log_path='/home/qhuaf/graph_pri/logs/', lr=0.0001, mess_dropout=[0.1, 0.1, 0.1], model_name='two_side_graph_run4_1.pkl', num_neighbor=10, num_process=4, pretrain_epoch=300, pri_epoch=200, privacy_protect=False, regs=[1e-05], report=0, save_flag=1, test_flag='part', user_batch_size=512, verbose=1, weights_path='model/')
INFO:root:Namespace(Ks='[10]', batch_size=64, data_path='./data/recommendation/', dataset='ml-1m', embed_size=128, epoch=2000, gpu=2, item_density_threshold=0.01, item_threshold=30, layer_size=[128], lmbda=1, local_batch_size=512, local_epoch=1, log_name='run4_1', log_path='/home/qhuaf/graph_pri/logs/', lr=0.0001, mess_dropout=[0.1, 0.1, 0.1], model_name='two_side_graph_run4_1.pkl', num_neighbor=10, num_process=4, pretrain_epoch=300, pri_epoch=200, privacy_protect=False, regs=[1e-05], report=0, save_flag=1, test_flag='part', user_batch_size=512, verbose=1, weights_path='model/')
INFO:root:Namespace(Ks='[10]', batch_size=64, data_path='./data/recommendation/', dataset='ml-1m', embed_size=128, epoch=2000, gpu=3, item_density_threshold=0.01, item_threshold=30, layer_size=[128], lmbda=1, local_batch_size=512, local_epoch=1, log_name='run4_1', log_path='/home/qhuaf/graph_pri/logs/', lr=0.0001, mess_dropout=[0.1, 0.1, 0.1], model_name='two_side_graph_run4_1.pkl', num_neighbor=10, num_process=4, pretrain_epoch=300, pri_epoch=200, privacy_protect=False, regs=[1e-05], report=0, save_flag=1, test_flag='part', user_batch_size=512, verbose=1, weights_path='model/')
INFO:root:Epoch 9 [30.9s + 28.4s]: train==[693.02240=693.00720 + 0.01583], recall=[0.20662, 0.20662], precision=[0.02066, 0.02066], hit=[0.20662, 0.20662], ndcg=[0.09224, 0.09224]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 19 [31.5s + 28.0s]: train==[692.75433=692.73853 + 0.01582], recall=[0.21126, 0.21126], precision=[0.02113, 0.02113], hit=[0.21126, 0.21126], ndcg=[0.09668, 0.09668]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 29 [29.6s + 27.9s]: train==[692.12799=692.11353 + 0.01580], recall=[0.24007, 0.24007], precision=[0.02401, 0.02401], hit=[0.24007, 0.24007], ndcg=[0.11160, 0.11160]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 39 [31.1s + 32.5s]: train==[691.56879=691.55206 + 0.01579], recall=[0.26755, 0.26755], precision=[0.02675, 0.02675], hit=[0.26755, 0.26755], ndcg=[0.13099, 0.13099]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 49 [31.0s + 29.8s]: train==[691.55157=691.53674 + 0.01577], recall=[0.29570, 0.29570], precision=[0.02957, 0.02957], hit=[0.29570, 0.29570], ndcg=[0.14944, 0.14944]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 59 [31.3s + 29.4s]: train==[691.70563=691.68951 + 0.01575], recall=[0.30944, 0.30944], precision=[0.03094, 0.03094], hit=[0.30944, 0.30944], ndcg=[0.16051, 0.16051]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 69 [30.0s + 30.2s]: train==[691.83575=691.82056 + 0.01573], recall=[0.31291, 0.31291], precision=[0.03129, 0.03129], hit=[0.31291, 0.31291], ndcg=[0.16393, 0.16393]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 79 [30.9s + 29.7s]: train==[691.95612=691.93933 + 0.01571], recall=[0.31523, 0.31523], precision=[0.03152, 0.03152], hit=[0.31523, 0.31523], ndcg=[0.16500, 0.16500]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 89 [31.1s + 29.9s]: train==[692.04022=692.02448 + 0.01570], recall=[0.30679, 0.30679], precision=[0.03068, 0.03068], hit=[0.30679, 0.30679], ndcg=[0.16065, 0.16065]
INFO:root:Epoch 99 [32.0s + 28.3s]: train==[692.15509=692.13940 + 0.01569], recall=[0.29818, 0.29818], precision=[0.02982, 0.02982], hit=[0.29818, 0.29818], ndcg=[0.15653, 0.15653]
INFO:root:Epoch 109 [32.2s + 29.9s]: train==[692.22345=692.20770 + 0.01568], recall=[0.29139, 0.29139], precision=[0.02914, 0.02914], hit=[0.29139, 0.29139], ndcg=[0.15275, 0.15275]
INFO:root:Epoch 119 [30.7s + 29.7s]: train==[692.32037=692.30469 + 0.01567], recall=[0.28924, 0.28924], precision=[0.02892, 0.02892], hit=[0.28924, 0.28924], ndcg=[0.14806, 0.14806]
INFO:root:Epoch 129 [30.9s + 30.5s]: train==[692.37439=692.35840 + 0.01567], recall=[0.28642, 0.28642], precision=[0.02864, 0.02864], hit=[0.28642, 0.28642], ndcg=[0.14641, 0.14641]
INFO:root:Namespace(Ks='[10]', batch_size=64, data_path='./data/recommendation/', dataset='ml-1m', embed_size=128, epoch=2000, gpu=3, item_density_threshold=0.01, item_threshold=30, layer_size=[128], lmbda=1, local_batch_size=512, local_epoch=1, log_name='run4_1', log_path='/home/qhuaf/graph_pri/logs/', lr=0.0001, mess_dropout=[0.1, 0.1, 0.1], model_name='two_side_graph_run4_1.pkl', num_neighbor=10, num_process=4, pretrain_epoch=300, pri_epoch=200, privacy_protect=False, regs=[1e-05], report=0, save_flag=1, test_flag='part', user_batch_size=512, verbose=1, weights_path='model/')
INFO:root:Epoch 139 [31.0s + 29.8s]: train==[692.44653=692.43091 + 0.01566], recall=[0.27268, 0.27268], precision=[0.02727, 0.02727], hit=[0.27268, 0.27268], ndcg=[0.13988, 0.13988]
INFO:root:Epoch 149 [34.6s + 34.8s]: train==[692.42352=692.40759 + 0.01566], recall=[0.27566, 0.27566], precision=[0.02757, 0.02757], hit=[0.27566, 0.27566], ndcg=[0.13919, 0.13919]
INFO:root:Epoch 159 [34.4s + 33.2s]: train==[692.45435=692.43835 + 0.01566], recall=[0.27119, 0.27119], precision=[0.02712, 0.02712], hit=[0.27119, 0.27119], ndcg=[0.13488, 0.13488]
INFO:root:Epoch 169 [34.7s + 34.4s]: train==[692.47711=692.46161 + 0.01566], recall=[0.27020, 0.27020], precision=[0.02702, 0.02702], hit=[0.27020, 0.27020], ndcg=[0.13569, 0.13569]
INFO:root:Epoch 9 [111.7s + 31.8s]: train==[692.91852=692.90277 + 0.01583], recall=[0.19834, 0.19834], precision=[0.01983, 0.01983], hit=[0.19834, 0.19834], ndcg=[0.09201, 0.09201]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 179 [35.0s + 32.9s]: train==[692.46967=692.45416 + 0.01566], recall=[0.26738, 0.26738], precision=[0.02674, 0.02674], hit=[0.26738, 0.26738], ndcg=[0.13409, 0.13409]
INFO:root:Epoch 189 [32.9s + 33.2s]: train==[692.44141=692.42615 + 0.01566], recall=[0.27136, 0.27136], precision=[0.02714, 0.02714], hit=[0.27136, 0.27136], ndcg=[0.13791, 0.13791]
INFO:root:Epoch 199 [32.2s + 32.2s]: train==[692.40662=692.39069 + 0.01566], recall=[0.27599, 0.27599], precision=[0.02760, 0.02760], hit=[0.27599, 0.27599], ndcg=[0.13932, 0.13932]
INFO:root:Epoch 209 [33.0s + 33.4s]: train==[692.33411=692.31860 + 0.01567], recall=[0.27483, 0.27483], precision=[0.02748, 0.02748], hit=[0.27483, 0.27483], ndcg=[0.14033, 0.14033]
INFO:root:Epoch 19 [111.9s + 33.2s]: train==[692.41840=692.40161 + 0.01582], recall=[0.21937, 0.21937], precision=[0.02194, 0.02194], hit=[0.21937, 0.21937], ndcg=[0.10200, 0.10200]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 219 [32.4s + 32.7s]: train==[692.24310=692.22809 + 0.01567], recall=[0.28444, 0.28444], precision=[0.02844, 0.02844], hit=[0.28444, 0.28444], ndcg=[0.14542, 0.14542]
INFO:root:Epoch 229 [33.4s + 33.4s]: train==[692.23419=692.21790 + 0.01568], recall=[0.29255, 0.29255], precision=[0.02925, 0.02925], hit=[0.29255, 0.29255], ndcg=[0.15190, 0.15190]
INFO:root:Epoch 239 [34.2s + 33.1s]: train==[692.07355=692.05865 + 0.01570], recall=[0.29917, 0.29917], precision=[0.02992, 0.02992], hit=[0.29917, 0.29917], ndcg=[0.15765, 0.15765]
INFO:root:Epoch 29 [111.8s + 33.1s]: train==[691.42291=691.40704 + 0.01581], recall=[0.26209, 0.26209], precision=[0.02621, 0.02621], hit=[0.26209, 0.26209], ndcg=[0.12517, 0.12517]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 249 [33.5s + 32.6s]: train==[691.96063=691.94550 + 0.01571], recall=[0.30745, 0.30745], precision=[0.03075, 0.03075], hit=[0.30745, 0.30745], ndcg=[0.16308, 0.16308]
INFO:root:Epoch 259 [32.9s + 33.1s]: train==[691.81903=691.80286 + 0.01572], recall=[0.32815, 0.32815], precision=[0.03281, 0.03281], hit=[0.32815, 0.32815], ndcg=[0.17618, 0.17618]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 269 [33.4s + 32.7s]: train==[691.63458=691.61908 + 0.01574], recall=[0.33841, 0.33841], precision=[0.03384, 0.03384], hit=[0.33841, 0.33841], ndcg=[0.18510, 0.18510]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 279 [33.2s + 33.9s]: train==[691.43237=691.41718 + 0.01576], recall=[0.35745, 0.35745], precision=[0.03575, 0.03575], hit=[0.35745, 0.35745], ndcg=[0.19664, 0.19664]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 39 [112.3s + 32.3s]: train==[690.40637=690.39001 + 0.01580], recall=[0.30050, 0.30050], precision=[0.03005, 0.03005], hit=[0.30050, 0.30050], ndcg=[0.15324, 0.15324]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 289 [32.4s + 33.6s]: train==[691.17279=691.15729 + 0.01579], recall=[0.37550, 0.37550], precision=[0.03755, 0.03755], hit=[0.37550, 0.37550], ndcg=[0.20859, 0.20859]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 299 [33.4s + 34.0s]: train==[691.03772=691.02167 + 0.01582], recall=[0.39868, 0.39868], precision=[0.03987, 0.03987], hit=[0.39868, 0.39868], ndcg=[0.22303, 0.22303]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 309 [33.3s + 34.9s]: train==[690.67511=690.65936 + 0.01585], recall=[0.42053, 0.42053], precision=[0.04205, 0.04205], hit=[0.42053, 0.42053], ndcg=[0.23899, 0.23899]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 49 [112.0s + 32.9s]: train==[690.37604=690.35974 + 0.01578], recall=[0.33543, 0.33543], precision=[0.03354, 0.03354], hit=[0.33543, 0.33543], ndcg=[0.17841, 0.17841]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 319 [32.4s + 39.3s]: train==[690.38849=690.37244 + 0.01589], recall=[0.44007, 0.44007], precision=[0.04401, 0.04401], hit=[0.44007, 0.44007], ndcg=[0.25431, 0.25431]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 329 [34.8s + 31.6s]: train==[689.95386=689.93799 + 0.01593], recall=[0.45977, 0.45977], precision=[0.04598, 0.04598], hit=[0.45977, 0.45977], ndcg=[0.26400, 0.26400]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 339 [32.6s + 31.3s]: train==[689.64026=689.62482 + 0.01597], recall=[0.48228, 0.48228], precision=[0.04823, 0.04823], hit=[0.48228, 0.48228], ndcg=[0.28041, 0.28041]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 349 [33.9s + 31.8s]: train==[689.14526=689.12933 + 0.01603], recall=[0.49321, 0.49321], precision=[0.04932, 0.04932], hit=[0.49321, 0.49321], ndcg=[0.28955, 0.28955]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 59 [112.0s + 33.7s]: train==[690.72974=690.71344 + 0.01577], recall=[0.33990, 0.33990], precision=[0.03399, 0.03399], hit=[0.33990, 0.33990], ndcg=[0.18796, 0.18796]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 359 [33.7s + 31.3s]: train==[688.84180=688.82581 + 0.01609], recall=[0.51722, 0.51722], precision=[0.05172, 0.05172], hit=[0.51722, 0.51722], ndcg=[0.30417, 0.30417]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 369 [34.1s + 32.0s]: train==[688.33612=688.31970 + 0.01615], recall=[0.53675, 0.53675], precision=[0.05368, 0.05368], hit=[0.53675, 0.53675], ndcg=[0.31360, 0.31360]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 379 [32.1s + 32.6s]: train==[687.67700=687.66180 + 0.01622], recall=[0.54255, 0.54255], precision=[0.05425, 0.05425], hit=[0.54255, 0.54255], ndcg=[0.31995, 0.31995]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 389 [32.0s + 32.8s]: train==[687.16010=687.14307 + 0.01630], recall=[0.55861, 0.55861], precision=[0.05586, 0.05586], hit=[0.55861, 0.55861], ndcg=[0.33275, 0.33275]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 69 [112.2s + 32.2s]: train==[690.94470=690.92853 + 0.01575], recall=[0.34520, 0.34520], precision=[0.03452, 0.03452], hit=[0.34520, 0.34520], ndcg=[0.19479, 0.19479]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 399 [31.8s + 31.7s]: train==[686.38586=686.36945 + 0.01639], recall=[0.56871, 0.56871], precision=[0.05687, 0.05687], hit=[0.56871, 0.56871], ndcg=[0.33575, 0.33575]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 409 [33.3s + 31.3s]: train==[685.55542=685.53906 + 0.01648], recall=[0.58162, 0.58162], precision=[0.05816, 0.05816], hit=[0.58162, 0.58162], ndcg=[0.34481, 0.34481]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 419 [33.6s + 32.1s]: train==[684.70087=684.68396 + 0.01658], recall=[0.59338, 0.59338], precision=[0.05934, 0.05934], hit=[0.59338, 0.59338], ndcg=[0.35398, 0.35398]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 79 [112.0s + 32.7s]: train==[691.08807=691.07141 + 0.01573], recall=[0.34272, 0.34272], precision=[0.03427, 0.03427], hit=[0.34272, 0.34272], ndcg=[0.19450, 0.19450]
INFO:root:Epoch 429 [32.5s + 32.7s]: train==[683.89722=683.88068 + 0.01670], recall=[0.59735, 0.59735], precision=[0.05974, 0.05974], hit=[0.59735, 0.59735], ndcg=[0.35223, 0.35223]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 439 [32.7s + 33.7s]: train==[682.78955=682.77344 + 0.01682], recall=[0.60795, 0.60795], precision=[0.06079, 0.06079], hit=[0.60795, 0.60795], ndcg=[0.35728, 0.35728]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 449 [33.0s + 33.7s]: train==[682.03357=682.01636 + 0.01695], recall=[0.60960, 0.60960], precision=[0.06096, 0.06096], hit=[0.60960, 0.60960], ndcg=[0.36154, 0.36154]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 459 [32.7s + 33.0s]: train==[681.13275=681.11615 + 0.01709], recall=[0.61987, 0.61987], precision=[0.06199, 0.06199], hit=[0.61987, 0.61987], ndcg=[0.36467, 0.36467]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 89 [112.6s + 33.8s]: train==[691.32758=691.31213 + 0.01572], recall=[0.34272, 0.34272], precision=[0.03427, 0.03427], hit=[0.34272, 0.34272], ndcg=[0.19278, 0.19278]
INFO:root:Epoch 469 [32.5s + 33.0s]: train==[680.26495=680.24695 + 0.01725], recall=[0.62235, 0.62235], precision=[0.06224, 0.06224], hit=[0.62235, 0.62235], ndcg=[0.36364, 0.36364]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 479 [32.0s + 33.5s]: train==[679.09473=679.07788 + 0.01741], recall=[0.63079, 0.63079], precision=[0.06308, 0.06308], hit=[0.63079, 0.63079], ndcg=[0.37013, 0.37013]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 489 [32.9s + 31.8s]: train==[678.26056=678.24310 + 0.01758], recall=[0.63195, 0.63195], precision=[0.06320, 0.06320], hit=[0.63195, 0.63195], ndcg=[0.37046, 0.37046]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 99 [112.8s + 33.1s]: train==[691.49872=691.48254 + 0.01571], recall=[0.32914, 0.32914], precision=[0.03291, 0.03291], hit=[0.32914, 0.32914], ndcg=[0.18729, 0.18729]
INFO:root:Epoch 499 [34.8s + 32.0s]: train==[677.22748=677.20892 + 0.01777], recall=[0.63146, 0.63146], precision=[0.06315, 0.06315], hit=[0.63146, 0.63146], ndcg=[0.37127, 0.37127]
INFO:root:Epoch 509 [32.2s + 32.6s]: train==[676.08350=676.06610 + 0.01798], recall=[0.63858, 0.63858], precision=[0.06386, 0.06386], hit=[0.63858, 0.63858], ndcg=[0.37122, 0.37122]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 519 [32.3s + 32.6s]: train==[675.09564=675.07758 + 0.01819], recall=[0.64023, 0.64023], precision=[0.06402, 0.06402], hit=[0.64023, 0.64023], ndcg=[0.37352, 0.37352]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 529 [33.6s + 32.8s]: train==[673.85059=673.83289 + 0.01841], recall=[0.63659, 0.63659], precision=[0.06366, 0.06366], hit=[0.63659, 0.63659], ndcg=[0.37233, 0.37233]
INFO:root:Epoch 109 [114.4s + 33.5s]: train==[691.68121=691.66437 + 0.01570], recall=[0.32517, 0.32517], precision=[0.03252, 0.03252], hit=[0.32517, 0.32517], ndcg=[0.18021, 0.18021]
INFO:root:Epoch 539 [34.1s + 32.9s]: train==[673.00519=672.98633 + 0.01866], recall=[0.64702, 0.64702], precision=[0.06470, 0.06470], hit=[0.64702, 0.64702], ndcg=[0.37428, 0.37428]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 549 [32.6s + 32.3s]: train==[671.64081=671.62061 + 0.01890], recall=[0.64570, 0.64570], precision=[0.06457, 0.06457], hit=[0.64570, 0.64570], ndcg=[0.37532, 0.37532]
INFO:root:Epoch 559 [34.4s + 33.4s]: train==[670.68683=670.66772 + 0.01917], recall=[0.64785, 0.64785], precision=[0.06478, 0.06478], hit=[0.64785, 0.64785], ndcg=[0.37885, 0.37885]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 119 [112.6s + 39.2s]: train==[691.80963=691.79462 + 0.01569], recall=[0.31374, 0.31374], precision=[0.03137, 0.03137], hit=[0.31374, 0.31374], ndcg=[0.17344, 0.17344]
INFO:root:Epoch 569 [32.5s + 38.5s]: train==[669.05487=669.03632 + 0.01945], recall=[0.64702, 0.64702], precision=[0.06470, 0.06470], hit=[0.64702, 0.64702], ndcg=[0.37678, 0.37678]
INFO:root:Epoch 579 [32.3s + 32.5s]: train==[668.28668=668.26764 + 0.01974], recall=[0.64487, 0.64487], precision=[0.06449, 0.06449], hit=[0.64487, 0.64487], ndcg=[0.37292, 0.37292]
INFO:root:Epoch 589 [33.8s + 32.7s]: train==[666.76465=666.74402 + 0.02004], recall=[0.64934, 0.64934], precision=[0.06493, 0.06493], hit=[0.64934, 0.64934], ndcg=[0.37675, 0.37675]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 599 [32.4s + 31.7s]: train==[664.91693=664.89606 + 0.02035], recall=[0.65232, 0.65232], precision=[0.06523, 0.06523], hit=[0.65232, 0.65232], ndcg=[0.37675, 0.37675]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 129 [112.4s + 32.3s]: train==[691.93384=691.91748 + 0.01569], recall=[0.30762, 0.30762], precision=[0.03076, 0.03076], hit=[0.30762, 0.30762], ndcg=[0.16883, 0.16883]
INFO:root:Epoch 609 [32.4s + 33.1s]: train==[663.44861=663.42694 + 0.02068], recall=[0.65017, 0.65017], precision=[0.06502, 0.06502], hit=[0.65017, 0.65017], ndcg=[0.37656, 0.37656]
INFO:root:Epoch 619 [34.7s + 34.8s]: train==[662.37781=662.35645 + 0.02103], recall=[0.64636, 0.64636], precision=[0.06464, 0.06464], hit=[0.64636, 0.64636], ndcg=[0.37621, 0.37621]
INFO:root:Epoch 629 [34.4s + 33.1s]: train==[660.29987=660.27893 + 0.02138], recall=[0.64603, 0.64603], precision=[0.06460, 0.06460], hit=[0.64603, 0.64603], ndcg=[0.37424, 0.37424]
INFO:root:Epoch 639 [33.8s + 31.3s]: train==[659.15796=659.13568 + 0.02175], recall=[0.65348, 0.65348], precision=[0.06535, 0.06535], hit=[0.65348, 0.65348], ndcg=[0.37618, 0.37618]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 139 [111.1s + 34.0s]: train==[692.03870=692.02301 + 0.01568], recall=[0.29801, 0.29801], precision=[0.02980, 0.02980], hit=[0.29801, 0.29801], ndcg=[0.16159, 0.16159]
INFO:root:Epoch 649 [33.7s + 32.7s]: train==[657.79211=657.77020 + 0.02213], recall=[0.65199, 0.65199], precision=[0.06520, 0.06520], hit=[0.65199, 0.65199], ndcg=[0.37786, 0.37786]
INFO:root:Epoch 659 [33.8s + 33.6s]: train==[655.86267=655.84064 + 0.02252], recall=[0.65381, 0.65381], precision=[0.06538, 0.06538], hit=[0.65381, 0.65381], ndcg=[0.37895, 0.37895]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 669 [33.8s + 32.6s]: train==[654.40588=654.38269 + 0.02294], recall=[0.65000, 0.65000], precision=[0.06500, 0.06500], hit=[0.65000, 0.65000], ndcg=[0.37663, 0.37663]
INFO:root:Epoch 149 [113.6s + 36.4s]: train==[692.11676=692.10040 + 0.01568], recall=[0.28858, 0.28858], precision=[0.02886, 0.02886], hit=[0.28858, 0.28858], ndcg=[0.15473, 0.15473]
INFO:root:Epoch 679 [36.9s + 34.6s]: train==[652.57257=652.55023 + 0.02334], recall=[0.64967, 0.64967], precision=[0.06497, 0.06497], hit=[0.64967, 0.64967], ndcg=[0.37634, 0.37634]
INFO:root:Epoch 689 [35.9s + 34.3s]: train==[651.00043=650.97699 + 0.02377], recall=[0.65248, 0.65248], precision=[0.06525, 0.06525], hit=[0.65248, 0.65248], ndcg=[0.37835, 0.37835]
INFO:root:Epoch 699 [36.0s + 36.5s]: train==[649.14996=649.12610 + 0.02423], recall=[0.65397, 0.65397], precision=[0.06540, 0.06540], hit=[0.65397, 0.65397], ndcg=[0.37997, 0.37997]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 709 [35.0s + 34.1s]: train==[647.47510=647.45117 + 0.02468], recall=[0.65397, 0.65397], precision=[0.06540, 0.06540], hit=[0.65397, 0.65397], ndcg=[0.37988, 0.37988]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 159 [113.8s + 35.0s]: train==[692.17993=692.16431 + 0.01568], recall=[0.28609, 0.28609], precision=[0.02861, 0.02861], hit=[0.28609, 0.28609], ndcg=[0.15267, 0.15267]
INFO:root:Epoch 719 [33.6s + 33.8s]: train==[645.50848=645.48279 + 0.02515], recall=[0.64983, 0.64983], precision=[0.06498, 0.06498], hit=[0.64983, 0.64983], ndcg=[0.37657, 0.37657]
INFO:root:Epoch 729 [34.3s + 33.7s]: train==[643.52942=643.50342 + 0.02564], recall=[0.65646, 0.65646], precision=[0.06565, 0.06565], hit=[0.65646, 0.65646], ndcg=[0.38137, 0.38137]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 739 [35.6s + 34.5s]: train==[642.00696=641.98029 + 0.02616], recall=[0.65464, 0.65464], precision=[0.06546, 0.06546], hit=[0.65464, 0.65464], ndcg=[0.38104, 0.38104]
INFO:root:Epoch 169 [112.8s + 33.4s]: train==[692.19989=692.18512 + 0.01568], recall=[0.28328, 0.28328], precision=[0.02833, 0.02833], hit=[0.28328, 0.28328], ndcg=[0.15040, 0.15040]
INFO:root:Epoch 749 [35.7s + 33.8s]: train==[640.32495=640.29895 + 0.02667], recall=[0.65050, 0.65050], precision=[0.06505, 0.06505], hit=[0.65050, 0.65050], ndcg=[0.38348, 0.38348]
INFO:root:Epoch 759 [34.2s + 34.4s]: train==[637.96259=637.93549 + 0.02719], recall=[0.65563, 0.65563], precision=[0.06556, 0.06556], hit=[0.65563, 0.65563], ndcg=[0.37862, 0.37862]
INFO:root:Epoch 769 [34.8s + 33.0s]: train==[636.24091=636.21350 + 0.02772], recall=[0.65149, 0.65149], precision=[0.06515, 0.06515], hit=[0.65149, 0.65149], ndcg=[0.37900, 0.37900]
INFO:root:Epoch 779 [33.5s + 32.4s]: train==[634.02594=633.99799 + 0.02829], recall=[0.65298, 0.65298], precision=[0.06530, 0.06530], hit=[0.65298, 0.65298], ndcg=[0.37689, 0.37689]
INFO:root:Epoch 179 [112.4s + 34.0s]: train==[692.18665=692.17120 + 0.01568], recall=[0.28030, 0.28030], precision=[0.02803, 0.02803], hit=[0.28030, 0.28030], ndcg=[0.14660, 0.14660]
INFO:root:Epoch 789 [35.3s + 32.8s]: train==[631.95868=631.92999 + 0.02884], recall=[0.65513, 0.65513], precision=[0.06551, 0.06551], hit=[0.65513, 0.65513], ndcg=[0.37924, 0.37924]
INFO:root:Epoch 799 [35.4s + 33.2s]: train==[630.08313=630.05371 + 0.02940], recall=[0.65232, 0.65232], precision=[0.06523, 0.06523], hit=[0.65232, 0.65232], ndcg=[0.37918, 0.37918]
INFO:root:Epoch 809 [33.7s + 34.0s]: train==[627.94373=627.91351 + 0.03001], recall=[0.65679, 0.65679], precision=[0.06568, 0.06568], hit=[0.65679, 0.65679], ndcg=[0.38046, 0.38046]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 189 [112.4s + 34.3s]: train==[692.21625=692.20087 + 0.01568], recall=[0.27566, 0.27566], precision=[0.02757, 0.02757], hit=[0.27566, 0.27566], ndcg=[0.14527, 0.14527]
INFO:root:Epoch 819 [34.6s + 33.0s]: train==[626.40497=626.37451 + 0.03063], recall=[0.65315, 0.65315], precision=[0.06531, 0.06531], hit=[0.65315, 0.65315], ndcg=[0.37929, 0.37929]
INFO:root:Epoch 829 [35.0s + 32.7s]: train==[623.46997=623.43811 + 0.03121], recall=[0.65679, 0.65679], precision=[0.06568, 0.06568], hit=[0.65679, 0.65679], ndcg=[0.38151, 0.38151]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 839 [34.6s + 33.4s]: train==[621.25055=621.21844 + 0.03186], recall=[0.65099, 0.65099], precision=[0.06510, 0.06510], hit=[0.65099, 0.65099], ndcg=[0.38045, 0.38045]
INFO:root:Epoch 849 [32.3s + 33.5s]: train==[619.45117=619.41803 + 0.03250], recall=[0.65281, 0.65281], precision=[0.06528, 0.06528], hit=[0.65281, 0.65281], ndcg=[0.38151, 0.38151]
INFO:root:Epoch 199 [113.3s + 33.1s]: train==[692.19446=692.17780 + 0.01568], recall=[0.27632, 0.27632], precision=[0.02763, 0.02763], hit=[0.27632, 0.27632], ndcg=[0.14592, 0.14592]
INFO:root:Epoch 859 [34.0s + 33.7s]: train==[617.12933=617.09521 + 0.03315], recall=[0.65464, 0.65464], precision=[0.06546, 0.06546], hit=[0.65464, 0.65464], ndcg=[0.38208, 0.38208]
INFO:root:Epoch 869 [33.8s + 33.5s]: train==[614.72504=614.69147 + 0.03380], recall=[0.65232, 0.65232], precision=[0.06523, 0.06523], hit=[0.65232, 0.65232], ndcg=[0.37712, 0.37712]
INFO:root:Epoch 879 [34.2s + 32.7s]: train==[612.84021=612.80585 + 0.03451], recall=[0.65265, 0.65265], precision=[0.06526, 0.06526], hit=[0.65265, 0.65265], ndcg=[0.38237, 0.38237]
INFO:root:Epoch 209 [113.6s + 34.8s]: train==[692.14825=692.13251 + 0.01569], recall=[0.28212, 0.28212], precision=[0.02821, 0.02821], hit=[0.28212, 0.28212], ndcg=[0.14821, 0.14821]
INFO:root:Epoch 889 [36.2s + 33.2s]: train==[610.52991=610.49548 + 0.03518], recall=[0.65811, 0.65811], precision=[0.06581, 0.06581], hit=[0.65811, 0.65811], ndcg=[0.38106, 0.38106]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 899 [33.8s + 33.5s]: train==[608.69653=608.66052 + 0.03589], recall=[0.65679, 0.65679], precision=[0.06568, 0.06568], hit=[0.65679, 0.65679], ndcg=[0.38210, 0.38210]
INFO:root:Epoch 909 [33.1s + 33.3s]: train==[606.00616=605.96918 + 0.03662], recall=[0.66010, 0.66010], precision=[0.06601, 0.06601], hit=[0.66010, 0.66010], ndcg=[0.38427, 0.38427]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 919 [33.2s + 33.1s]: train==[603.74609=603.70886 + 0.03733], recall=[0.65116, 0.65116], precision=[0.06512, 0.06512], hit=[0.65116, 0.65116], ndcg=[0.37856, 0.37856]
INFO:root:Epoch 219 [113.9s + 34.9s]: train==[692.10187=692.08740 + 0.01570], recall=[0.28411, 0.28411], precision=[0.02841, 0.02841], hit=[0.28411, 0.28411], ndcg=[0.15006, 0.15006]
INFO:root:Epoch 929 [34.0s + 32.9s]: train==[601.75586=601.71881 + 0.03808], recall=[0.65728, 0.65728], precision=[0.06573, 0.06573], hit=[0.65728, 0.65728], ndcg=[0.38125, 0.38125]
INFO:root:Epoch 939 [34.4s + 34.0s]: train==[599.60071=599.56201 + 0.03884], recall=[0.65629, 0.65629], precision=[0.06563, 0.06563], hit=[0.65629, 0.65629], ndcg=[0.38217, 0.38217]
INFO:root:Epoch 949 [32.8s + 32.4s]: train==[596.33313=596.29382 + 0.03961], recall=[0.65712, 0.65712], precision=[0.06571, 0.06571], hit=[0.65712, 0.65712], ndcg=[0.37999, 0.37999]
INFO:root:Epoch 229 [113.1s + 33.2s]: train==[691.99652=691.98029 + 0.01571], recall=[0.28841, 0.28841], precision=[0.02884, 0.02884], hit=[0.28841, 0.28841], ndcg=[0.15356, 0.15356]
INFO:root:Epoch 959 [32.1s + 33.1s]: train==[595.24536=595.20477 + 0.04042], recall=[0.65397, 0.65397], precision=[0.06540, 0.06540], hit=[0.65397, 0.65397], ndcg=[0.37949, 0.37949]
INFO:root:Epoch 969 [33.9s + 32.7s]: train==[591.39905=591.35876 + 0.04114], recall=[0.65712, 0.65712], precision=[0.06571, 0.06571], hit=[0.65712, 0.65712], ndcg=[0.37876, 0.37876]
INFO:root:Epoch 979 [33.2s + 32.7s]: train==[588.95319=588.91132 + 0.04198], recall=[0.65695, 0.65695], precision=[0.06570, 0.06570], hit=[0.65695, 0.65695], ndcg=[0.38036, 0.38036]
INFO:root:Epoch 989 [36.0s + 33.5s]: train==[587.66675=587.62384 + 0.04282], recall=[0.65844, 0.65844], precision=[0.06584, 0.06584], hit=[0.65844, 0.65844], ndcg=[0.38297, 0.38297]
INFO:root:Epoch 239 [112.6s + 33.6s]: train==[691.95776=691.94232 + 0.01572], recall=[0.29553, 0.29553], precision=[0.02955, 0.02955], hit=[0.29553, 0.29553], ndcg=[0.15610, 0.15610]
INFO:root:Epoch 999 [35.2s + 33.1s]: train==[584.10095=584.05737 + 0.04361], recall=[0.65464, 0.65464], precision=[0.06546, 0.06546], hit=[0.65464, 0.65464], ndcg=[0.38063, 0.38063]
INFO:root:Epoch 1009 [33.9s + 32.5s]: train==[581.64923=581.60455 + 0.04447], recall=[0.65480, 0.65480], precision=[0.06548, 0.06548], hit=[0.65480, 0.65480], ndcg=[0.38122, 0.38122]
INFO:root:Epoch 1019 [32.9s + 35.0s]: train==[580.27417=580.22870 + 0.04531], recall=[0.65977, 0.65977], precision=[0.06598, 0.06598], hit=[0.65977, 0.65977], ndcg=[0.38349, 0.38349]
INFO:root:Epoch 249 [114.1s + 32.5s]: train==[691.81866=691.80322 + 0.01573], recall=[0.31010, 0.31010], precision=[0.03101, 0.03101], hit=[0.31010, 0.31010], ndcg=[0.16322, 0.16322]
INFO:root:Epoch 1029 [35.8s + 33.6s]: train==[577.12366=577.07782 + 0.04621], recall=[0.65828, 0.65828], precision=[0.06583, 0.06583], hit=[0.65828, 0.65828], ndcg=[0.38343, 0.38343]
INFO:root:Epoch 1039 [35.1s + 33.2s]: train==[574.21985=574.17291 + 0.04706], recall=[0.66407, 0.66407], precision=[0.06641, 0.06641], hit=[0.66407, 0.66407], ndcg=[0.38542, 0.38542]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1049 [35.6s + 34.4s]: train==[571.67493=571.62646 + 0.04796], recall=[0.65563, 0.65563], precision=[0.06556, 0.06556], hit=[0.65563, 0.65563], ndcg=[0.38097, 0.38097]
INFO:root:Epoch 1059 [34.5s + 33.4s]: train==[569.64862=569.59949 + 0.04887], recall=[0.65281, 0.65281], precision=[0.06528, 0.06528], hit=[0.65281, 0.65281], ndcg=[0.37785, 0.37785]
INFO:root:Epoch 259 [112.8s + 34.7s]: train==[691.69000=691.67444 + 0.01575], recall=[0.31689, 0.31689], precision=[0.03169, 0.03169], hit=[0.31689, 0.31689], ndcg=[0.17093, 0.17093]
INFO:root:Epoch 1069 [34.7s + 33.2s]: train==[566.86652=566.81689 + 0.04981], recall=[0.65364, 0.65364], precision=[0.06536, 0.06536], hit=[0.65364, 0.65364], ndcg=[0.37930, 0.37930]
INFO:root:Epoch 1079 [35.4s + 33.2s]: train==[564.84528=564.79498 + 0.05067], recall=[0.65546, 0.65546], precision=[0.06555, 0.06555], hit=[0.65546, 0.65546], ndcg=[0.38060, 0.38060]
INFO:root:Epoch 1089 [33.4s + 33.0s]: train==[563.63391=563.58167 + 0.05171], recall=[0.65546, 0.65546], precision=[0.06555, 0.06555], hit=[0.65546, 0.65546], ndcg=[0.38102, 0.38102]
INFO:root:Epoch 269 [113.3s + 34.9s]: train==[691.52429=691.50854 + 0.01577], recall=[0.32831, 0.32831], precision=[0.03283, 0.03283], hit=[0.32831, 0.32831], ndcg=[0.17914, 0.17914]
INFO:root:Epoch 1099 [36.3s + 33.8s]: train==[559.92871=559.87598 + 0.05263], recall=[0.65828, 0.65828], precision=[0.06583, 0.06583], hit=[0.65828, 0.65828], ndcg=[0.37960, 0.37960]
INFO:root:Epoch 1109 [33.9s + 33.8s]: train==[556.08478=556.03137 + 0.05353], recall=[0.66093, 0.66093], precision=[0.06609, 0.06609], hit=[0.66093, 0.66093], ndcg=[0.37900, 0.37900]
INFO:root:Epoch 1119 [33.8s + 33.8s]: train==[555.92352=555.86835 + 0.05461], recall=[0.65613, 0.65613], precision=[0.06561, 0.06561], hit=[0.65613, 0.65613], ndcg=[0.38063, 0.38063]
INFO:root:Epoch 1129 [33.9s + 33.6s]: train==[551.12494=551.06946 + 0.05552], recall=[0.65877, 0.65877], precision=[0.06588, 0.06588], hit=[0.65877, 0.65877], ndcg=[0.38118, 0.38118]
INFO:root:Epoch 279 [113.4s + 32.1s]: train==[691.31274=691.29620 + 0.01579], recall=[0.34338, 0.34338], precision=[0.03434, 0.03434], hit=[0.34338, 0.34338], ndcg=[0.19102, 0.19102]
INFO:root:Epoch 1139 [32.3s + 30.5s]: train==[550.17676=550.11981 + 0.05657], recall=[0.65795, 0.65795], precision=[0.06579, 0.06579], hit=[0.65795, 0.65795], ndcg=[0.38219, 0.38219]
INFO:root:Epoch 1149 [32.8s + 32.0s]: train==[547.76233=547.70502 + 0.05758], recall=[0.65116, 0.65116], precision=[0.06512, 0.06512], hit=[0.65116, 0.65116], ndcg=[0.37848, 0.37848]
INFO:root:Epoch 1159 [34.1s + 33.4s]: train==[546.78223=546.72382 + 0.05863], recall=[0.65762, 0.65762], precision=[0.06576, 0.06576], hit=[0.65762, 0.65762], ndcg=[0.38346, 0.38346]
INFO:root:Epoch 289 [111.6s + 32.3s]: train==[691.06256=691.04584 + 0.01582], recall=[0.35944, 0.35944], precision=[0.03594, 0.03594], hit=[0.35944, 0.35944], ndcg=[0.19846, 0.19846]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1169 [32.9s + 33.5s]: train==[545.01337=544.95392 + 0.05970], recall=[0.65613, 0.65613], precision=[0.06561, 0.06561], hit=[0.65613, 0.65613], ndcg=[0.38521, 0.38521]
INFO:root:Epoch 1179 [31.4s + 32.9s]: train==[542.24823=542.18781 + 0.06070], recall=[0.66374, 0.66374], precision=[0.06637, 0.06637], hit=[0.66374, 0.66374], ndcg=[0.37947, 0.37947]
INFO:root:Epoch 1189 [33.5s + 33.1s]: train==[539.11334=539.05170 + 0.06181], recall=[0.65911, 0.65911], precision=[0.06591, 0.06591], hit=[0.65911, 0.65911], ndcg=[0.38053, 0.38053]
INFO:root:Epoch 1199 [33.2s + 32.0s]: train==[537.29626=537.23358 + 0.06288], recall=[0.66026, 0.66026], precision=[0.06603, 0.06603], hit=[0.66026, 0.66026], ndcg=[0.37971, 0.37971]
INFO:root:Epoch 299 [111.0s + 30.9s]: train==[690.90375=690.88782 + 0.01585], recall=[0.37351, 0.37351], precision=[0.03735, 0.03735], hit=[0.37351, 0.37351], ndcg=[0.21413, 0.21413]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1209 [32.2s + 30.9s]: train==[534.91974=534.85590 + 0.06400], recall=[0.65629, 0.65629], precision=[0.06563, 0.06563], hit=[0.65629, 0.65629], ndcg=[0.38037, 0.38037]
INFO:root:Epoch 1219 [31.6s + 31.8s]: train==[531.31268=531.24786 + 0.06502], recall=[0.65480, 0.65480], precision=[0.06548, 0.06548], hit=[0.65480, 0.65480], ndcg=[0.38064, 0.38064]
INFO:root:Epoch 1229 [32.8s + 32.8s]: train==[530.13971=530.07379 + 0.06614], recall=[0.65596, 0.65596], precision=[0.06560, 0.06560], hit=[0.65596, 0.65596], ndcg=[0.37927, 0.37927]
INFO:root:Epoch 1239 [30.9s + 31.6s]: train==[528.13947=528.07220 + 0.06732], recall=[0.65298, 0.65298], precision=[0.06530, 0.06530], hit=[0.65298, 0.65298], ndcg=[0.37870, 0.37870]
INFO:root:Best Iter=[103]@[37942.2]	recall=[0.66407], precision=[0.06641], hit=[0.66407], ndcg=[0.38542]
INFO:root:Epoch 309 [109.7s + 31.2s]: train==[690.59766=690.58130 + 0.01589], recall=[0.39321, 0.39321], precision=[0.03932, 0.03932], hit=[0.39321, 0.39321], ndcg=[0.22502, 0.22502]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 319 [110.4s + 30.2s]: train==[690.28577=690.26996 + 0.01592], recall=[0.41325, 0.41325], precision=[0.04132, 0.04132], hit=[0.41325, 0.41325], ndcg=[0.23799, 0.23799]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 329 [109.5s + 31.4s]: train==[690.08130=690.06543 + 0.01597], recall=[0.42897, 0.42897], precision=[0.04290, 0.04290], hit=[0.42897, 0.42897], ndcg=[0.25297, 0.25297]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 339 [109.1s + 31.3s]: train==[689.55389=689.53802 + 0.01602], recall=[0.45464, 0.45464], precision=[0.04546, 0.04546], hit=[0.45464, 0.45464], ndcg=[0.26539, 0.26539]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 349 [110.4s + 31.4s]: train==[689.18005=689.16327 + 0.01607], recall=[0.47301, 0.47301], precision=[0.04730, 0.04730], hit=[0.47301, 0.47301], ndcg=[0.27696, 0.27696]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 359 [109.8s + 29.6s]: train==[688.68530=688.66895 + 0.01613], recall=[0.49056, 0.49056], precision=[0.04906, 0.04906], hit=[0.49056, 0.49056], ndcg=[0.28820, 0.28820]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 369 [111.1s + 30.3s]: train==[688.30261=688.28632 + 0.01619], recall=[0.50298, 0.50298], precision=[0.05030, 0.05030], hit=[0.50298, 0.50298], ndcg=[0.29964, 0.29964]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 379 [109.6s + 31.3s]: train==[687.56787=687.55127 + 0.01627], recall=[0.51937, 0.51937], precision=[0.05194, 0.05194], hit=[0.51937, 0.51937], ndcg=[0.31076, 0.31076]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 389 [110.0s + 32.4s]: train==[687.03375=687.01746 + 0.01635], recall=[0.54106, 0.54106], precision=[0.05411, 0.05411], hit=[0.54106, 0.54106], ndcg=[0.32057, 0.32057]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 399 [109.3s + 31.0s]: train==[686.38031=686.36322 + 0.01643], recall=[0.55050, 0.55050], precision=[0.05505, 0.05505], hit=[0.55050, 0.55050], ndcg=[0.32516, 0.32516]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 409 [109.8s + 30.9s]: train==[685.56744=685.55139 + 0.01653], recall=[0.55762, 0.55762], precision=[0.05576, 0.05576], hit=[0.55762, 0.55762], ndcg=[0.32939, 0.32939]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 419 [108.9s + 31.5s]: train==[684.61902=684.60327 + 0.01663], recall=[0.57036, 0.57036], precision=[0.05704, 0.05704], hit=[0.57036, 0.57036], ndcg=[0.33597, 0.33597]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 429 [108.7s + 32.1s]: train==[683.90552=683.88843 + 0.01675], recall=[0.57765, 0.57765], precision=[0.05776, 0.05776], hit=[0.57765, 0.57765], ndcg=[0.34276, 0.34276]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 439 [109.7s + 28.1s]: train==[683.40802=683.39160 + 0.01687], recall=[0.59007, 0.59007], precision=[0.05901, 0.05901], hit=[0.59007, 0.59007], ndcg=[0.34699, 0.34699]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 449 [109.8s + 29.6s]: train==[682.42371=682.40674 + 0.01700], recall=[0.59735, 0.59735], precision=[0.05974, 0.05974], hit=[0.59735, 0.59735], ndcg=[0.35196, 0.35196]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 459 [108.9s + 31.4s]: train==[681.52502=681.50739 + 0.01715], recall=[0.60563, 0.60563], precision=[0.06056, 0.06056], hit=[0.60563, 0.60563], ndcg=[0.35866, 0.35866]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 469 [109.9s + 29.8s]: train==[680.75281=680.73651 + 0.01730], recall=[0.60679, 0.60679], precision=[0.06068, 0.06068], hit=[0.60679, 0.60679], ndcg=[0.35783, 0.35783]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 479 [109.1s + 30.4s]: train==[679.86725=679.85071 + 0.01747], recall=[0.61573, 0.61573], precision=[0.06157, 0.06157], hit=[0.61573, 0.61573], ndcg=[0.35954, 0.35954]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 489 [108.9s + 31.6s]: train==[679.06287=679.04517 + 0.01765], recall=[0.62334, 0.62334], precision=[0.06233, 0.06233], hit=[0.62334, 0.62334], ndcg=[0.36575, 0.36575]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 499 [110.4s + 31.3s]: train==[678.24316=678.22510 + 0.01783], recall=[0.62268, 0.62268], precision=[0.06227, 0.06227], hit=[0.62268, 0.62268], ndcg=[0.36617, 0.36617]
INFO:root:Epoch 509 [109.3s + 30.8s]: train==[677.08771=677.06982 + 0.01804], recall=[0.62748, 0.62748], precision=[0.06275, 0.06275], hit=[0.62748, 0.62748], ndcg=[0.36578, 0.36578]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 519 [110.2s + 32.4s]: train==[676.08679=676.06854 + 0.01825], recall=[0.63046, 0.63046], precision=[0.06305, 0.06305], hit=[0.63046, 0.63046], ndcg=[0.36562, 0.36562]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 529 [109.5s + 30.9s]: train==[675.21881=675.19989 + 0.01848], recall=[0.63593, 0.63593], precision=[0.06359, 0.06359], hit=[0.63593, 0.63593], ndcg=[0.36747, 0.36747]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 539 [109.6s + 31.7s]: train==[673.68762=673.66968 + 0.01872], recall=[0.63560, 0.63560], precision=[0.06356, 0.06356], hit=[0.63560, 0.63560], ndcg=[0.36815, 0.36815]
INFO:root:Epoch 549 [110.2s + 29.8s]: train==[672.95587=672.93823 + 0.01897], recall=[0.64272, 0.64272], precision=[0.06427, 0.06427], hit=[0.64272, 0.64272], ndcg=[0.37292, 0.37292]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 559 [109.6s + 30.3s]: train==[672.00543=671.98669 + 0.01924], recall=[0.64503, 0.64503], precision=[0.06450, 0.06450], hit=[0.64503, 0.64503], ndcg=[0.37435, 0.37435]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 569 [110.8s + 31.2s]: train==[670.81311=670.79382 + 0.01952], recall=[0.63659, 0.63659], precision=[0.06366, 0.06366], hit=[0.63659, 0.63659], ndcg=[0.37029, 0.37029]
INFO:root:Epoch 579 [109.6s + 29.7s]: train==[668.99200=668.97180 + 0.01981], recall=[0.64139, 0.64139], precision=[0.06414, 0.06414], hit=[0.64139, 0.64139], ndcg=[0.37424, 0.37424]
INFO:root:Epoch 589 [109.2s + 32.0s]: train==[667.97620=667.95667 + 0.02011], recall=[0.64387, 0.64387], precision=[0.06439, 0.06439], hit=[0.64387, 0.64387], ndcg=[0.37203, 0.37203]
INFO:root:Epoch 599 [111.1s + 32.5s]: train==[666.62109=666.60114 + 0.02043], recall=[0.64834, 0.64834], precision=[0.06483, 0.06483], hit=[0.64834, 0.64834], ndcg=[0.37829, 0.37829]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 609 [109.7s + 31.5s]: train==[665.53906=665.51831 + 0.02077], recall=[0.64950, 0.64950], precision=[0.06495, 0.06495], hit=[0.64950, 0.64950], ndcg=[0.37538, 0.37538]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 619 [110.1s + 30.5s]: train==[664.10986=664.08875 + 0.02110], recall=[0.64851, 0.64851], precision=[0.06485, 0.06485], hit=[0.64851, 0.64851], ndcg=[0.37276, 0.37276]
INFO:root:Epoch 629 [111.2s + 29.8s]: train==[662.41443=662.39288 + 0.02146], recall=[0.64868, 0.64868], precision=[0.06487, 0.06487], hit=[0.64868, 0.64868], ndcg=[0.37600, 0.37600]
INFO:root:Epoch 639 [109.3s + 28.6s]: train==[660.26221=660.24127 + 0.02182], recall=[0.64801, 0.64801], precision=[0.06480, 0.06480], hit=[0.64801, 0.64801], ndcg=[0.37780, 0.37780]
INFO:root:Epoch 649 [110.7s + 31.8s]: train==[659.04932=659.02698 + 0.02220], recall=[0.65613, 0.65613], precision=[0.06561, 0.06561], hit=[0.65613, 0.65613], ndcg=[0.38088, 0.38088]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 659 [109.9s + 30.0s]: train==[657.70227=657.67993 + 0.02259], recall=[0.65348, 0.65348], precision=[0.06535, 0.06535], hit=[0.65348, 0.65348], ndcg=[0.37953, 0.37953]
INFO:root:Epoch 669 [111.5s + 29.6s]: train==[656.50470=656.48114 + 0.02302], recall=[0.65348, 0.65348], precision=[0.06535, 0.06535], hit=[0.65348, 0.65348], ndcg=[0.37824, 0.37824]
INFO:root:Epoch 679 [109.3s + 29.8s]: train==[655.15277=655.12921 + 0.02344], recall=[0.65646, 0.65646], precision=[0.06565, 0.06565], hit=[0.65646, 0.65646], ndcg=[0.37725, 0.37725]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 689 [109.6s + 30.1s]: train==[652.81183=652.78729 + 0.02385], recall=[0.65116, 0.65116], precision=[0.06512, 0.06512], hit=[0.65116, 0.65116], ndcg=[0.37913, 0.37913]
INFO:root:Epoch 699 [109.5s + 27.7s]: train==[651.67883=651.65436 + 0.02431], recall=[0.65728, 0.65728], precision=[0.06573, 0.06573], hit=[0.65728, 0.65728], ndcg=[0.37990, 0.37990]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Namespace(Ks='[10]', batch_size=64, data_path='./data/recommendation/', dataset='ml-1m', embed_size=128, epoch=2000, gpu=2, item_density_threshold=0.01, item_threshold=30, layer_size=[128], lmbda=1, local_batch_size=512, local_epoch=1, log_name='run4_1', log_path='/home/qhuaf/graph_pri/logs/', lr=0.0001, mess_dropout=[0.1, 0.1, 0.1], model_name='two_side_graph_run4_1.pkl', num_neighbor=10, num_process=4, pretrain_epoch=300, pri_epoch=200, privacy_protect=False, regs=[1e-05], report=0, save_flag=1, test_flag='part', user_batch_size=512, verbose=1, weights_path='model/')
INFO:root:Epoch 709 [112.5s + 32.2s]: train==[649.87677=649.85168 + 0.02476], recall=[0.65447, 0.65447], precision=[0.06545, 0.06545], hit=[0.65447, 0.65447], ndcg=[0.37805, 0.37805]
INFO:root:Epoch 9 [108.6s + 32.8s]: train==[693.06708=693.05060 + 0.01583], recall=[0.20646, 0.20646], precision=[0.02065, 0.02065], hit=[0.20646, 0.20646], ndcg=[0.09136, 0.09136]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 719 [112.1s + 31.7s]: train==[647.91705=647.89313 + 0.02523], recall=[0.65563, 0.65563], precision=[0.06556, 0.06556], hit=[0.65563, 0.65563], ndcg=[0.38047, 0.38047]
INFO:root:Epoch 19 [108.9s + 33.3s]: train==[692.34436=692.32947 + 0.01582], recall=[0.23162, 0.23162], precision=[0.02316, 0.02316], hit=[0.23162, 0.23162], ndcg=[0.10386, 0.10386]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 729 [111.4s + 31.9s]: train==[646.24597=646.21906 + 0.02573], recall=[0.65844, 0.65844], precision=[0.06584, 0.06584], hit=[0.65844, 0.65844], ndcg=[0.37978, 0.37978]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 29 [108.4s + 34.1s]: train==[691.45148=691.43555 + 0.01580], recall=[0.26606, 0.26606], precision=[0.02661, 0.02661], hit=[0.26606, 0.26606], ndcg=[0.12435, 0.12435]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 739 [111.5s + 32.3s]: train==[643.97266=643.94672 + 0.02622], recall=[0.65116, 0.65116], precision=[0.06512, 0.06512], hit=[0.65116, 0.65116], ndcg=[0.37675, 0.37675]
INFO:root:Epoch 39 [109.0s + 33.5s]: train==[690.78381=690.76788 + 0.01579], recall=[0.30480, 0.30480], precision=[0.03048, 0.03048], hit=[0.30480, 0.30480], ndcg=[0.15233, 0.15233]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 749 [111.3s + 31.7s]: train==[642.26361=642.23706 + 0.02674], recall=[0.65745, 0.65745], precision=[0.06575, 0.06575], hit=[0.65745, 0.65745], ndcg=[0.38012, 0.38012]
INFO:root:Epoch 49 [109.0s + 34.3s]: train==[690.81342=690.79712 + 0.01577], recall=[0.33179, 0.33179], precision=[0.03318, 0.03318], hit=[0.33179, 0.33179], ndcg=[0.17237, 0.17237]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 759 [111.0s + 31.5s]: train==[640.47931=640.45306 + 0.02727], recall=[0.65364, 0.65364], precision=[0.06536, 0.06536], hit=[0.65364, 0.65364], ndcg=[0.37852, 0.37852]
INFO:root:Epoch 59 [109.0s + 34.0s]: train==[691.03363=691.01733 + 0.01575], recall=[0.33477, 0.33477], precision=[0.03348, 0.03348], hit=[0.33477, 0.33477], ndcg=[0.18163, 0.18163]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 769 [111.7s + 31.4s]: train==[638.34412=638.31586 + 0.02779], recall=[0.65596, 0.65596], precision=[0.06560, 0.06560], hit=[0.65596, 0.65596], ndcg=[0.37850, 0.37850]
INFO:root:Epoch 69 [109.2s + 34.4s]: train==[691.15521=691.13959 + 0.01573], recall=[0.35083, 0.35083], precision=[0.03508, 0.03508], hit=[0.35083, 0.35083], ndcg=[0.19324, 0.19324]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 779 [111.8s + 32.4s]: train==[636.85205=636.82410 + 0.02835], recall=[0.65199, 0.65199], precision=[0.06520, 0.06520], hit=[0.65199, 0.65199], ndcg=[0.37823, 0.37823]
INFO:root:Epoch 79 [109.6s + 33.1s]: train==[691.31458=691.29846 + 0.01571], recall=[0.35066, 0.35066], precision=[0.03507, 0.03507], hit=[0.35066, 0.35066], ndcg=[0.19287, 0.19287]
INFO:root:Epoch 789 [111.1s + 31.8s]: train==[634.70105=634.67200 + 0.02891], recall=[0.65513, 0.65513], precision=[0.06551, 0.06551], hit=[0.65513, 0.65513], ndcg=[0.37927, 0.37927]
INFO:root:Epoch 89 [109.7s + 33.2s]: train==[691.45880=691.44354 + 0.01570], recall=[0.33974, 0.33974], precision=[0.03397, 0.03397], hit=[0.33974, 0.33974], ndcg=[0.18939, 0.18939]
INFO:root:Epoch 799 [111.5s + 31.9s]: train==[633.40021=633.37115 + 0.02949], recall=[0.65778, 0.65778], precision=[0.06578, 0.06578], hit=[0.65778, 0.65778], ndcg=[0.38045, 0.38045]
INFO:root:Epoch 99 [110.1s + 33.4s]: train==[691.64600=691.63025 + 0.01569], recall=[0.33212, 0.33212], precision=[0.03321, 0.03321], hit=[0.33212, 0.33212], ndcg=[0.18488, 0.18488]
INFO:root:Epoch 809 [111.8s + 33.0s]: train==[630.48889=630.45923 + 0.03006], recall=[0.66060, 0.66060], precision=[0.06606, 0.06606], hit=[0.66060, 0.66060], ndcg=[0.38368, 0.38368]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 109 [109.2s + 33.8s]: train==[691.74603=691.73138 + 0.01568], recall=[0.32417, 0.32417], precision=[0.03242, 0.03242], hit=[0.32417, 0.32417], ndcg=[0.17832, 0.17832]
INFO:root:Epoch 819 [111.2s + 32.0s]: train==[628.92517=628.89417 + 0.03068], recall=[0.65795, 0.65795], precision=[0.06579, 0.06579], hit=[0.65795, 0.65795], ndcg=[0.37745, 0.37745]
INFO:root:Epoch 119 [109.3s + 33.8s]: train==[691.88599=691.86981 + 0.01567], recall=[0.30927, 0.30927], precision=[0.03093, 0.03093], hit=[0.30927, 0.30927], ndcg=[0.17019, 0.17019]
INFO:root:Epoch 829 [111.4s + 31.6s]: train==[626.52386=626.49274 + 0.03126], recall=[0.65000, 0.65000], precision=[0.06500, 0.06500], hit=[0.65000, 0.65000], ndcg=[0.37612, 0.37612]
INFO:root:Epoch 129 [109.3s + 33.7s]: train==[692.00012=691.98505 + 0.01567], recall=[0.30281, 0.30281], precision=[0.03028, 0.03028], hit=[0.30281, 0.30281], ndcg=[0.16518, 0.16518]
INFO:root:Epoch 839 [111.4s + 32.2s]: train==[624.29474=624.26208 + 0.03190], recall=[0.65364, 0.65364], precision=[0.06536, 0.06536], hit=[0.65364, 0.65364], ndcg=[0.37767, 0.37767]
INFO:root:Epoch 139 [108.7s + 33.8s]: train==[692.05890=692.04303 + 0.01566], recall=[0.29884, 0.29884], precision=[0.02988, 0.02988], hit=[0.29884, 0.29884], ndcg=[0.16150, 0.16150]
INFO:root:Epoch 849 [111.2s + 31.9s]: train==[622.17578=622.14258 + 0.03255], recall=[0.65993, 0.65993], precision=[0.06599, 0.06599], hit=[0.65993, 0.65993], ndcg=[0.38088, 0.38088]
INFO:root:Epoch 149 [109.0s + 32.5s]: train==[692.14075=692.12512 + 0.01566], recall=[0.28907, 0.28907], precision=[0.02891, 0.02891], hit=[0.28907, 0.28907], ndcg=[0.15479, 0.15479]
INFO:root:Epoch 859 [111.9s + 32.2s]: train==[620.61993=620.58624 + 0.03319], recall=[0.66474, 0.66474], precision=[0.06647, 0.06647], hit=[0.66474, 0.66474], ndcg=[0.38321, 0.38321]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 159 [109.4s + 34.0s]: train==[692.19952=692.18359 + 0.01565], recall=[0.28162, 0.28162], precision=[0.02816, 0.02816], hit=[0.28162, 0.28162], ndcg=[0.15066, 0.15066]
INFO:root:Epoch 869 [111.8s + 31.8s]: train==[618.20166=618.16827 + 0.03386], recall=[0.65596, 0.65596], precision=[0.06560, 0.06560], hit=[0.65596, 0.65596], ndcg=[0.37912, 0.37912]
INFO:root:Epoch 169 [109.4s + 33.8s]: train==[692.20782=692.19287 + 0.01565], recall=[0.28146, 0.28146], precision=[0.02815, 0.02815], hit=[0.28146, 0.28146], ndcg=[0.14865, 0.14865]
INFO:root:Epoch 879 [111.3s + 32.4s]: train==[615.75574=615.72083 + 0.03451], recall=[0.66275, 0.66275], precision=[0.06627, 0.06627], hit=[0.66275, 0.66275], ndcg=[0.38295, 0.38295]
INFO:root:Epoch 179 [109.5s + 33.3s]: train==[692.22119=692.20630 + 0.01565], recall=[0.27748, 0.27748], precision=[0.02775, 0.02775], hit=[0.27748, 0.27748], ndcg=[0.14566, 0.14566]
INFO:root:Epoch 889 [111.4s + 31.5s]: train==[613.80090=613.76538 + 0.03521], recall=[0.65315, 0.65315], precision=[0.06531, 0.06531], hit=[0.65315, 0.65315], ndcg=[0.38135, 0.38135]
INFO:root:Epoch 189 [109.5s + 33.5s]: train==[692.19238=692.17670 + 0.01566], recall=[0.27864, 0.27864], precision=[0.02786, 0.02786], hit=[0.27864, 0.27864], ndcg=[0.14663, 0.14663]
INFO:root:Epoch 899 [111.4s + 32.0s]: train==[612.27325=612.23767 + 0.03594], recall=[0.66474, 0.66474], precision=[0.06647, 0.06647], hit=[0.66474, 0.66474], ndcg=[0.38237, 0.38237]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 199 [110.1s + 33.6s]: train==[692.15912=692.14319 + 0.01566], recall=[0.28046, 0.28046], precision=[0.02805, 0.02805], hit=[0.28046, 0.28046], ndcg=[0.14800, 0.14800]
INFO:root:Epoch 909 [111.4s + 31.9s]: train==[608.84619=608.80896 + 0.03661], recall=[0.65430, 0.65430], precision=[0.06543, 0.06543], hit=[0.65430, 0.65430], ndcg=[0.37923, 0.37923]
INFO:root:Epoch 209 [109.9s + 33.6s]: train==[692.15729=692.14233 + 0.01566], recall=[0.28642, 0.28642], precision=[0.02864, 0.02864], hit=[0.28642, 0.28642], ndcg=[0.14789, 0.14789]
INFO:root:Epoch 919 [111.2s + 32.2s]: train==[607.06561=607.02924 + 0.03734], recall=[0.65497, 0.65497], precision=[0.06550, 0.06550], hit=[0.65497, 0.65497], ndcg=[0.38007, 0.38007]
INFO:root:Epoch 219 [109.7s + 32.1s]: train==[692.10138=692.08539 + 0.01567], recall=[0.28758, 0.28758], precision=[0.02876, 0.02876], hit=[0.28758, 0.28758], ndcg=[0.15129, 0.15129]
INFO:root:Epoch 929 [111.5s + 32.1s]: train==[605.39777=605.35944 + 0.03810], recall=[0.65265, 0.65265], precision=[0.06526, 0.06526], hit=[0.65265, 0.65265], ndcg=[0.37808, 0.37808]
INFO:root:Epoch 229 [110.8s + 33.6s]: train==[691.96893=691.95349 + 0.01568], recall=[0.29917, 0.29917], precision=[0.02992, 0.02992], hit=[0.29917, 0.29917], ndcg=[0.15549, 0.15549]
INFO:root:Epoch 939 [112.3s + 32.4s]: train==[603.75208=603.71423 + 0.03883], recall=[0.65811, 0.65811], precision=[0.06581, 0.06581], hit=[0.65811, 0.65811], ndcg=[0.37985, 0.37985]
INFO:root:Epoch 239 [110.4s + 33.5s]: train==[691.85419=691.83850 + 0.01569], recall=[0.30331, 0.30331], precision=[0.03033, 0.03033], hit=[0.30331, 0.30331], ndcg=[0.16090, 0.16090]
INFO:root:Epoch 949 [112.3s + 33.6s]: train==[600.64685=600.60638 + 0.03962], recall=[0.65861, 0.65861], precision=[0.06586, 0.06586], hit=[0.65861, 0.65861], ndcg=[0.38253, 0.38253]
INFO:root:Epoch 249 [113.0s + 33.9s]: train==[691.76886=691.75354 + 0.01570], recall=[0.31242, 0.31242], precision=[0.03124, 0.03124], hit=[0.31242, 0.31242], ndcg=[0.16807, 0.16807]
INFO:root:Epoch 959 [111.8s + 32.0s]: train==[598.76630=598.72559 + 0.04041], recall=[0.66060, 0.66060], precision=[0.06606, 0.06606], hit=[0.66060, 0.66060], ndcg=[0.38293, 0.38293]
INFO:root:Epoch 259 [112.4s + 33.1s]: train==[691.58582=691.57202 + 0.01572], recall=[0.32748, 0.32748], precision=[0.03275, 0.03275], hit=[0.32748, 0.32748], ndcg=[0.17855, 0.17855]
INFO:root:Epoch 969 [112.3s + 33.0s]: train==[596.08167=596.03961 + 0.04113], recall=[0.66010, 0.66010], precision=[0.06601, 0.06601], hit=[0.66010, 0.66010], ndcg=[0.38260, 0.38260]
INFO:root:Epoch 269 [110.8s + 33.6s]: train==[691.41254=691.39655 + 0.01574], recall=[0.34238, 0.34238], precision=[0.03424, 0.03424], hit=[0.34238, 0.34238], ndcg=[0.18706, 0.18706]
INFO:root:Epoch 279 [111.1s + 32.7s]: train==[691.22784=691.21106 + 0.01576], recall=[0.35795, 0.35795], precision=[0.03579, 0.03579], hit=[0.35795, 0.35795], ndcg=[0.19821, 0.19821]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 979 [112.9s + 34.1s]: train==[593.62952=593.58771 + 0.04199], recall=[0.65447, 0.65447], precision=[0.06545, 0.06545], hit=[0.65447, 0.65447], ndcg=[0.37855, 0.37855]
INFO:root:Epoch 289 [110.5s + 31.3s]: train==[690.96570=690.94965 + 0.01579], recall=[0.38096, 0.38096], precision=[0.03810, 0.03810], hit=[0.38096, 0.38096], ndcg=[0.21214, 0.21214]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 989 [114.6s + 33.9s]: train==[591.88483=591.84204 + 0.04277], recall=[0.65430, 0.65430], precision=[0.06543, 0.06543], hit=[0.65430, 0.65430], ndcg=[0.37850, 0.37850]
INFO:root:Epoch 299 [110.1s + 32.3s]: train==[690.65155=690.63568 + 0.01581], recall=[0.39785, 0.39785], precision=[0.03978, 0.03978], hit=[0.39785, 0.39785], ndcg=[0.22334, 0.22334]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 999 [112.0s + 32.2s]: train==[589.82953=589.78595 + 0.04362], recall=[0.65778, 0.65778], precision=[0.06578, 0.06578], hit=[0.65778, 0.65778], ndcg=[0.37779, 0.37779]
INFO:root:Epoch 309 [109.7s + 33.3s]: train==[690.38434=690.36914 + 0.01585], recall=[0.41904, 0.41904], precision=[0.04190, 0.04190], hit=[0.41904, 0.41904], ndcg=[0.23542, 0.23542]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1009 [112.6s + 31.5s]: train==[586.32294=586.27863 + 0.04442], recall=[0.65844, 0.65844], precision=[0.06584, 0.06584], hit=[0.65844, 0.65844], ndcg=[0.38036, 0.38036]
INFO:root:Epoch 319 [110.1s + 33.0s]: train==[690.13470=690.11902 + 0.01588], recall=[0.43974, 0.43974], precision=[0.04397, 0.04397], hit=[0.43974, 0.43974], ndcg=[0.24914, 0.24914]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1019 [111.7s + 32.2s]: train==[584.23700=584.19189 + 0.04524], recall=[0.65646, 0.65646], precision=[0.06565, 0.06565], hit=[0.65646, 0.65646], ndcg=[0.38250, 0.38250]
INFO:root:Epoch 329 [109.9s + 33.7s]: train==[689.78046=689.76416 + 0.01593], recall=[0.45977, 0.45977], precision=[0.04598, 0.04598], hit=[0.45977, 0.45977], ndcg=[0.26442, 0.26442]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1029 [112.8s + 32.5s]: train==[583.44897=583.40253 + 0.04614], recall=[0.65762, 0.65762], precision=[0.06576, 0.06576], hit=[0.65762, 0.65762], ndcg=[0.38085, 0.38085]
INFO:root:Epoch 339 [110.5s + 31.8s]: train==[689.30707=689.29120 + 0.01597], recall=[0.48013, 0.48013], precision=[0.04801, 0.04801], hit=[0.48013, 0.48013], ndcg=[0.27716, 0.27716]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1039 [111.9s + 32.8s]: train==[580.80096=580.75415 + 0.04704], recall=[0.65844, 0.65844], precision=[0.06584, 0.06584], hit=[0.65844, 0.65844], ndcg=[0.38198, 0.38198]
INFO:root:Epoch 349 [111.2s + 32.8s]: train==[688.93286=688.91638 + 0.01602], recall=[0.49636, 0.49636], precision=[0.04964, 0.04964], hit=[0.49636, 0.49636], ndcg=[0.28821, 0.28821]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1049 [111.3s + 33.0s]: train==[578.28766=578.24017 + 0.04785], recall=[0.66026, 0.66026], precision=[0.06603, 0.06603], hit=[0.66026, 0.66026], ndcg=[0.38168, 0.38168]
INFO:root:Epoch 359 [110.4s + 32.5s]: train==[688.39307=688.37677 + 0.01608], recall=[0.51325, 0.51325], precision=[0.05132, 0.05132], hit=[0.51325, 0.51325], ndcg=[0.29958, 0.29958]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1059 [111.7s + 31.9s]: train==[575.67096=575.62207 + 0.04881], recall=[0.66126, 0.66126], precision=[0.06613, 0.06613], hit=[0.66126, 0.66126], ndcg=[0.38143, 0.38143]
INFO:root:Epoch 369 [110.4s + 33.9s]: train==[687.83691=687.82129 + 0.01615], recall=[0.53079, 0.53079], precision=[0.05308, 0.05308], hit=[0.53079, 0.53079], ndcg=[0.31047, 0.31047]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1069 [111.8s + 32.6s]: train==[573.72253=573.67273 + 0.04965], recall=[0.65795, 0.65795], precision=[0.06579, 0.06579], hit=[0.65795, 0.65795], ndcg=[0.38164, 0.38164]
INFO:root:Epoch 379 [111.3s + 32.9s]: train==[687.20648=687.19000 + 0.01622], recall=[0.54272, 0.54272], precision=[0.05427, 0.05427], hit=[0.54272, 0.54272], ndcg=[0.32070, 0.32070]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1079 [112.3s + 32.0s]: train==[571.17999=571.12939 + 0.05055], recall=[0.65811, 0.65811], precision=[0.06581, 0.06581], hit=[0.65811, 0.65811], ndcg=[0.38090, 0.38090]
INFO:root:Epoch 389 [110.1s + 33.2s]: train==[686.39685=686.38000 + 0.01630], recall=[0.55712, 0.55712], precision=[0.05571, 0.05571], hit=[0.55712, 0.55712], ndcg=[0.32810, 0.32810]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1089 [111.9s + 32.4s]: train==[570.47119=570.42029 + 0.05153], recall=[0.66209, 0.66209], precision=[0.06621, 0.06621], hit=[0.66209, 0.66209], ndcg=[0.37709, 0.37709]
INFO:root:Epoch 399 [110.7s + 32.4s]: train==[685.58594=685.56891 + 0.01638], recall=[0.56391, 0.56391], precision=[0.05639, 0.05639], hit=[0.56391, 0.56391], ndcg=[0.32993, 0.32993]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1099 [111.5s + 32.4s]: train==[566.61090=566.55890 + 0.05244], recall=[0.65894, 0.65894], precision=[0.06589, 0.06589], hit=[0.65894, 0.65894], ndcg=[0.38051, 0.38051]
INFO:root:Epoch 409 [111.2s + 34.1s]: train==[684.80127=684.78552 + 0.01648], recall=[0.57467, 0.57467], precision=[0.05747, 0.05747], hit=[0.57467, 0.57467], ndcg=[0.33922, 0.33922]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1109 [111.5s + 32.0s]: train==[563.72083=563.66711 + 0.05343], recall=[0.65497, 0.65497], precision=[0.06550, 0.06550], hit=[0.65497, 0.65497], ndcg=[0.38186, 0.38186]
INFO:root:Epoch 419 [110.0s + 32.4s]: train==[684.20544=684.18817 + 0.01658], recall=[0.59106, 0.59106], precision=[0.05911, 0.05911], hit=[0.59106, 0.59106], ndcg=[0.34527, 0.34527]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1119 [112.3s + 31.9s]: train==[563.41138=563.35730 + 0.05439], recall=[0.65364, 0.65364], precision=[0.06536, 0.06536], hit=[0.65364, 0.65364], ndcg=[0.37885, 0.37885]
INFO:root:Epoch 429 [110.7s + 32.6s]: train==[683.49207=683.47528 + 0.01670], recall=[0.59553, 0.59553], precision=[0.05955, 0.05955], hit=[0.59553, 0.59553], ndcg=[0.35199, 0.35199]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1129 [112.2s + 33.1s]: train==[560.46564=560.41022 + 0.05536], recall=[0.65745, 0.65745], precision=[0.06575, 0.06575], hit=[0.65745, 0.65745], ndcg=[0.37857, 0.37857]
INFO:root:Epoch 439 [109.9s + 32.7s]: train==[682.98230=682.96588 + 0.01681], recall=[0.60430, 0.60430], precision=[0.06043, 0.06043], hit=[0.60430, 0.60430], ndcg=[0.35591, 0.35591]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1139 [111.4s + 33.3s]: train==[558.33307=558.27728 + 0.05635], recall=[0.65546, 0.65546], precision=[0.06555, 0.06555], hit=[0.65546, 0.65546], ndcg=[0.37817, 0.37817]
INFO:root:Epoch 449 [112.0s + 34.5s]: train==[681.81250=681.79529 + 0.01694], recall=[0.61126, 0.61126], precision=[0.06113, 0.06113], hit=[0.61126, 0.61126], ndcg=[0.35849, 0.35849]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1149 [111.6s + 32.1s]: train==[556.94958=556.89276 + 0.05743], recall=[0.65116, 0.65116], precision=[0.06512, 0.06512], hit=[0.65116, 0.65116], ndcg=[0.37798, 0.37798]
INFO:root:Epoch 459 [111.3s + 36.1s]: train==[681.01221=680.99475 + 0.01709], recall=[0.61606, 0.61606], precision=[0.06161, 0.06161], hit=[0.61606, 0.61606], ndcg=[0.35890, 0.35890]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1159 [111.8s + 31.4s]: train==[553.82715=553.76868 + 0.05839], recall=[0.65414, 0.65414], precision=[0.06541, 0.06541], hit=[0.65414, 0.65414], ndcg=[0.37783, 0.37783]
INFO:root:Epoch 469 [111.2s + 32.4s]: train==[680.49158=680.47388 + 0.01724], recall=[0.62169, 0.62169], precision=[0.06217, 0.06217], hit=[0.62169, 0.62169], ndcg=[0.35966, 0.35966]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1169 [112.0s + 32.8s]: train==[551.39270=551.33337 + 0.05929], recall=[0.65828, 0.65828], precision=[0.06583, 0.06583], hit=[0.65828, 0.65828], ndcg=[0.38194, 0.38194]
INFO:root:Epoch 479 [111.1s + 31.1s]: train==[679.16705=679.14941 + 0.01741], recall=[0.62533, 0.62533], precision=[0.06253, 0.06253], hit=[0.62533, 0.62533], ndcg=[0.36622, 0.36622]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1179 [111.8s + 32.6s]: train==[549.10400=549.04382 + 0.06034], recall=[0.66109, 0.66109], precision=[0.06611, 0.06611], hit=[0.66109, 0.66109], ndcg=[0.38384, 0.38384]
INFO:root:Epoch 489 [111.2s + 33.6s]: train==[678.18231=678.16437 + 0.01758], recall=[0.63030, 0.63030], precision=[0.06303, 0.06303], hit=[0.63030, 0.63030], ndcg=[0.36742, 0.36742]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1189 [111.8s + 31.5s]: train==[547.18158=547.12036 + 0.06142], recall=[0.65993, 0.65993], precision=[0.06599, 0.06599], hit=[0.65993, 0.65993], ndcg=[0.38173, 0.38173]
INFO:root:Epoch 499 [109.6s + 34.0s]: train==[677.26941=677.25140 + 0.01777], recall=[0.63129, 0.63129], precision=[0.06313, 0.06313], hit=[0.63129, 0.63129], ndcg=[0.36773, 0.36773]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1199 [111.9s + 32.9s]: train==[545.45111=545.38843 + 0.06249], recall=[0.66490, 0.66490], precision=[0.06649, 0.06649], hit=[0.66490, 0.66490], ndcg=[0.38245, 0.38245]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 509 [111.5s + 34.0s]: train==[676.57587=676.55756 + 0.01797], recall=[0.63212, 0.63212], precision=[0.06321, 0.06321], hit=[0.63212, 0.63212], ndcg=[0.36970, 0.36970]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1209 [112.5s + 32.4s]: train==[542.96545=542.90186 + 0.06354], recall=[0.65695, 0.65695], precision=[0.06570, 0.06570], hit=[0.65695, 0.65695], ndcg=[0.38190, 0.38190]
INFO:root:Epoch 519 [111.6s + 32.5s]: train==[675.40881=675.39062 + 0.01818], recall=[0.63791, 0.63791], precision=[0.06379, 0.06379], hit=[0.63791, 0.63791], ndcg=[0.37075, 0.37075]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1219 [112.0s + 32.1s]: train==[541.50507=541.44006 + 0.06473], recall=[0.66026, 0.66026], precision=[0.06603, 0.06603], hit=[0.66026, 0.66026], ndcg=[0.38505, 0.38505]
INFO:root:Epoch 529 [111.0s + 32.7s]: train==[674.24579=674.22656 + 0.01840], recall=[0.63758, 0.63758], precision=[0.06376, 0.06376], hit=[0.63758, 0.63758], ndcg=[0.37222, 0.37222]
INFO:root:Epoch 1229 [111.6s + 32.1s]: train==[539.54071=539.47540 + 0.06575], recall=[0.65861, 0.65861], precision=[0.06586, 0.06586], hit=[0.65861, 0.65861], ndcg=[0.37963, 0.37963]
INFO:root:Epoch 539 [111.6s + 33.3s]: train==[673.64526=673.62524 + 0.01864], recall=[0.64570, 0.64570], precision=[0.06457, 0.06457], hit=[0.64570, 0.64570], ndcg=[0.37650, 0.37650]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1239 [112.8s + 32.1s]: train==[538.01080=537.94373 + 0.06683], recall=[0.65795, 0.65795], precision=[0.06579, 0.06579], hit=[0.65795, 0.65795], ndcg=[0.38019, 0.38019]
INFO:root:Epoch 549 [110.9s + 32.5s]: train==[671.80768=671.78943 + 0.01888], recall=[0.64272, 0.64272], precision=[0.06427, 0.06427], hit=[0.64272, 0.64272], ndcg=[0.37160, 0.37160]
INFO:root:Epoch 1249 [112.3s + 33.5s]: train==[535.38959=535.32153 + 0.06791], recall=[0.66258, 0.66258], precision=[0.06626, 0.06626], hit=[0.66258, 0.66258], ndcg=[0.38372, 0.38372]
INFO:root:Epoch 559 [110.9s + 34.1s]: train==[671.11609=671.09637 + 0.01915], recall=[0.65116, 0.65116], precision=[0.06512, 0.06512], hit=[0.65116, 0.65116], ndcg=[0.38010, 0.38010]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1259 [112.2s + 32.5s]: train==[534.21173=534.14270 + 0.06904], recall=[0.65513, 0.65513], precision=[0.06551, 0.06551], hit=[0.65513, 0.65513], ndcg=[0.37987, 0.37987]
INFO:root:Epoch 569 [110.9s + 33.9s]: train==[669.56647=669.54749 + 0.01942], recall=[0.64669, 0.64669], precision=[0.06467, 0.06467], hit=[0.64669, 0.64669], ndcg=[0.37720, 0.37720]
INFO:root:Epoch 1269 [112.2s + 33.4s]: train==[529.56238=529.49176 + 0.07016], recall=[0.66341, 0.66341], precision=[0.06634, 0.06634], hit=[0.66341, 0.66341], ndcg=[0.38021, 0.38021]
INFO:root:Epoch 579 [111.9s + 34.1s]: train==[668.34137=668.32178 + 0.01971], recall=[0.65066, 0.65066], precision=[0.06507, 0.06507], hit=[0.65066, 0.65066], ndcg=[0.37413, 0.37413]
INFO:root:Epoch 1279 [112.1s + 33.7s]: train==[527.71716=527.64569 + 0.07134], recall=[0.66126, 0.66126], precision=[0.06613, 0.06613], hit=[0.66126, 0.66126], ndcg=[0.38194, 0.38194]
INFO:root:Epoch 589 [111.3s + 34.8s]: train==[667.36316=667.34265 + 0.02001], recall=[0.64305, 0.64305], precision=[0.06430, 0.06430], hit=[0.64305, 0.64305], ndcg=[0.37523, 0.37523]
INFO:root:Epoch 1289 [112.4s + 33.6s]: train==[527.84247=527.76978 + 0.07260], recall=[0.65944, 0.65944], precision=[0.06594, 0.06594], hit=[0.65944, 0.65944], ndcg=[0.37988, 0.37988]
INFO:root:Epoch 599 [111.1s + 35.4s]: train==[665.58508=665.56531 + 0.02032], recall=[0.64636, 0.64636], precision=[0.06464, 0.06464], hit=[0.64636, 0.64636], ndcg=[0.37463, 0.37463]
INFO:root:Epoch 1299 [112.9s + 33.6s]: train==[524.75867=524.68512 + 0.07371], recall=[0.66026, 0.66026], precision=[0.06603, 0.06603], hit=[0.66026, 0.66026], ndcg=[0.38294, 0.38294]
INFO:root:Epoch 609 [111.5s + 33.4s]: train==[664.09888=664.07819 + 0.02064], recall=[0.65265, 0.65265], precision=[0.06526, 0.06526], hit=[0.65265, 0.65265], ndcg=[0.37620, 0.37620]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1309 [112.1s + 33.6s]: train==[523.90253=523.82715 + 0.07488], recall=[0.66142, 0.66142], precision=[0.06614, 0.06614], hit=[0.66142, 0.66142], ndcg=[0.38284, 0.38284]
INFO:root:Epoch 619 [111.7s + 33.8s]: train==[663.13635=663.11578 + 0.02099], recall=[0.65149, 0.65149], precision=[0.06515, 0.06515], hit=[0.65149, 0.65149], ndcg=[0.37795, 0.37795]
INFO:root:Epoch 1319 [111.9s + 33.0s]: train==[522.15350=522.07721 + 0.07609], recall=[0.65728, 0.65728], precision=[0.06573, 0.06573], hit=[0.65728, 0.65728], ndcg=[0.38202, 0.38202]
INFO:root:Epoch 629 [111.0s + 34.2s]: train==[661.36615=661.34473 + 0.02134], recall=[0.65149, 0.65149], precision=[0.06515, 0.06515], hit=[0.65149, 0.65149], ndcg=[0.37868, 0.37868]
INFO:root:Epoch 1329 [113.0s + 33.3s]: train==[519.56781=519.49005 + 0.07733], recall=[0.65944, 0.65944], precision=[0.06594, 0.06594], hit=[0.65944, 0.65944], ndcg=[0.38342, 0.38342]
INFO:root:Epoch 639 [110.6s + 32.5s]: train==[659.77875=659.75763 + 0.02170], recall=[0.65166, 0.65166], precision=[0.06517, 0.06517], hit=[0.65166, 0.65166], ndcg=[0.37785, 0.37785]
INFO:root:Epoch 1339 [113.1s + 33.6s]: train==[516.89020=516.81207 + 0.07848], recall=[0.65861, 0.65861], precision=[0.06586, 0.06586], hit=[0.65861, 0.65861], ndcg=[0.37947, 0.37947]
INFO:root:Epoch 649 [111.1s + 34.2s]: train==[658.64972=658.62750 + 0.02209], recall=[0.65215, 0.65215], precision=[0.06522, 0.06522], hit=[0.65215, 0.65215], ndcg=[0.37829, 0.37829]
INFO:root:Epoch 1349 [113.0s + 32.8s]: train==[514.28125=514.20160 + 0.07972], recall=[0.66093, 0.66093], precision=[0.06609, 0.06609], hit=[0.66093, 0.66093], ndcg=[0.38386, 0.38386]
INFO:root:Epoch 659 [110.6s + 32.5s]: train==[656.54688=656.52411 + 0.02247], recall=[0.65066, 0.65066], precision=[0.06507, 0.06507], hit=[0.65066, 0.65066], ndcg=[0.37746, 0.37746]
INFO:root:Epoch 1359 [112.6s + 33.3s]: train==[513.58801=513.50690 + 0.08110], recall=[0.66490, 0.66490], precision=[0.06649, 0.06649], hit=[0.66490, 0.66490], ndcg=[0.38226, 0.38226]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 669 [110.4s + 33.9s]: train==[655.10461=655.08124 + 0.02289], recall=[0.65364, 0.65364], precision=[0.06536, 0.06536], hit=[0.65364, 0.65364], ndcg=[0.37932, 0.37932]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1369 [113.0s + 32.4s]: train==[510.03311=509.95010 + 0.08235], recall=[0.66126, 0.66126], precision=[0.06613, 0.06613], hit=[0.66126, 0.66126], ndcg=[0.38479, 0.38479]
INFO:root:Epoch 679 [110.3s + 33.3s]: train==[653.64166=653.61884 + 0.02329], recall=[0.65579, 0.65579], precision=[0.06558, 0.06558], hit=[0.65579, 0.65579], ndcg=[0.37640, 0.37640]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1379 [112.4s + 33.9s]: train==[509.94269=509.85828 + 0.08368], recall=[0.65530, 0.65530], precision=[0.06553, 0.06553], hit=[0.65530, 0.65530], ndcg=[0.37975, 0.37975]
INFO:root:Epoch 689 [110.9s + 32.9s]: train==[651.37982=651.35645 + 0.02371], recall=[0.65695, 0.65695], precision=[0.06570, 0.06570], hit=[0.65695, 0.65695], ndcg=[0.38114, 0.38114]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1389 [112.4s + 32.9s]: train==[507.51770=507.43240 + 0.08486], recall=[0.66076, 0.66076], precision=[0.06608, 0.06608], hit=[0.66076, 0.66076], ndcg=[0.37995, 0.37995]
INFO:root:Epoch 699 [111.4s + 33.1s]: train==[650.10376=650.07886 + 0.02415], recall=[0.65414, 0.65414], precision=[0.06541, 0.06541], hit=[0.65414, 0.65414], ndcg=[0.37941, 0.37941]
INFO:root:Epoch 1399 [113.5s + 34.1s]: train==[504.44028=504.35461 + 0.08618], recall=[0.65199, 0.65199], precision=[0.06520, 0.06520], hit=[0.65199, 0.65199], ndcg=[0.37947, 0.37947]
INFO:root:Epoch 709 [111.5s + 33.5s]: train==[648.29669=648.27258 + 0.02462], recall=[0.65397, 0.65397], precision=[0.06540, 0.06540], hit=[0.65397, 0.65397], ndcg=[0.38060, 0.38060]
INFO:root:Epoch 1409 [112.8s + 35.9s]: train==[502.92108=502.83350 + 0.08746], recall=[0.65613, 0.65613], precision=[0.06561, 0.06561], hit=[0.65613, 0.65613], ndcg=[0.37770, 0.37770]
INFO:root:Epoch 719 [110.7s + 33.0s]: train==[646.20892=646.18439 + 0.02509], recall=[0.65662, 0.65662], precision=[0.06566, 0.06566], hit=[0.65662, 0.65662], ndcg=[0.37982, 0.37982]
INFO:root:Epoch 1419 [113.7s + 33.0s]: train==[499.69153=499.60248 + 0.08876], recall=[0.66440, 0.66440], precision=[0.06644, 0.06644], hit=[0.66440, 0.66440], ndcg=[0.38066, 0.38066]
INFO:root:Epoch 729 [110.5s + 33.0s]: train==[644.85168=644.82721 + 0.02556], recall=[0.65066, 0.65066], precision=[0.06507, 0.06507], hit=[0.65066, 0.65066], ndcg=[0.37700, 0.37700]
INFO:root:Epoch 1429 [112.6s + 32.9s]: train==[500.15054=500.06030 + 0.09020], recall=[0.65613, 0.65613], precision=[0.06561, 0.06561], hit=[0.65613, 0.65613], ndcg=[0.37996, 0.37996]
INFO:root:Epoch 739 [110.3s + 33.9s]: train==[643.56757=643.54095 + 0.02607], recall=[0.65099, 0.65099], precision=[0.06510, 0.06510], hit=[0.65099, 0.65099], ndcg=[0.37697, 0.37697]
INFO:root:Epoch 1439 [112.8s + 33.1s]: train==[497.55832=497.46674 + 0.09147], recall=[0.66159, 0.66159], precision=[0.06616, 0.06616], hit=[0.66159, 0.66159], ndcg=[0.38007, 0.38007]
INFO:root:Epoch 749 [110.1s + 33.7s]: train==[640.95251=640.92633 + 0.02656], recall=[0.65265, 0.65265], precision=[0.06526, 0.06526], hit=[0.65265, 0.65265], ndcg=[0.37978, 0.37978]
INFO:root:Epoch 1449 [112.6s + 32.9s]: train==[496.59485=496.50217 + 0.09290], recall=[0.65927, 0.65927], precision=[0.06593, 0.06593], hit=[0.65927, 0.65927], ndcg=[0.38404, 0.38404]
INFO:root:Epoch 759 [111.1s + 33.9s]: train==[639.28625=639.25903 + 0.02709], recall=[0.65132, 0.65132], precision=[0.06513, 0.06513], hit=[0.65132, 0.65132], ndcg=[0.37872, 0.37872]
INFO:root:Epoch 1459 [112.1s + 33.4s]: train==[496.03870=495.94455 + 0.09429], recall=[0.66325, 0.66325], precision=[0.06632, 0.06632], hit=[0.66325, 0.66325], ndcg=[0.38391, 0.38391]
INFO:root:Epoch 769 [111.0s + 33.2s]: train==[637.60315=637.57568 + 0.02761], recall=[0.65728, 0.65728], precision=[0.06573, 0.06573], hit=[0.65728, 0.65728], ndcg=[0.38191, 0.38191]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1469 [112.9s + 33.4s]: train==[492.42868=492.33289 + 0.09568], recall=[0.65579, 0.65579], precision=[0.06558, 0.06558], hit=[0.65579, 0.65579], ndcg=[0.38112, 0.38112]
INFO:root:Epoch 779 [111.2s + 33.3s]: train==[635.09637=635.06781 + 0.02816], recall=[0.65778, 0.65778], precision=[0.06578, 0.06578], hit=[0.65778, 0.65778], ndcg=[0.38242, 0.38242]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1479 [113.0s + 33.2s]: train==[490.08237=489.98544 + 0.09701], recall=[0.65629, 0.65629], precision=[0.06563, 0.06563], hit=[0.65629, 0.65629], ndcg=[0.37978, 0.37978]
INFO:root:Epoch 789 [111.3s + 32.8s]: train==[633.07733=633.04919 + 0.02872], recall=[0.65116, 0.65116], precision=[0.06512, 0.06512], hit=[0.65116, 0.65116], ndcg=[0.37953, 0.37953]
INFO:root:Epoch 1489 [112.8s + 33.6s]: train==[489.66141=489.56253 + 0.09846], recall=[0.65911, 0.65911], precision=[0.06591, 0.06591], hit=[0.65911, 0.65911], ndcg=[0.38116, 0.38116]
INFO:root:Epoch 799 [110.7s + 34.9s]: train==[631.77704=631.74768 + 0.02930], recall=[0.65679, 0.65679], precision=[0.06568, 0.06568], hit=[0.65679, 0.65679], ndcg=[0.37939, 0.37939]
INFO:root:Epoch 1499 [112.8s + 35.1s]: train==[487.58075=487.48129 + 0.09991], recall=[0.66126, 0.66126], precision=[0.06613, 0.06613], hit=[0.66126, 0.66126], ndcg=[0.38204, 0.38204]
INFO:root:Epoch 809 [111.6s + 32.8s]: train==[629.67969=629.64941 + 0.02988], recall=[0.65480, 0.65480], precision=[0.06548, 0.06548], hit=[0.65480, 0.65480], ndcg=[0.38073, 0.38073]
INFO:root:Epoch 1509 [113.5s + 33.3s]: train==[485.93225=485.83096 + 0.10122], recall=[0.65894, 0.65894], precision=[0.06589, 0.06589], hit=[0.65894, 0.65894], ndcg=[0.38032, 0.38032]
INFO:root:Epoch 819 [111.1s + 33.4s]: train==[627.42712=627.39606 + 0.03047], recall=[0.65646, 0.65646], precision=[0.06565, 0.06565], hit=[0.65646, 0.65646], ndcg=[0.38096, 0.38096]
INFO:root:Epoch 1519 [112.4s + 31.8s]: train==[487.07065=486.96774 + 0.10279], recall=[0.65662, 0.65662], precision=[0.06566, 0.06566], hit=[0.65662, 0.65662], ndcg=[0.37961, 0.37961]
INFO:root:Epoch 829 [112.8s + 33.3s]: train==[625.42157=625.39038 + 0.03107], recall=[0.65927, 0.65927], precision=[0.06593, 0.06593], hit=[0.65927, 0.65927], ndcg=[0.38417, 0.38417]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1529 [113.4s + 35.6s]: train==[479.42859=479.32510 + 0.10402], recall=[0.66093, 0.66093], precision=[0.06609, 0.06609], hit=[0.66093, 0.66093], ndcg=[0.38094, 0.38094]
INFO:root:Epoch 839 [112.0s + 38.3s]: train==[623.29510=623.26379 + 0.03168], recall=[0.65877, 0.65877], precision=[0.06588, 0.06588], hit=[0.65877, 0.65877], ndcg=[0.38130, 0.38130]
INFO:root:Epoch 849 [109.2s + 34.5s]: train==[620.81689=620.78400 + 0.03231], recall=[0.65430, 0.65430], precision=[0.06543, 0.06543], hit=[0.65430, 0.65430], ndcg=[0.37996, 0.37996]
INFO:root:Epoch 1539 [113.4s + 35.1s]: train==[482.98376=482.87778 + 0.10584], recall=[0.65745, 0.65745], precision=[0.06575, 0.06575], hit=[0.65745, 0.65745], ndcg=[0.38341, 0.38341]
INFO:root:Epoch 859 [110.0s + 31.7s]: train==[618.38910=618.35565 + 0.03295], recall=[0.65695, 0.65695], precision=[0.06570, 0.06570], hit=[0.65695, 0.65695], ndcg=[0.38013, 0.38013]
INFO:root:Epoch 1549 [114.5s + 33.6s]: train==[479.41635=479.30920 + 0.10715], recall=[0.65414, 0.65414], precision=[0.06541, 0.06541], hit=[0.65414, 0.65414], ndcg=[0.38021, 0.38021]
INFO:root:Epoch 869 [111.1s + 33.9s]: train==[616.86401=616.83057 + 0.03364], recall=[0.66043, 0.66043], precision=[0.06604, 0.06604], hit=[0.66043, 0.66043], ndcg=[0.38136, 0.38136]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1559 [112.5s + 32.3s]: train==[477.13721=477.02844 + 0.10855], recall=[0.65132, 0.65132], precision=[0.06513, 0.06513], hit=[0.65132, 0.65132], ndcg=[0.37962, 0.37962]
INFO:root:Epoch 879 [109.1s + 31.6s]: train==[614.43024=614.39636 + 0.03429], recall=[0.65712, 0.65712], precision=[0.06571, 0.06571], hit=[0.65712, 0.65712], ndcg=[0.37909, 0.37909]
INFO:root:Epoch 1569 [113.8s + 34.2s]: train==[479.01004=478.89929 + 0.11016], recall=[0.65364, 0.65364], precision=[0.06536, 0.06536], hit=[0.65364, 0.65364], ndcg=[0.38014, 0.38014]
INFO:root:Epoch 889 [110.0s + 31.9s]: train==[611.30847=611.27313 + 0.03494], recall=[0.65530, 0.65530], precision=[0.06553, 0.06553], hit=[0.65530, 0.65530], ndcg=[0.38160, 0.38160]
INFO:root:Epoch 1579 [113.3s + 34.0s]: train==[474.82608=474.71439 + 0.11171], recall=[0.66076, 0.66076], precision=[0.06608, 0.06608], hit=[0.66076, 0.66076], ndcg=[0.38391, 0.38391]
INFO:root:Epoch 899 [110.0s + 33.3s]: train==[610.34375=610.30695 + 0.03569], recall=[0.65927, 0.65927], precision=[0.06593, 0.06593], hit=[0.65927, 0.65927], ndcg=[0.37962, 0.37962]
INFO:root:Epoch 1589 [114.0s + 34.4s]: train==[473.61084=473.49765 + 0.11333], recall=[0.66225, 0.66225], precision=[0.06623, 0.06623], hit=[0.66225, 0.66225], ndcg=[0.38637, 0.38637]
INFO:root:Epoch 909 [110.8s + 32.1s]: train==[607.53174=607.49524 + 0.03638], recall=[0.65911, 0.65911], precision=[0.06591, 0.06591], hit=[0.65911, 0.65911], ndcg=[0.38071, 0.38071]
INFO:root:Epoch 1599 [113.9s + 34.1s]: train==[472.14584=472.03098 + 0.11473], recall=[0.66440, 0.66440], precision=[0.06644, 0.06644], hit=[0.66440, 0.66440], ndcg=[0.38023, 0.38023]
INFO:root:Epoch 919 [110.4s + 33.0s]: train==[605.92145=605.88489 + 0.03711], recall=[0.66175, 0.66175], precision=[0.06618, 0.06618], hit=[0.66175, 0.66175], ndcg=[0.38190, 0.38190]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1609 [113.7s + 32.8s]: train==[470.11316=469.99652 + 0.11633], recall=[0.66374, 0.66374], precision=[0.06637, 0.06637], hit=[0.66374, 0.66374], ndcg=[0.38448, 0.38448]
INFO:root:Epoch 929 [110.0s + 33.3s]: train==[602.91113=602.87372 + 0.03785], recall=[0.65215, 0.65215], precision=[0.06522, 0.06522], hit=[0.65215, 0.65215], ndcg=[0.37556, 0.37556]
INFO:root:Epoch 1619 [113.4s + 34.2s]: train==[468.74109=468.62302 + 0.11784], recall=[0.66341, 0.66341], precision=[0.06634, 0.06634], hit=[0.66341, 0.66341], ndcg=[0.38474, 0.38474]
INFO:root:Epoch 939 [109.7s + 32.0s]: train==[600.88599=600.84729 + 0.03857], recall=[0.65629, 0.65629], precision=[0.06563, 0.06563], hit=[0.65629, 0.65629], ndcg=[0.38332, 0.38332]
INFO:root:Epoch 1629 [113.3s + 34.0s]: train==[467.42542=467.30600 + 0.11943], recall=[0.65811, 0.65811], precision=[0.06581, 0.06581], hit=[0.65811, 0.65811], ndcg=[0.38116, 0.38116]
INFO:root:Epoch 949 [111.5s + 32.7s]: train==[599.66589=599.62640 + 0.03936], recall=[0.65662, 0.65662], precision=[0.06566, 0.06566], hit=[0.65662, 0.65662], ndcg=[0.37819, 0.37819]
INFO:root:Epoch 1639 [113.7s + 36.0s]: train==[464.54095=464.42029 + 0.12083], recall=[0.65993, 0.65993], precision=[0.06599, 0.06599], hit=[0.65993, 0.65993], ndcg=[0.38024, 0.38024]
INFO:root:Epoch 959 [110.1s + 35.6s]: train==[595.82672=595.78680 + 0.04012], recall=[0.65662, 0.65662], precision=[0.06566, 0.06566], hit=[0.65662, 0.65662], ndcg=[0.37947, 0.37947]
INFO:root:Epoch 1649 [113.7s + 32.8s]: train==[465.07794=464.95563 + 0.12250], recall=[0.65712, 0.65712], precision=[0.06571, 0.06571], hit=[0.65712, 0.65712], ndcg=[0.38114, 0.38114]
INFO:root:Epoch 969 [110.5s + 31.8s]: train==[594.53558=594.49524 + 0.04091], recall=[0.66175, 0.66175], precision=[0.06618, 0.06618], hit=[0.66175, 0.66175], ndcg=[0.37800, 0.37800]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1659 [113.0s + 33.2s]: train==[464.30325=464.17886 + 0.12411], recall=[0.66308, 0.66308], precision=[0.06631, 0.06631], hit=[0.66308, 0.66308], ndcg=[0.38097, 0.38097]
INFO:root:Best Iter=[119]@[180979.9]	recall=[0.66490], precision=[0.06649], hit=[0.66490], ndcg=[0.38245]
INFO:root:Epoch 979 [108.9s + 31.5s]: train==[592.40521=592.36304 + 0.04169], recall=[0.65646, 0.65646], precision=[0.06565, 0.06565], hit=[0.65646, 0.65646], ndcg=[0.38111, 0.38111]
INFO:root:Epoch 989 [108.2s + 31.1s]: train==[589.97595=589.93365 + 0.04249], recall=[0.65430, 0.65430], precision=[0.06543, 0.06543], hit=[0.65430, 0.65430], ndcg=[0.37951, 0.37951]
INFO:root:Epoch 999 [109.1s + 31.3s]: train==[588.57471=588.53198 + 0.04334], recall=[0.65745, 0.65745], precision=[0.06575, 0.06575], hit=[0.65745, 0.65745], ndcg=[0.38296, 0.38296]
INFO:root:Epoch 1009 [108.4s + 34.3s]: train==[584.86304=584.81879 + 0.04414], recall=[0.65728, 0.65728], precision=[0.06573, 0.06573], hit=[0.65728, 0.65728], ndcg=[0.37926, 0.37926]
INFO:root:Epoch 1019 [109.0s + 31.2s]: train==[582.53400=582.48956 + 0.04495], recall=[0.65927, 0.65927], precision=[0.06593, 0.06593], hit=[0.65927, 0.65927], ndcg=[0.38016, 0.38016]
INFO:root:Epoch 1029 [110.0s + 31.9s]: train==[581.40283=581.35693 + 0.04584], recall=[0.65348, 0.65348], precision=[0.06535, 0.06535], hit=[0.65348, 0.65348], ndcg=[0.37876, 0.37876]
INFO:root:Epoch 1039 [108.4s + 32.8s]: train==[578.47296=578.42676 + 0.04667], recall=[0.65579, 0.65579], precision=[0.06558, 0.06558], hit=[0.65579, 0.65579], ndcg=[0.37958, 0.37958]
INFO:root:Epoch 1049 [108.8s + 32.6s]: train==[576.18073=576.13287 + 0.04756], recall=[0.65579, 0.65579], precision=[0.06558, 0.06558], hit=[0.65579, 0.65579], ndcg=[0.37814, 0.37814]
INFO:root:Epoch 1059 [112.2s + 33.7s]: train==[573.20715=573.15881 + 0.04843], recall=[0.65877, 0.65877], precision=[0.06588, 0.06588], hit=[0.65877, 0.65877], ndcg=[0.37943, 0.37943]
INFO:root:Epoch 1069 [109.8s + 30.8s]: train==[571.56610=571.51685 + 0.04931], recall=[0.65877, 0.65877], precision=[0.06588, 0.06588], hit=[0.65877, 0.65877], ndcg=[0.38217, 0.38217]
INFO:root:Epoch 1079 [109.0s + 32.5s]: train==[570.58478=570.53424 + 0.05026], recall=[0.65877, 0.65877], precision=[0.06588, 0.06588], hit=[0.65877, 0.65877], ndcg=[0.38358, 0.38358]
INFO:root:Epoch 1089 [108.9s + 31.7s]: train==[567.81537=567.76422 + 0.05121], recall=[0.66142, 0.66142], precision=[0.06614, 0.06614], hit=[0.66142, 0.66142], ndcg=[0.38228, 0.38228]
INFO:root:Epoch 1099 [108.7s + 31.9s]: train==[563.89471=563.84265 + 0.05217], recall=[0.66010, 0.66010], precision=[0.06601, 0.06601], hit=[0.66010, 0.66010], ndcg=[0.38043, 0.38043]
INFO:root:Epoch 1109 [108.9s + 32.0s]: train==[561.88708=561.83429 + 0.05305], recall=[0.66060, 0.66060], precision=[0.06606, 0.06606], hit=[0.66060, 0.66060], ndcg=[0.38103, 0.38103]
INFO:root:Epoch 1119 [109.4s + 32.2s]: train==[560.41583=560.36194 + 0.05403], recall=[0.65546, 0.65546], precision=[0.06555, 0.06555], hit=[0.65546, 0.65546], ndcg=[0.38049, 0.38049]
INFO:root:Epoch 1129 [109.1s + 32.0s]: train==[558.42291=558.36780 + 0.05505], recall=[0.66093, 0.66093], precision=[0.06609, 0.06609], hit=[0.66093, 0.66093], ndcg=[0.38209, 0.38209]
INFO:root:Epoch 1139 [108.9s + 31.6s]: train==[556.01483=555.95856 + 0.05599], recall=[0.66109, 0.66109], precision=[0.06611, 0.06611], hit=[0.66109, 0.66109], ndcg=[0.38390, 0.38390]
INFO:root:Epoch 1149 [108.9s + 33.1s]: train==[554.37164=554.31458 + 0.05705], recall=[0.66242, 0.66242], precision=[0.06624, 0.06624], hit=[0.66242, 0.66242], ndcg=[0.38332, 0.38332]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1159 [108.4s + 31.6s]: train==[552.17303=552.11536 + 0.05801], recall=[0.65960, 0.65960], precision=[0.06596, 0.06596], hit=[0.65960, 0.65960], ndcg=[0.38266, 0.38266]
INFO:root:Epoch 1169 [109.3s + 32.1s]: train==[550.85425=550.79517 + 0.05907], recall=[0.65778, 0.65778], precision=[0.06578, 0.06578], hit=[0.65778, 0.65778], ndcg=[0.38313, 0.38313]
INFO:root:Epoch 1179 [109.2s + 31.8s]: train==[547.30383=547.24353 + 0.06008], recall=[0.66010, 0.66010], precision=[0.06601, 0.06601], hit=[0.66010, 0.66010], ndcg=[0.38298, 0.38298]
INFO:root:Epoch 1189 [109.4s + 31.3s]: train==[546.65985=546.59869 + 0.06113], recall=[0.66076, 0.66076], precision=[0.06608, 0.06608], hit=[0.66076, 0.66076], ndcg=[0.38392, 0.38392]
INFO:root:Epoch 1199 [109.3s + 31.2s]: train==[543.39398=543.33154 + 0.06218], recall=[0.65430, 0.65430], precision=[0.06543, 0.06543], hit=[0.65430, 0.65430], ndcg=[0.38146, 0.38146]
INFO:root:Epoch 1209 [109.4s + 31.5s]: train==[542.49860=542.43512 + 0.06334], recall=[0.65629, 0.65629], precision=[0.06563, 0.06563], hit=[0.65629, 0.65629], ndcg=[0.38013, 0.38013]
INFO:root:Epoch 1219 [108.4s + 32.2s]: train==[538.91626=538.85187 + 0.06429], recall=[0.65811, 0.65811], precision=[0.06581, 0.06581], hit=[0.65811, 0.65811], ndcg=[0.37782, 0.37782]
INFO:root:Epoch 1229 [109.2s + 32.0s]: train==[537.10596=537.04028 + 0.06540], recall=[0.65861, 0.65861], precision=[0.06586, 0.06586], hit=[0.65861, 0.65861], ndcg=[0.37997, 0.37997]
INFO:root:Epoch 1239 [108.8s + 32.4s]: train==[535.08496=535.01837 + 0.06647], recall=[0.65762, 0.65762], precision=[0.06576, 0.06576], hit=[0.65762, 0.65762], ndcg=[0.38006, 0.38006]
INFO:root:Epoch 1249 [108.8s + 31.4s]: train==[531.86871=531.80078 + 0.06769], recall=[0.65662, 0.65662], precision=[0.06566, 0.06566], hit=[0.65662, 0.65662], ndcg=[0.38146, 0.38146]
INFO:root:Epoch 1259 [109.5s + 31.3s]: train==[530.31042=530.24249 + 0.06878], recall=[0.66424, 0.66424], precision=[0.06642, 0.06642], hit=[0.66424, 0.66424], ndcg=[0.38113, 0.38113]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1269 [109.3s + 30.7s]: train==[525.51868=525.44873 + 0.06981], recall=[0.66159, 0.66159], precision=[0.06616, 0.06616], hit=[0.66159, 0.66159], ndcg=[0.38495, 0.38495]
INFO:root:Epoch 1279 [109.0s + 31.6s]: train==[526.08258=526.01172 + 0.07111], recall=[0.66175, 0.66175], precision=[0.06618, 0.06618], hit=[0.66175, 0.66175], ndcg=[0.38286, 0.38286]
INFO:root:Epoch 1289 [108.6s + 31.7s]: train==[524.75250=524.68066 + 0.07222], recall=[0.65778, 0.65778], precision=[0.06578, 0.06578], hit=[0.65778, 0.65778], ndcg=[0.38161, 0.38161]
INFO:root:Epoch 1299 [108.8s + 32.3s]: train==[521.73865=521.66498 + 0.07341], recall=[0.65430, 0.65430], precision=[0.06543, 0.06543], hit=[0.65430, 0.65430], ndcg=[0.38208, 0.38208]
INFO:root:Epoch 1309 [108.8s + 31.1s]: train==[519.36987=519.29523 + 0.07457], recall=[0.65960, 0.65960], precision=[0.06596, 0.06596], hit=[0.65960, 0.65960], ndcg=[0.38100, 0.38100]
INFO:root:Epoch 1319 [109.3s + 32.4s]: train==[517.77533=517.69965 + 0.07578], recall=[0.65728, 0.65728], precision=[0.06573, 0.06573], hit=[0.65728, 0.65728], ndcg=[0.38438, 0.38438]
INFO:root:Epoch 1329 [109.2s + 32.5s]: train==[515.63477=515.55859 + 0.07699], recall=[0.66209, 0.66209], precision=[0.06621, 0.06621], hit=[0.66209, 0.66209], ndcg=[0.38317, 0.38317]
INFO:root:Epoch 1339 [109.5s + 31.7s]: train==[513.80774=513.72925 + 0.07824], recall=[0.66093, 0.66093], precision=[0.06609, 0.06609], hit=[0.66093, 0.66093], ndcg=[0.38407, 0.38407]
INFO:root:Epoch 1349 [108.9s + 32.7s]: train==[512.02124=511.94186 + 0.07952], recall=[0.65828, 0.65828], precision=[0.06583, 0.06583], hit=[0.65828, 0.65828], ndcg=[0.38044, 0.38044]
INFO:root:Epoch 1359 [108.7s + 30.6s]: train==[511.68234=511.60187 + 0.08075], recall=[0.65546, 0.65546], precision=[0.06555, 0.06555], hit=[0.65546, 0.65546], ndcg=[0.38022, 0.38022]
INFO:root:Epoch 1369 [109.0s + 32.5s]: train==[507.02148=506.93912 + 0.08193], recall=[0.65927, 0.65927], precision=[0.06593, 0.06593], hit=[0.65927, 0.65927], ndcg=[0.37909, 0.37909]
INFO:root:Epoch 1379 [109.3s + 31.3s]: train==[504.61890=504.53534 + 0.08325], recall=[0.65778, 0.65778], precision=[0.06578, 0.06578], hit=[0.65778, 0.65778], ndcg=[0.38300, 0.38300]
INFO:root:Epoch 1389 [110.0s + 30.8s]: train==[505.38376=505.29913 + 0.08463], recall=[0.65613, 0.65613], precision=[0.06561, 0.06561], hit=[0.65613, 0.65613], ndcg=[0.37914, 0.37914]
INFO:root:Epoch 1399 [109.2s + 31.9s]: train==[502.10464=502.01837 + 0.08593], recall=[0.65993, 0.65993], precision=[0.06599, 0.06599], hit=[0.65993, 0.65993], ndcg=[0.38227, 0.38227]
INFO:root:Epoch 1409 [111.1s + 33.1s]: train==[499.53345=499.44632 + 0.08713], recall=[0.65795, 0.65795], precision=[0.06579, 0.06579], hit=[0.65795, 0.65795], ndcg=[0.37979, 0.37979]
INFO:root:Epoch 1419 [108.7s + 30.7s]: train==[497.83084=497.74213 + 0.08850], recall=[0.65861, 0.65861], precision=[0.06586, 0.06586], hit=[0.65861, 0.65861], ndcg=[0.38063, 0.38063]
INFO:root:Epoch 1429 [108.6s + 32.0s]: train==[497.13086=497.04120 + 0.08982], recall=[0.65530, 0.65530], precision=[0.06553, 0.06553], hit=[0.65530, 0.65530], ndcg=[0.38262, 0.38262]
INFO:root:Epoch 1439 [109.8s + 31.7s]: train==[496.17480=496.08350 + 0.09119], recall=[0.66209, 0.66209], precision=[0.06621, 0.06621], hit=[0.66209, 0.66209], ndcg=[0.38394, 0.38394]
INFO:root:Epoch 1449 [108.7s + 31.4s]: train==[492.52109=492.42847 + 0.09252], recall=[0.65911, 0.65911], precision=[0.06591, 0.06591], hit=[0.65911, 0.65911], ndcg=[0.38212, 0.38212]
INFO:root:Epoch 1459 [110.0s + 32.0s]: train==[489.48999=489.39621 + 0.09386], recall=[0.66126, 0.66126], precision=[0.06613, 0.06613], hit=[0.66126, 0.66126], ndcg=[0.38196, 0.38196]
INFO:root:Epoch 1469 [110.5s + 34.6s]: train==[488.25342=488.15833 + 0.09537], recall=[0.66026, 0.66026], precision=[0.06603, 0.06603], hit=[0.66026, 0.66026], ndcg=[0.38272, 0.38272]
INFO:root:Epoch 1479 [110.6s + 34.9s]: train==[487.56506=487.46820 + 0.09668], recall=[0.65811, 0.65811], precision=[0.06581, 0.06581], hit=[0.65811, 0.65811], ndcg=[0.38203, 0.38203]
INFO:root:Epoch 1489 [111.3s + 33.3s]: train==[484.87238=484.77463 + 0.09805], recall=[0.65646, 0.65646], precision=[0.06565, 0.06565], hit=[0.65646, 0.65646], ndcg=[0.37888, 0.37888]
INFO:root:Epoch 1499 [111.0s + 34.1s]: train==[483.47623=483.37698 + 0.09949], recall=[0.66060, 0.66060], precision=[0.06606, 0.06606], hit=[0.66060, 0.66060], ndcg=[0.38237, 0.38237]
INFO:root:Epoch 1509 [110.7s + 33.4s]: train==[482.41391=482.31299 + 0.10098], recall=[0.66010, 0.66010], precision=[0.06601, 0.06601], hit=[0.66010, 0.66010], ndcg=[0.38189, 0.38189]
INFO:root:Epoch 1519 [111.2s + 33.0s]: train==[480.51205=480.40961 + 0.10227], recall=[0.65894, 0.65894], precision=[0.06589, 0.06589], hit=[0.65894, 0.65894], ndcg=[0.38082, 0.38082]
INFO:root:Epoch 1529 [112.0s + 35.7s]: train==[479.18369=479.08002 + 0.10383], recall=[0.66242, 0.66242], precision=[0.06624, 0.06624], hit=[0.66242, 0.66242], ndcg=[0.38074, 0.38074]
INFO:root:Epoch 1539 [112.5s + 33.4s]: train==[477.23709=477.13245 + 0.10529], recall=[0.65464, 0.65464], precision=[0.06546, 0.06546], hit=[0.65464, 0.65464], ndcg=[0.38088, 0.38088]
INFO:root:Epoch 1549 [113.1s + 40.2s]: train==[476.03958=475.93326 + 0.10664], recall=[0.66225, 0.66225], precision=[0.06623, 0.06623], hit=[0.66225, 0.66225], ndcg=[0.38182, 0.38182]
INFO:root:Epoch 1559 [110.8s + 37.7s]: train==[475.30585=475.19797 + 0.10818], recall=[0.66291, 0.66291], precision=[0.06629, 0.06629], hit=[0.66291, 0.66291], ndcg=[0.38209, 0.38209]
INFO:root:Best Iter=[125]@[167249.6]	recall=[0.66424], precision=[0.06642], hit=[0.66424], ndcg=[0.38113]
INFO:root:Namespace(Ks='[10]', batch_size=64, data_path='./data/recommendation/', dataset='ml-1m', embed_size=128, epoch=2000, gpu=2, item_density_threshold=0.01, item_threshold=30, layer_size=[128], lmbda=1, local_batch_size=512, local_epoch=1, log_name='run4_1', log_path='/home/qhuaf/graph_pri/logs/', lr=0.0001, mess_dropout=[0.1, 0.1, 0.1], model_name='two_side_graph_run4_1.pkl', num_neighbor=10, num_process=4, pretrain_epoch=300, pri_epoch=200, privacy_protect=False, regs=[1e-05], report=0, save_flag=1, test_flag='part', user_batch_size=512, verbose=1, weights_path='model/')
INFO:root:Namespace(Ks='[10]', batch_size=64, data_path='./data/recommendation/', dataset='ml-1m', embed_size=128, epoch=2000, gpu=2, item_density_threshold=0.01, item_threshold=30, layer_size=[128], lmbda=1, local_batch_size=512, local_epoch=1, log_name='run4_1', log_path='/home/qhuaf/graph_pri/logs/', lr=0.0001, mess_dropout=[0.1, 0.1, 0.1], model_name='two_side_graph_run4_1.pkl', num_neighbor=10, num_process=4, pretrain_epoch=300, pri_epoch=200, privacy_protect=False, regs=[1e-05], report=0, save_flag=1, test_flag='part', user_batch_size=512, verbose=1, weights_path='model/')
INFO:root:Epoch 9 [30.2s + 48.6s]: train==[692.99011=692.97461 + 0.01584], recall=[0.20778, 0.20778], precision=[0.02078, 0.02078], hit=[0.20778, 0.20778], ndcg=[0.09419, 0.09419]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 19 [29.5s + 49.5s]: train==[692.67523=692.65900 + 0.01584], recall=[0.20911, 0.20911], precision=[0.02091, 0.02091], hit=[0.20911, 0.20911], ndcg=[0.09539, 0.09539]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 29 [29.5s + 49.2s]: train==[692.45624=692.44031 + 0.01584], recall=[0.22219, 0.22219], precision=[0.02222, 0.02222], hit=[0.22219, 0.22219], ndcg=[0.10046, 0.10046]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 39 [30.1s + 48.5s]: train==[692.10986=692.09363 + 0.01584], recall=[0.22748, 0.22748], precision=[0.02275, 0.02275], hit=[0.22748, 0.22748], ndcg=[0.10453, 0.10453]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 49 [29.7s + 48.7s]: train==[691.74286=691.72656 + 0.01584], recall=[0.23228, 0.23228], precision=[0.02323, 0.02323], hit=[0.23228, 0.23228], ndcg=[0.10772, 0.10772]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 59 [28.8s + 50.0s]: train==[691.41553=691.39886 + 0.01584], recall=[0.24222, 0.24222], precision=[0.02422, 0.02422], hit=[0.24222, 0.24222], ndcg=[0.11211, 0.11211]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 69 [29.8s + 49.7s]: train==[690.85590=690.84039 + 0.01584], recall=[0.24934, 0.24934], precision=[0.02493, 0.02493], hit=[0.24934, 0.24934], ndcg=[0.11694, 0.11694]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 79 [29.8s + 49.4s]: train==[690.37537=690.36035 + 0.01584], recall=[0.26772, 0.26772], precision=[0.02677, 0.02677], hit=[0.26772, 0.26772], ndcg=[0.12625, 0.12625]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 89 [29.9s + 49.7s]: train==[689.71893=689.70319 + 0.01584], recall=[0.28146, 0.28146], precision=[0.02815, 0.02815], hit=[0.28146, 0.28146], ndcg=[0.13481, 0.13481]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 99 [29.6s + 49.7s]: train==[688.87036=688.85529 + 0.01584], recall=[0.29934, 0.29934], precision=[0.02993, 0.02993], hit=[0.29934, 0.29934], ndcg=[0.14617, 0.14617]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 109 [29.8s + 49.8s]: train==[687.80457=687.78754 + 0.01584], recall=[0.32136, 0.32136], precision=[0.03214, 0.03214], hit=[0.32136, 0.32136], ndcg=[0.15911, 0.15911]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 119 [30.6s + 49.6s]: train==[686.63794=686.62238 + 0.01584], recall=[0.34702, 0.34702], precision=[0.03470, 0.03470], hit=[0.34702, 0.34702], ndcg=[0.17316, 0.17316]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 129 [29.1s + 50.2s]: train==[685.29016=685.27380 + 0.01584], recall=[0.37815, 0.37815], precision=[0.03781, 0.03781], hit=[0.37815, 0.37815], ndcg=[0.19284, 0.19284]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 139 [29.1s + 49.3s]: train==[683.53320=683.51709 + 0.01585], recall=[0.40993, 0.40993], precision=[0.04099, 0.04099], hit=[0.40993, 0.40993], ndcg=[0.21626, 0.21626]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 149 [29.1s + 49.9s]: train==[681.40247=681.38550 + 0.01585], recall=[0.44950, 0.44950], precision=[0.04495, 0.04495], hit=[0.44950, 0.44950], ndcg=[0.24117, 0.24117]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 159 [29.1s + 48.9s]: train==[678.99341=678.97778 + 0.01585], recall=[0.47649, 0.47649], precision=[0.04765, 0.04765], hit=[0.47649, 0.47649], ndcg=[0.26169, 0.26169]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 169 [28.5s + 50.2s]: train==[675.93591=675.92059 + 0.01585], recall=[0.50844, 0.50844], precision=[0.05084, 0.05084], hit=[0.50844, 0.50844], ndcg=[0.28121, 0.28121]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 179 [29.8s + 50.3s]: train==[672.50085=672.48547 + 0.01585], recall=[0.54305, 0.54305], precision=[0.05430, 0.05430], hit=[0.54305, 0.54305], ndcg=[0.30306, 0.30306]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 189 [28.7s + 49.4s]: train==[668.29053=668.27399 + 0.01586], recall=[0.56109, 0.56109], precision=[0.05611, 0.05611], hit=[0.56109, 0.56109], ndcg=[0.31682, 0.31682]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 199 [29.0s + 48.6s]: train==[663.57147=663.55511 + 0.01586], recall=[0.58030, 0.58030], precision=[0.05803, 0.05803], hit=[0.58030, 0.58030], ndcg=[0.32782, 0.32782]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 209 [28.9s + 48.7s]: train==[658.62238=658.60687 + 0.01586], recall=[0.59735, 0.59735], precision=[0.05974, 0.05974], hit=[0.59735, 0.59735], ndcg=[0.34250, 0.34250]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 219 [28.5s + 50.0s]: train==[652.75635=652.73987 + 0.01587], recall=[0.60596, 0.60596], precision=[0.06060, 0.06060], hit=[0.60596, 0.60596], ndcg=[0.34924, 0.34924]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 229 [29.5s + 48.9s]: train==[646.73694=646.72125 + 0.01587], recall=[0.61689, 0.61689], precision=[0.06169, 0.06169], hit=[0.61689, 0.61689], ndcg=[0.35279, 0.35279]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 239 [28.1s + 50.2s]: train==[639.84467=639.82898 + 0.01588], recall=[0.62483, 0.62483], precision=[0.06248, 0.06248], hit=[0.62483, 0.62483], ndcg=[0.35741, 0.35741]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 249 [28.3s + 48.6s]: train==[632.38251=632.36584 + 0.01589], recall=[0.63063, 0.63063], precision=[0.06306, 0.06306], hit=[0.63063, 0.63063], ndcg=[0.36230, 0.36230]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 259 [28.4s + 49.3s]: train==[623.78748=623.77228 + 0.01589], recall=[0.63493, 0.63493], precision=[0.06349, 0.06349], hit=[0.63493, 0.63493], ndcg=[0.36694, 0.36694]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 269 [29.0s + 50.4s]: train==[615.54095=615.52539 + 0.01590], recall=[0.64272, 0.64272], precision=[0.06427, 0.06427], hit=[0.64272, 0.64272], ndcg=[0.37291, 0.37291]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 279 [28.6s + 49.5s]: train==[606.85345=606.83759 + 0.01591], recall=[0.64123, 0.64123], precision=[0.06412, 0.06412], hit=[0.64123, 0.64123], ndcg=[0.37183, 0.37183]
INFO:root:Epoch 289 [28.5s + 50.3s]: train==[597.71149=597.69623 + 0.01592], recall=[0.64073, 0.64073], precision=[0.06407, 0.06407], hit=[0.64073, 0.64073], ndcg=[0.36873, 0.36873]
INFO:root:Epoch 299 [29.0s + 50.5s]: train==[588.18408=588.16815 + 0.01593], recall=[0.64983, 0.64983], precision=[0.06498, 0.06498], hit=[0.64983, 0.64983], ndcg=[0.37387, 0.37387]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 309 [29.6s + 49.9s]: train==[579.68390=579.66785 + 0.01594], recall=[0.64454, 0.64454], precision=[0.06445, 0.06445], hit=[0.64454, 0.64454], ndcg=[0.37309, 0.37309]
INFO:root:Epoch 319 [28.8s + 50.1s]: train==[570.96191=570.94550 + 0.01595], recall=[0.64719, 0.64719], precision=[0.06472, 0.06472], hit=[0.64719, 0.64719], ndcg=[0.37484, 0.37484]
INFO:root:Epoch 329 [28.6s + 48.7s]: train==[563.05786=563.04193 + 0.01596], recall=[0.64586, 0.64586], precision=[0.06459, 0.06459], hit=[0.64586, 0.64586], ndcg=[0.37823, 0.37823]
INFO:root:Epoch 339 [29.0s + 49.8s]: train==[555.76208=555.74658 + 0.01598], recall=[0.64917, 0.64917], precision=[0.06492, 0.06492], hit=[0.64917, 0.64917], ndcg=[0.37765, 0.37765]
INFO:root:Epoch 349 [28.9s + 48.3s]: train==[546.97119=546.95483 + 0.01599], recall=[0.65381, 0.65381], precision=[0.06538, 0.06538], hit=[0.65381, 0.65381], ndcg=[0.38092, 0.38092]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 359 [29.7s + 49.2s]: train==[539.45203=539.43634 + 0.01600], recall=[0.65695, 0.65695], precision=[0.06570, 0.06570], hit=[0.65695, 0.65695], ndcg=[0.38050, 0.38050]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 369 [28.5s + 48.8s]: train==[534.40405=534.38800 + 0.01602], recall=[0.65182, 0.65182], precision=[0.06518, 0.06518], hit=[0.65182, 0.65182], ndcg=[0.37671, 0.37671]
INFO:root:Epoch 379 [28.4s + 50.4s]: train==[527.35107=527.33496 + 0.01603], recall=[0.65464, 0.65464], precision=[0.06546, 0.06546], hit=[0.65464, 0.65464], ndcg=[0.37854, 0.37854]
INFO:root:Epoch 389 [27.0s + 37.4s]: train==[522.34863=522.33301 + 0.01605], recall=[0.65646, 0.65646], precision=[0.06565, 0.06565], hit=[0.65646, 0.65646], ndcg=[0.38183, 0.38183]
INFO:root:Epoch 399 [22.9s + 39.7s]: train==[517.97028=517.95447 + 0.01606], recall=[0.65397, 0.65397], precision=[0.06540, 0.06540], hit=[0.65397, 0.65397], ndcg=[0.38087, 0.38087]
INFO:root:Epoch 409 [22.0s + 37.5s]: train==[512.06866=512.05249 + 0.01608], recall=[0.65546, 0.65546], precision=[0.06555, 0.06555], hit=[0.65546, 0.65546], ndcg=[0.37904, 0.37904]
INFO:root:Epoch 419 [22.4s + 37.8s]: train==[507.74338=507.72717 + 0.01610], recall=[0.65695, 0.65695], precision=[0.06570, 0.06570], hit=[0.65695, 0.65695], ndcg=[0.37884, 0.37884]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 429 [21.0s + 37.7s]: train==[503.93796=503.92245 + 0.01612], recall=[0.65613, 0.65613], precision=[0.06561, 0.06561], hit=[0.65613, 0.65613], ndcg=[0.38014, 0.38014]
INFO:root:Epoch 439 [22.1s + 38.0s]: train==[500.75995=500.74442 + 0.01613], recall=[0.65066, 0.65066], precision=[0.06507, 0.06507], hit=[0.65066, 0.65066], ndcg=[0.37606, 0.37606]
INFO:root:Epoch 449 [21.7s + 35.9s]: train==[496.70496=496.68884 + 0.01615], recall=[0.66076, 0.66076], precision=[0.06608, 0.06608], hit=[0.66076, 0.66076], ndcg=[0.38048, 0.38048]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 459 [21.5s + 39.0s]: train==[492.60095=492.58475 + 0.01617], recall=[0.65563, 0.65563], precision=[0.06556, 0.06556], hit=[0.65563, 0.65563], ndcg=[0.37760, 0.37760]
INFO:root:Epoch 469 [20.6s + 38.0s]: train==[491.49545=491.47958 + 0.01619], recall=[0.65662, 0.65662], precision=[0.06566, 0.06566], hit=[0.65662, 0.65662], ndcg=[0.38248, 0.38248]
INFO:root:Epoch 479 [21.6s + 38.3s]: train==[485.85349=485.83752 + 0.01621], recall=[0.65894, 0.65894], precision=[0.06589, 0.06589], hit=[0.65894, 0.65894], ndcg=[0.38346, 0.38346]
INFO:root:Epoch 489 [21.2s + 37.6s]: train==[484.04633=484.03046 + 0.01623], recall=[0.65861, 0.65861], precision=[0.06586, 0.06586], hit=[0.65861, 0.65861], ndcg=[0.38138, 0.38138]
INFO:root:Epoch 499 [20.9s + 39.8s]: train==[481.15045=481.13388 + 0.01625], recall=[0.65331, 0.65331], precision=[0.06533, 0.06533], hit=[0.65331, 0.65331], ndcg=[0.38016, 0.38016]
INFO:root:Epoch 509 [21.6s + 37.8s]: train==[478.23315=478.21716 + 0.01627], recall=[0.65877, 0.65877], precision=[0.06588, 0.06588], hit=[0.65877, 0.65877], ndcg=[0.38029, 0.38029]
INFO:root:Epoch 519 [22.2s + 37.5s]: train==[477.32071=477.30460 + 0.01629], recall=[0.66142, 0.66142], precision=[0.06614, 0.06614], hit=[0.66142, 0.66142], ndcg=[0.38273, 0.38273]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 529 [21.2s + 38.1s]: train==[473.69592=473.67966 + 0.01631], recall=[0.66060, 0.66060], precision=[0.06606, 0.06606], hit=[0.66060, 0.66060], ndcg=[0.38242, 0.38242]
INFO:root:Epoch 539 [21.1s + 37.0s]: train==[470.59796=470.58200 + 0.01633], recall=[0.65762, 0.65762], precision=[0.06576, 0.06576], hit=[0.65762, 0.65762], ndcg=[0.37808, 0.37808]
INFO:root:Epoch 549 [20.9s + 36.7s]: train==[467.65997=467.64386 + 0.01635], recall=[0.65778, 0.65778], precision=[0.06578, 0.06578], hit=[0.65778, 0.65778], ndcg=[0.38125, 0.38125]
INFO:root:Epoch 559 [21.1s + 36.4s]: train==[464.00903=463.99228 + 0.01637], recall=[0.65596, 0.65596], precision=[0.06560, 0.06560], hit=[0.65596, 0.65596], ndcg=[0.38056, 0.38056]
INFO:root:Epoch 569 [21.3s + 37.0s]: train==[461.08075=461.06497 + 0.01639], recall=[0.66093, 0.66093], precision=[0.06609, 0.06609], hit=[0.66093, 0.66093], ndcg=[0.38249, 0.38249]
INFO:root:Epoch 579 [20.7s + 37.3s]: train==[457.71564=457.69913 + 0.01641], recall=[0.65811, 0.65811], precision=[0.06581, 0.06581], hit=[0.65811, 0.65811], ndcg=[0.38170, 0.38170]
INFO:root:Epoch 589 [21.5s + 38.1s]: train==[456.17166=456.15533 + 0.01643], recall=[0.65579, 0.65579], precision=[0.06558, 0.06558], hit=[0.65579, 0.65579], ndcg=[0.38211, 0.38211]
INFO:root:Epoch 599 [20.9s + 37.4s]: train==[450.50888=450.49240 + 0.01645], recall=[0.65960, 0.65960], precision=[0.06596, 0.06596], hit=[0.65960, 0.65960], ndcg=[0.38262, 0.38262]
INFO:root:Epoch 609 [21.2s + 38.7s]: train==[448.13708=448.12036 + 0.01647], recall=[0.66043, 0.66043], precision=[0.06604, 0.06604], hit=[0.66043, 0.66043], ndcg=[0.38455, 0.38455]
INFO:root:Epoch 619 [21.6s + 36.6s]: train==[443.69150=443.67410 + 0.01649], recall=[0.66258, 0.66258], precision=[0.06626, 0.06626], hit=[0.66258, 0.66258], ndcg=[0.38313, 0.38313]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 629 [20.9s + 37.0s]: train==[442.06274=442.04675 + 0.01651], recall=[0.66026, 0.66026], precision=[0.06603, 0.06603], hit=[0.66026, 0.66026], ndcg=[0.38486, 0.38486]
INFO:root:Epoch 639 [21.8s + 37.6s]: train==[436.17245=436.15625 + 0.01653], recall=[0.65828, 0.65828], precision=[0.06583, 0.06583], hit=[0.65828, 0.65828], ndcg=[0.38383, 0.38383]
INFO:root:Epoch 649 [21.3s + 36.8s]: train==[432.57700=432.55994 + 0.01654], recall=[0.65778, 0.65778], precision=[0.06578, 0.06578], hit=[0.65778, 0.65778], ndcg=[0.37977, 0.37977]
INFO:root:Epoch 659 [20.8s + 36.8s]: train==[431.94601=431.92957 + 0.01655], recall=[0.65894, 0.65894], precision=[0.06589, 0.06589], hit=[0.65894, 0.65894], ndcg=[0.38001, 0.38001]
INFO:root:Epoch 669 [21.4s + 36.4s]: train==[423.55194=423.53598 + 0.01657], recall=[0.65993, 0.65993], precision=[0.06599, 0.06599], hit=[0.65993, 0.65993], ndcg=[0.38428, 0.38428]
INFO:root:Epoch 679 [21.6s + 36.9s]: train==[421.16983=421.15317 + 0.01659], recall=[0.66225, 0.66225], precision=[0.06623, 0.06623], hit=[0.66225, 0.66225], ndcg=[0.38542, 0.38542]
INFO:root:Epoch 689 [21.1s + 36.7s]: train==[420.68964=420.67334 + 0.01660], recall=[0.66093, 0.66093], precision=[0.06609, 0.06609], hit=[0.66093, 0.66093], ndcg=[0.38111, 0.38111]
INFO:root:Epoch 699 [23.0s + 37.8s]: train==[418.49722=418.48056 + 0.01661], recall=[0.65861, 0.65861], precision=[0.06586, 0.06586], hit=[0.65861, 0.65861], ndcg=[0.38424, 0.38424]
INFO:root:Epoch 709 [20.6s + 36.6s]: train==[414.01740=414.00073 + 0.01662], recall=[0.65778, 0.65778], precision=[0.06578, 0.06578], hit=[0.65778, 0.65778], ndcg=[0.38035, 0.38035]
INFO:root:Epoch 719 [20.9s + 37.1s]: train==[412.84204=412.82547 + 0.01663], recall=[0.66209, 0.66209], precision=[0.06621, 0.06621], hit=[0.66209, 0.66209], ndcg=[0.38246, 0.38246]
INFO:root:Epoch 729 [21.5s + 36.5s]: train==[409.86823=409.85175 + 0.01664], recall=[0.65977, 0.65977], precision=[0.06598, 0.06598], hit=[0.65977, 0.65977], ndcg=[0.38425, 0.38425]
INFO:root:Epoch 739 [21.4s + 35.9s]: train==[407.74432=407.72766 + 0.01666], recall=[0.65828, 0.65828], precision=[0.06583, 0.06583], hit=[0.65828, 0.65828], ndcg=[0.38394, 0.38394]
INFO:root:Epoch 749 [21.1s + 36.2s]: train==[408.83908=408.82214 + 0.01667], recall=[0.65464, 0.65464], precision=[0.06546, 0.06546], hit=[0.65464, 0.65464], ndcg=[0.37935, 0.37935]
INFO:root:Epoch 759 [23.1s + 38.4s]: train==[407.43918=407.42233 + 0.01668], recall=[0.66093, 0.66093], precision=[0.06609, 0.06609], hit=[0.66093, 0.66093], ndcg=[0.38382, 0.38382]
INFO:root:Epoch 769 [20.6s + 37.6s]: train==[405.14725=405.13043 + 0.01669], recall=[0.65579, 0.65579], precision=[0.06558, 0.06558], hit=[0.65579, 0.65579], ndcg=[0.38195, 0.38195]
INFO:root:Epoch 779 [21.5s + 37.2s]: train==[404.97394=404.95737 + 0.01670], recall=[0.66010, 0.66010], precision=[0.06601, 0.06601], hit=[0.66010, 0.66010], ndcg=[0.38245, 0.38245]
INFO:root:Epoch 789 [21.5s + 38.3s]: train==[404.80026=404.78345 + 0.01671], recall=[0.65911, 0.65911], precision=[0.06591, 0.06591], hit=[0.65911, 0.65911], ndcg=[0.38033, 0.38033]
INFO:root:Epoch 799 [21.5s + 36.9s]: train==[405.78464=405.76816 + 0.01672], recall=[0.66043, 0.66043], precision=[0.06604, 0.06604], hit=[0.66043, 0.66043], ndcg=[0.38017, 0.38017]
INFO:root:Epoch 809 [21.9s + 35.5s]: train==[400.85437=400.83710 + 0.01673], recall=[0.66076, 0.66076], precision=[0.06608, 0.06608], hit=[0.66076, 0.66076], ndcg=[0.38390, 0.38390]
INFO:root:Epoch 819 [21.6s + 37.6s]: train==[404.85657=404.83972 + 0.01674], recall=[0.65977, 0.65977], precision=[0.06598, 0.06598], hit=[0.65977, 0.65977], ndcg=[0.38325, 0.38325]
INFO:root:Epoch 829 [21.0s + 36.7s]: train==[403.43875=403.42221 + 0.01675], recall=[0.65960, 0.65960], precision=[0.06596, 0.06596], hit=[0.65960, 0.65960], ndcg=[0.38300, 0.38300]
INFO:root:Epoch 839 [21.7s + 36.5s]: train==[401.13818=401.12158 + 0.01676], recall=[0.65811, 0.65811], precision=[0.06581, 0.06581], hit=[0.65811, 0.65811], ndcg=[0.38201, 0.38201]
INFO:root:Epoch 849 [20.4s + 38.1s]: train==[401.91965=401.90225 + 0.01677], recall=[0.66010, 0.66010], precision=[0.06601, 0.06601], hit=[0.66010, 0.66010], ndcg=[0.38203, 0.38203]
INFO:root:Epoch 859 [22.7s + 39.9s]: train==[401.11691=401.10016 + 0.01678], recall=[0.65911, 0.65911], precision=[0.06591, 0.06591], hit=[0.65911, 0.65911], ndcg=[0.38519, 0.38519]
INFO:root:Epoch 869 [20.7s + 36.8s]: train==[401.25180=401.23553 + 0.01679], recall=[0.66093, 0.66093], precision=[0.06609, 0.06609], hit=[0.66093, 0.66093], ndcg=[0.37998, 0.37998]
INFO:root:Epoch 879 [20.9s + 37.0s]: train==[400.07104=400.05411 + 0.01680], recall=[0.66258, 0.66258], precision=[0.06626, 0.06626], hit=[0.66258, 0.66258], ndcg=[0.38483, 0.38483]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 889 [22.7s + 36.9s]: train==[396.58990=396.57245 + 0.01681], recall=[0.66374, 0.66374], precision=[0.06637, 0.06637], hit=[0.66374, 0.66374], ndcg=[0.38410, 0.38410]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 899 [21.0s + 37.6s]: train==[398.28384=398.26691 + 0.01682], recall=[0.65861, 0.65861], precision=[0.06586, 0.06586], hit=[0.65861, 0.65861], ndcg=[0.37926, 0.37926]
INFO:root:Epoch 909 [20.8s + 37.3s]: train==[398.36453=398.34772 + 0.01683], recall=[0.66341, 0.66341], precision=[0.06634, 0.06634], hit=[0.66341, 0.66341], ndcg=[0.38150, 0.38150]
INFO:root:Epoch 919 [21.6s + 38.0s]: train==[397.50397=397.48691 + 0.01684], recall=[0.66225, 0.66225], precision=[0.06623, 0.06623], hit=[0.66225, 0.66225], ndcg=[0.38007, 0.38007]
INFO:root:Epoch 929 [21.5s + 36.9s]: train==[399.87091=399.85364 + 0.01686], recall=[0.66175, 0.66175], precision=[0.06618, 0.06618], hit=[0.66175, 0.66175], ndcg=[0.38065, 0.38065]
INFO:root:Epoch 939 [20.9s + 37.2s]: train==[397.49182=397.47482 + 0.01686], recall=[0.66010, 0.66010], precision=[0.06601, 0.06601], hit=[0.66010, 0.66010], ndcg=[0.38013, 0.38013]
INFO:root:Epoch 949 [20.9s + 37.0s]: train==[399.09564=399.07809 + 0.01688], recall=[0.65844, 0.65844], precision=[0.06584, 0.06584], hit=[0.65844, 0.65844], ndcg=[0.37908, 0.37908]
INFO:root:Epoch 959 [20.8s + 37.2s]: train==[398.43585=398.41867 + 0.01688], recall=[0.66109, 0.66109], precision=[0.06611, 0.06611], hit=[0.66109, 0.66109], ndcg=[0.37973, 0.37973]
INFO:root:Epoch 969 [20.3s + 35.4s]: train==[397.58875=397.57214 + 0.01690], recall=[0.66126, 0.66126], precision=[0.06613, 0.06613], hit=[0.66126, 0.66126], ndcg=[0.37911, 0.37911]
INFO:root:Epoch 979 [20.8s + 37.9s]: train==[394.97406=394.95694 + 0.01690], recall=[0.65811, 0.65811], precision=[0.06581, 0.06581], hit=[0.65811, 0.65811], ndcg=[0.37834, 0.37834]
INFO:root:Epoch 989 [21.3s + 36.8s]: train==[395.09177=395.07486 + 0.01692], recall=[0.66589, 0.66589], precision=[0.06659, 0.06659], hit=[0.66589, 0.66589], ndcg=[0.37986, 0.37986]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 999 [21.2s + 37.8s]: train==[395.04431=395.02728 + 0.01693], recall=[0.66159, 0.66159], precision=[0.06616, 0.06616], hit=[0.66159, 0.66159], ndcg=[0.37726, 0.37726]
INFO:root:Epoch 1009 [21.3s + 39.3s]: train==[395.27432=395.25647 + 0.01694], recall=[0.66192, 0.66192], precision=[0.06619, 0.06619], hit=[0.66192, 0.66192], ndcg=[0.37805, 0.37805]
INFO:root:Epoch 1019 [23.0s + 36.7s]: train==[397.57867=397.56219 + 0.01694], recall=[0.66126, 0.66126], precision=[0.06613, 0.06613], hit=[0.66126, 0.66126], ndcg=[0.37816, 0.37816]
INFO:root:Epoch 1029 [21.6s + 38.6s]: train==[394.63074=394.61346 + 0.01695], recall=[0.66109, 0.66109], precision=[0.06611, 0.06611], hit=[0.66109, 0.66109], ndcg=[0.37900, 0.37900]
INFO:root:Epoch 1039 [20.9s + 35.9s]: train==[395.88388=395.86725 + 0.01696], recall=[0.66325, 0.66325], precision=[0.06632, 0.06632], hit=[0.66325, 0.66325], ndcg=[0.38017, 0.38017]
INFO:root:Epoch 1049 [21.6s + 40.0s]: train==[398.04776=398.03067 + 0.01698], recall=[0.65530, 0.65530], precision=[0.06553, 0.06553], hit=[0.65530, 0.65530], ndcg=[0.37471, 0.37471]
INFO:root:Epoch 1059 [17.9s + 30.2s]: train==[393.45221=393.43515 + 0.01699], recall=[0.66275, 0.66275], precision=[0.06627, 0.06627], hit=[0.66275, 0.66275], ndcg=[0.38193, 0.38193]
INFO:root:Epoch 1069 [15.6s + 31.1s]: train==[393.42773=393.41019 + 0.01699], recall=[0.66308, 0.66308], precision=[0.06631, 0.06631], hit=[0.66308, 0.66308], ndcg=[0.37830, 0.37830]
INFO:root:Epoch 1079 [15.3s + 30.5s]: train==[396.38910=396.37247 + 0.01700], recall=[0.66142, 0.66142], precision=[0.06614, 0.06614], hit=[0.66142, 0.66142], ndcg=[0.37678, 0.37678]
INFO:root:Epoch 1089 [15.3s + 30.1s]: train==[394.98831=394.97177 + 0.01701], recall=[0.66242, 0.66242], precision=[0.06624, 0.06624], hit=[0.66242, 0.66242], ndcg=[0.37994, 0.37994]
INFO:root:Epoch 1099 [15.7s + 31.2s]: train==[392.73022=392.71323 + 0.01702], recall=[0.65960, 0.65960], precision=[0.06596, 0.06596], hit=[0.65960, 0.65960], ndcg=[0.37896, 0.37896]
INFO:root:Epoch 1109 [16.9s + 33.0s]: train==[394.11484=394.09756 + 0.01704], recall=[0.66192, 0.66192], precision=[0.06619, 0.06619], hit=[0.66192, 0.66192], ndcg=[0.37819, 0.37819]
INFO:root:Epoch 1119 [14.9s + 29.4s]: train==[391.05658=391.03940 + 0.01704], recall=[0.65911, 0.65911], precision=[0.06591, 0.06591], hit=[0.65911, 0.65911], ndcg=[0.37986, 0.37986]
INFO:root:Epoch 1129 [16.8s + 30.4s]: train==[389.08234=389.06561 + 0.01706], recall=[0.66209, 0.66209], precision=[0.06621, 0.06621], hit=[0.66209, 0.66209], ndcg=[0.38067, 0.38067]
INFO:root:Epoch 1139 [15.0s + 31.0s]: train==[392.57840=392.56128 + 0.01706], recall=[0.66076, 0.66076], precision=[0.06608, 0.06608], hit=[0.66076, 0.66076], ndcg=[0.38082, 0.38082]
INFO:root:Epoch 1149 [15.9s + 30.7s]: train==[392.94141=392.92462 + 0.01707], recall=[0.66507, 0.66507], precision=[0.06651, 0.06651], hit=[0.66507, 0.66507], ndcg=[0.37853, 0.37853]
INFO:root:Epoch 1159 [17.2s + 28.9s]: train==[392.01102=391.99411 + 0.01708], recall=[0.66921, 0.66921], precision=[0.06692, 0.06692], hit=[0.66921, 0.66921], ndcg=[0.38093, 0.38093]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1169 [15.3s + 30.5s]: train==[393.33508=393.31830 + 0.01709], recall=[0.65811, 0.65811], precision=[0.06581, 0.06581], hit=[0.65811, 0.65811], ndcg=[0.37968, 0.37968]
INFO:root:Epoch 1179 [15.2s + 31.7s]: train==[392.13104=392.11398 + 0.01710], recall=[0.66060, 0.66060], precision=[0.06606, 0.06606], hit=[0.66060, 0.66060], ndcg=[0.37727, 0.37727]
INFO:root:Epoch 1189 [15.2s + 30.2s]: train==[390.16772=390.15042 + 0.01711], recall=[0.65795, 0.65795], precision=[0.06579, 0.06579], hit=[0.65795, 0.65795], ndcg=[0.37689, 0.37689]
INFO:root:Epoch 1199 [15.4s + 30.5s]: train==[391.63913=391.62186 + 0.01712], recall=[0.66126, 0.66126], precision=[0.06613, 0.06613], hit=[0.66126, 0.66126], ndcg=[0.38101, 0.38101]
INFO:root:Epoch 1209 [15.5s + 30.4s]: train==[392.63629=392.61911 + 0.01713], recall=[0.65993, 0.65993], precision=[0.06599, 0.06599], hit=[0.65993, 0.65993], ndcg=[0.37853, 0.37853]
INFO:root:Epoch 1219 [15.0s + 30.8s]: train==[393.13376=393.11673 + 0.01714], recall=[0.66159, 0.66159], precision=[0.06616, 0.06616], hit=[0.66159, 0.66159], ndcg=[0.37800, 0.37800]
INFO:root:Epoch 1229 [15.4s + 30.8s]: train==[391.52432=391.50681 + 0.01715], recall=[0.65960, 0.65960], precision=[0.06596, 0.06596], hit=[0.65960, 0.65960], ndcg=[0.37991, 0.37991]
INFO:root:Epoch 1239 [15.2s + 30.0s]: train==[392.74374=392.72656 + 0.01715], recall=[0.66076, 0.66076], precision=[0.06608, 0.06608], hit=[0.66076, 0.66076], ndcg=[0.37809, 0.37809]
INFO:root:Epoch 1249 [15.1s + 29.8s]: train==[391.44235=391.42517 + 0.01716], recall=[0.65728, 0.65728], precision=[0.06573, 0.06573], hit=[0.65728, 0.65728], ndcg=[0.37419, 0.37419]
INFO:root:Epoch 1259 [15.4s + 30.4s]: train==[392.05148=392.03394 + 0.01717], recall=[0.66258, 0.66258], precision=[0.06626, 0.06626], hit=[0.66258, 0.66258], ndcg=[0.38002, 0.38002]
INFO:root:Epoch 1269 [15.5s + 29.6s]: train==[393.63916=393.62259 + 0.01719], recall=[0.65844, 0.65844], precision=[0.06584, 0.06584], hit=[0.65844, 0.65844], ndcg=[0.37667, 0.37667]
INFO:root:Epoch 1279 [17.3s + 31.6s]: train==[391.48245=391.46582 + 0.01719], recall=[0.65728, 0.65728], precision=[0.06573, 0.06573], hit=[0.65728, 0.65728], ndcg=[0.37695, 0.37695]
INFO:root:Epoch 1289 [15.4s + 30.2s]: train==[390.43121=390.41354 + 0.01720], recall=[0.66225, 0.66225], precision=[0.06623, 0.06623], hit=[0.66225, 0.66225], ndcg=[0.37690, 0.37690]
INFO:root:Epoch 1299 [17.0s + 29.7s]: train==[390.06076=390.04391 + 0.01721], recall=[0.66043, 0.66043], precision=[0.06604, 0.06604], hit=[0.66043, 0.66043], ndcg=[0.37927, 0.37927]
INFO:root:Epoch 1309 [15.1s + 32.0s]: train==[393.56146=393.54434 + 0.01722], recall=[0.66258, 0.66258], precision=[0.06626, 0.06626], hit=[0.66258, 0.66258], ndcg=[0.37569, 0.37569]
INFO:root:Epoch 1319 [15.1s + 31.6s]: train==[391.08032=391.06317 + 0.01723], recall=[0.66474, 0.66474], precision=[0.06647, 0.06647], hit=[0.66474, 0.66474], ndcg=[0.37643, 0.37643]
INFO:root:Epoch 1329 [15.4s + 30.7s]: train==[391.41116=391.39355 + 0.01723], recall=[0.65563, 0.65563], precision=[0.06556, 0.06556], hit=[0.65563, 0.65563], ndcg=[0.37735, 0.37735]
INFO:root:Epoch 1339 [15.7s + 30.9s]: train==[390.23343=390.21609 + 0.01724], recall=[0.66192, 0.66192], precision=[0.06619, 0.06619], hit=[0.66192, 0.66192], ndcg=[0.37903, 0.37903]
INFO:root:Epoch 1349 [15.1s + 32.1s]: train==[390.61673=390.59961 + 0.01725], recall=[0.66142, 0.66142], precision=[0.06614, 0.06614], hit=[0.66142, 0.66142], ndcg=[0.38098, 0.38098]
INFO:root:Epoch 1359 [16.8s + 31.7s]: train==[389.71747=389.70026 + 0.01726], recall=[0.65861, 0.65861], precision=[0.06586, 0.06586], hit=[0.65861, 0.65861], ndcg=[0.37975, 0.37975]
INFO:root:Epoch 1369 [15.1s + 31.6s]: train==[388.29111=388.27359 + 0.01727], recall=[0.65762, 0.65762], precision=[0.06576, 0.06576], hit=[0.65762, 0.65762], ndcg=[0.37665, 0.37665]
INFO:root:Epoch 1379 [15.3s + 30.5s]: train==[392.11420=392.09631 + 0.01728], recall=[0.65762, 0.65762], precision=[0.06576, 0.06576], hit=[0.65762, 0.65762], ndcg=[0.37873, 0.37873]
INFO:root:Epoch 1389 [15.5s + 31.5s]: train==[390.11859=390.10092 + 0.01729], recall=[0.65795, 0.65795], precision=[0.06579, 0.06579], hit=[0.65795, 0.65795], ndcg=[0.37962, 0.37962]
INFO:root:Epoch 1399 [15.2s + 29.5s]: train==[392.96289=392.94534 + 0.01729], recall=[0.66209, 0.66209], precision=[0.06621, 0.06621], hit=[0.66209, 0.66209], ndcg=[0.37731, 0.37731]
INFO:root:Epoch 1409 [14.9s + 28.9s]: train==[391.27188=391.25470 + 0.01730], recall=[0.66010, 0.66010], precision=[0.06601, 0.06601], hit=[0.66010, 0.66010], ndcg=[0.37705, 0.37705]
INFO:root:Epoch 1419 [15.6s + 30.3s]: train==[390.87784=390.86066 + 0.01731], recall=[0.66159, 0.66159], precision=[0.06616, 0.06616], hit=[0.66159, 0.66159], ndcg=[0.37841, 0.37841]
INFO:root:Epoch 1429 [15.5s + 31.5s]: train==[391.54514=391.52789 + 0.01731], recall=[0.65911, 0.65911], precision=[0.06591, 0.06591], hit=[0.65911, 0.65911], ndcg=[0.38017, 0.38017]
INFO:root:Epoch 1439 [15.1s + 29.6s]: train==[390.62967=390.61212 + 0.01732], recall=[0.66142, 0.66142], precision=[0.06614, 0.06614], hit=[0.66142, 0.66142], ndcg=[0.37851, 0.37851]
INFO:root:Epoch 1449 [17.8s + 33.2s]: train==[390.93408=390.91699 + 0.01733], recall=[0.66109, 0.66109], precision=[0.06611, 0.06611], hit=[0.66109, 0.66109], ndcg=[0.37757, 0.37757]
INFO:root:Epoch 1459 [18.3s + 31.8s]: train==[393.46463=393.44791 + 0.01734], recall=[0.66209, 0.66209], precision=[0.06621, 0.06621], hit=[0.66209, 0.66209], ndcg=[0.37751, 0.37751]
INFO:root:Best Iter=[115]@[26077.3]	recall=[0.66921], precision=[0.06692], hit=[0.66921], ndcg=[0.38093]
INFO:root:Namespace(Ks='[10]', batch_size=64, data_path='./data/recommendation/', dataset='ml-1m', embed_size=128, epoch=2000, gpu=2, item_density_threshold=0.01, item_threshold=30, layer_size=[128], lmbda=1, local_batch_size=512, local_epoch=10, log_name='run4_1', log_path='/home/qhuaf/graph_pri/logs/', lr=0.0001, mess_dropout=[0.1, 0.1, 0.1], model_name='two_side_graph_run4_1.pkl', num_neighbor=10, num_process=4, pretrain_epoch=300, pri_epoch=200, privacy_protect=False, regs=[1e-05], report=0, save_flag=1, test_flag='part', user_batch_size=512, verbose=1, weights_path='model/')
INFO:root:Epoch 9 [61.9s + 30.3s]: train==[691.58380=691.56683 + 0.01584], recall=[0.22781, 0.22781], precision=[0.02278, 0.02278], hit=[0.22781, 0.22781], ndcg=[0.10723, 0.10723]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 19 [62.7s + 30.6s]: train==[686.42194=686.40570 + 0.01584], recall=[0.30298, 0.30298], precision=[0.03030, 0.03030], hit=[0.30298, 0.30298], ndcg=[0.15537, 0.15537]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 29 [62.5s + 30.5s]: train==[668.43860=668.42218 + 0.01584], recall=[0.43245, 0.43245], precision=[0.04325, 0.04325], hit=[0.43245, 0.43245], ndcg=[0.24922, 0.24922]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 39 [61.9s + 30.3s]: train==[629.81958=629.80408 + 0.01586], recall=[0.52616, 0.52616], precision=[0.05262, 0.05262], hit=[0.52616, 0.52616], ndcg=[0.31196, 0.31196]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 49 [63.8s + 30.3s]: train==[580.72125=580.70502 + 0.01588], recall=[0.57368, 0.57368], precision=[0.05737, 0.05737], hit=[0.57368, 0.57368], ndcg=[0.33636, 0.33636]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 59 [63.0s + 30.3s]: train==[538.65485=538.63843 + 0.01591], recall=[0.59868, 0.59868], precision=[0.05987, 0.05987], hit=[0.59868, 0.59868], ndcg=[0.35061, 0.35061]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 69 [65.3s + 30.4s]: train==[506.91040=506.89392 + 0.01595], recall=[0.61523, 0.61523], precision=[0.06152, 0.06152], hit=[0.61523, 0.61523], ndcg=[0.36206, 0.36206]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 79 [65.9s + 31.4s]: train==[479.24744=479.23175 + 0.01600], recall=[0.62980, 0.62980], precision=[0.06298, 0.06298], hit=[0.62980, 0.62980], ndcg=[0.36703, 0.36703]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 89 [61.3s + 30.9s]: train==[460.41370=460.39819 + 0.01605], recall=[0.64222, 0.64222], precision=[0.06422, 0.06422], hit=[0.64222, 0.64222], ndcg=[0.37412, 0.37412]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 99 [61.4s + 29.8s]: train==[448.71536=448.69919 + 0.01610], recall=[0.63957, 0.63957], precision=[0.06396, 0.06396], hit=[0.63957, 0.63957], ndcg=[0.37509, 0.37509]
INFO:root:Epoch 109 [63.5s + 30.6s]: train==[442.85013=442.83432 + 0.01615], recall=[0.64570, 0.64570], precision=[0.06457, 0.06457], hit=[0.64570, 0.64570], ndcg=[0.37645, 0.37645]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 119 [105.7s + 51.4s]: train==[434.47302=434.45676 + 0.01621], recall=[0.64801, 0.64801], precision=[0.06480, 0.06480], hit=[0.64801, 0.64801], ndcg=[0.37718, 0.37718]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 129 [107.5s + 51.7s]: train==[426.32364=426.30756 + 0.01627], recall=[0.64983, 0.64983], precision=[0.06498, 0.06498], hit=[0.64983, 0.64983], ndcg=[0.37763, 0.37763]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 139 [104.9s + 52.4s]: train==[422.40570=422.38898 + 0.01633], recall=[0.65116, 0.65116], precision=[0.06512, 0.06512], hit=[0.65116, 0.65116], ndcg=[0.37758, 0.37758]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 149 [107.4s + 50.9s]: train==[418.02664=418.01031 + 0.01640], recall=[0.65298, 0.65298], precision=[0.06530, 0.06530], hit=[0.65298, 0.65298], ndcg=[0.37844, 0.37844]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 159 [105.6s + 52.3s]: train==[413.01642=413.00046 + 0.01647], recall=[0.65232, 0.65232], precision=[0.06523, 0.06523], hit=[0.65232, 0.65232], ndcg=[0.37676, 0.37676]
INFO:root:Epoch 169 [105.8s + 51.2s]: train==[408.88202=408.86572 + 0.01655], recall=[0.65546, 0.65546], precision=[0.06555, 0.06555], hit=[0.65546, 0.65546], ndcg=[0.38237, 0.38237]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 179 [94.6s + 45.5s]: train==[409.00552=408.98941 + 0.01663], recall=[0.65414, 0.65414], precision=[0.06541, 0.06541], hit=[0.65414, 0.65414], ndcg=[0.38027, 0.38027]
INFO:root:Epoch 189 [92.9s + 46.1s]: train==[405.66382=405.64755 + 0.01672], recall=[0.64834, 0.64834], precision=[0.06483, 0.06483], hit=[0.64834, 0.64834], ndcg=[0.37876, 0.37876]
INFO:root:Epoch 199 [61.9s + 30.1s]: train==[404.22250=404.20581 + 0.01681], recall=[0.65795, 0.65795], precision=[0.06579, 0.06579], hit=[0.65795, 0.65795], ndcg=[0.38209, 0.38209]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 209 [62.0s + 30.1s]: train==[404.00751=403.99078 + 0.01690], recall=[0.65629, 0.65629], precision=[0.06563, 0.06563], hit=[0.65629, 0.65629], ndcg=[0.38228, 0.38228]
INFO:root:Epoch 219 [64.7s + 30.0s]: train==[401.64532=401.62851 + 0.01699], recall=[0.65712, 0.65712], precision=[0.06571, 0.06571], hit=[0.65712, 0.65712], ndcg=[0.38167, 0.38167]
INFO:root:Epoch 229 [62.8s + 30.7s]: train==[401.42349=401.40588 + 0.01709], recall=[0.65480, 0.65480], precision=[0.06548, 0.06548], hit=[0.65480, 0.65480], ndcg=[0.38099, 0.38099]
INFO:root:Epoch 239 [65.8s + 32.3s]: train==[397.86310=397.84598 + 0.01718], recall=[0.65331, 0.65331], precision=[0.06533, 0.06533], hit=[0.65331, 0.65331], ndcg=[0.38352, 0.38352]
INFO:root:Epoch 249 [59.2s + 30.8s]: train==[395.45074=395.43375 + 0.01728], recall=[0.65000, 0.65000], precision=[0.06500, 0.06500], hit=[0.65000, 0.65000], ndcg=[0.37750, 0.37750]
INFO:root:Epoch 259 [59.9s + 28.9s]: train==[397.66483=397.64761 + 0.01737], recall=[0.65497, 0.65497], precision=[0.06550, 0.06550], hit=[0.65497, 0.65497], ndcg=[0.38269, 0.38269]
INFO:root:Epoch 269 [59.6s + 29.2s]: train==[397.47964=397.46222 + 0.01747], recall=[0.65381, 0.65381], precision=[0.06538, 0.06538], hit=[0.65381, 0.65381], ndcg=[0.38333, 0.38333]
INFO:root:Epoch 279 [59.6s + 30.2s]: train==[396.71713=396.70004 + 0.01757], recall=[0.65513, 0.65513], precision=[0.06551, 0.06551], hit=[0.65513, 0.65513], ndcg=[0.37949, 0.37949]
INFO:root:Epoch 289 [62.1s + 29.1s]: train==[396.48734=396.46994 + 0.01767], recall=[0.65828, 0.65828], precision=[0.06583, 0.06583], hit=[0.65828, 0.65828], ndcg=[0.38420, 0.38420]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 299 [61.2s + 29.7s]: train==[395.64777=395.63055 + 0.01775], recall=[0.65248, 0.65248], precision=[0.06525, 0.06525], hit=[0.65248, 0.65248], ndcg=[0.38075, 0.38075]
INFO:root:Epoch 309 [61.2s + 30.8s]: train==[396.60129=396.58408 + 0.01785], recall=[0.65447, 0.65447], precision=[0.06545, 0.06545], hit=[0.65447, 0.65447], ndcg=[0.38157, 0.38157]
INFO:root:Epoch 319 [62.5s + 30.0s]: train==[395.02618=395.00830 + 0.01794], recall=[0.65066, 0.65066], precision=[0.06507, 0.06507], hit=[0.65066, 0.65066], ndcg=[0.38080, 0.38080]
INFO:root:Epoch 329 [62.3s + 30.3s]: train==[397.71124=397.69318 + 0.01803], recall=[0.65563, 0.65563], precision=[0.06556, 0.06556], hit=[0.65563, 0.65563], ndcg=[0.38159, 0.38159]
INFO:root:Epoch 339 [60.9s + 28.6s]: train==[394.64261=394.62430 + 0.01812], recall=[0.65166, 0.65166], precision=[0.06517, 0.06517], hit=[0.65166, 0.65166], ndcg=[0.37766, 0.37766]
INFO:root:Epoch 349 [62.8s + 29.6s]: train==[396.92285=396.90448 + 0.01821], recall=[0.65414, 0.65414], precision=[0.06541, 0.06541], hit=[0.65414, 0.65414], ndcg=[0.38188, 0.38188]
INFO:root:Epoch 359 [61.5s + 29.7s]: train==[398.74454=398.72620 + 0.01831], recall=[0.65811, 0.65811], precision=[0.06581, 0.06581], hit=[0.65811, 0.65811], ndcg=[0.38335, 0.38335]
INFO:root:Epoch 369 [63.5s + 29.7s]: train==[397.11670=397.09830 + 0.01841], recall=[0.65679, 0.65679], precision=[0.06568, 0.06568], hit=[0.65679, 0.65679], ndcg=[0.38224, 0.38224]
INFO:root:Epoch 379 [61.2s + 29.2s]: train==[397.27066=397.25204 + 0.01850], recall=[0.65265, 0.65265], precision=[0.06526, 0.06526], hit=[0.65265, 0.65265], ndcg=[0.37670, 0.37670]
INFO:root:Epoch 389 [62.6s + 31.5s]: train==[399.56668=399.54819 + 0.01860], recall=[0.65563, 0.65563], precision=[0.06556, 0.06556], hit=[0.65563, 0.65563], ndcg=[0.38006, 0.38006]
INFO:root:Epoch 399 [62.9s + 30.0s]: train==[398.32214=398.30334 + 0.01870], recall=[0.65613, 0.65613], precision=[0.06561, 0.06561], hit=[0.65613, 0.65613], ndcg=[0.38019, 0.38019]
INFO:root:Epoch 409 [63.3s + 29.7s]: train==[397.66013=397.64087 + 0.01880], recall=[0.65066, 0.65066], precision=[0.06507, 0.06507], hit=[0.65066, 0.65066], ndcg=[0.37806, 0.37806]
INFO:root:Epoch 419 [63.6s + 32.0s]: train==[400.00031=399.98160 + 0.01890], recall=[0.65546, 0.65546], precision=[0.06555, 0.06555], hit=[0.65546, 0.65546], ndcg=[0.38035, 0.38035]
INFO:root:Epoch 429 [62.5s + 30.2s]: train==[397.28461=397.26575 + 0.01900], recall=[0.65894, 0.65894], precision=[0.06589, 0.06589], hit=[0.65894, 0.65894], ndcg=[0.38417, 0.38417]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 439 [62.7s + 29.2s]: train==[396.57004=396.55127 + 0.01909], recall=[0.65430, 0.65430], precision=[0.06543, 0.06543], hit=[0.65430, 0.65430], ndcg=[0.38321, 0.38321]
INFO:root:Epoch 449 [60.5s + 31.0s]: train==[399.22186=399.20212 + 0.01919], recall=[0.65017, 0.65017], precision=[0.06502, 0.06502], hit=[0.65017, 0.65017], ndcg=[0.38023, 0.38023]
INFO:root:Epoch 459 [64.2s + 31.9s]: train==[397.39609=397.37747 + 0.01930], recall=[0.65596, 0.65596], precision=[0.06560, 0.06560], hit=[0.65596, 0.65596], ndcg=[0.38403, 0.38403]
INFO:root:Epoch 469 [61.7s + 31.8s]: train==[400.65912=400.63977 + 0.01940], recall=[0.65728, 0.65728], precision=[0.06573, 0.06573], hit=[0.65728, 0.65728], ndcg=[0.38353, 0.38353]
INFO:root:Epoch 479 [62.3s + 30.4s]: train==[398.95578=398.93625 + 0.01950], recall=[0.65166, 0.65166], precision=[0.06517, 0.06517], hit=[0.65166, 0.65166], ndcg=[0.37903, 0.37903]
INFO:root:Epoch 489 [62.2s + 30.2s]: train==[398.09262=398.07321 + 0.01960], recall=[0.65166, 0.65166], precision=[0.06517, 0.06517], hit=[0.65166, 0.65166], ndcg=[0.37827, 0.37827]
INFO:root:Epoch 499 [61.0s + 28.0s]: train==[399.38675=399.36667 + 0.01971], recall=[0.65530, 0.65530], precision=[0.06553, 0.06553], hit=[0.65530, 0.65530], ndcg=[0.38242, 0.38242]
INFO:root:Epoch 509 [60.3s + 28.6s]: train==[399.79163=399.77191 + 0.01981], recall=[0.65911, 0.65911], precision=[0.06591, 0.06591], hit=[0.65911, 0.65911], ndcg=[0.38087, 0.38087]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 519 [60.9s + 30.1s]: train==[399.74042=399.72086 + 0.01993], recall=[0.65414, 0.65414], precision=[0.06541, 0.06541], hit=[0.65414, 0.65414], ndcg=[0.37916, 0.37916]
INFO:root:Epoch 529 [60.4s + 30.0s]: train==[399.37729=399.35739 + 0.02004], recall=[0.66192, 0.66192], precision=[0.06619, 0.06619], hit=[0.66192, 0.66192], ndcg=[0.38467, 0.38467]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 539 [61.4s + 31.9s]: train==[401.29779=401.27686 + 0.02014], recall=[0.65629, 0.65629], precision=[0.06563, 0.06563], hit=[0.65629, 0.65629], ndcg=[0.38197, 0.38197]
INFO:root:Epoch 549 [62.2s + 30.5s]: train==[399.06320=399.04254 + 0.02026], recall=[0.65861, 0.65861], precision=[0.06586, 0.06586], hit=[0.65861, 0.65861], ndcg=[0.38124, 0.38124]
INFO:root:Epoch 559 [63.8s + 29.0s]: train==[398.26453=398.24420 + 0.02037], recall=[0.65530, 0.65530], precision=[0.06553, 0.06553], hit=[0.65530, 0.65530], ndcg=[0.38297, 0.38297]
INFO:root:Epoch 569 [60.9s + 30.9s]: train==[398.26846=398.24783 + 0.02048], recall=[0.65348, 0.65348], precision=[0.06535, 0.06535], hit=[0.65348, 0.65348], ndcg=[0.38152, 0.38152]
INFO:root:Epoch 579 [61.7s + 28.5s]: train==[398.37442=398.35388 + 0.02060], recall=[0.65464, 0.65464], precision=[0.06546, 0.06546], hit=[0.65464, 0.65464], ndcg=[0.38124, 0.38124]
INFO:root:Epoch 589 [62.1s + 29.0s]: train==[398.31091=398.29028 + 0.02070], recall=[0.65662, 0.65662], precision=[0.06566, 0.06566], hit=[0.65662, 0.65662], ndcg=[0.38069, 0.38069]
INFO:root:Epoch 599 [62.2s + 30.8s]: train==[397.07965=397.05905 + 0.02084], recall=[0.64983, 0.64983], precision=[0.06498, 0.06498], hit=[0.64983, 0.64983], ndcg=[0.37872, 0.37872]
INFO:root:Epoch 609 [64.5s + 30.6s]: train==[397.61838=397.59732 + 0.02095], recall=[0.65728, 0.65728], precision=[0.06573, 0.06573], hit=[0.65728, 0.65728], ndcg=[0.38031, 0.38031]
INFO:root:Epoch 619 [60.3s + 29.2s]: train==[397.73181=397.71082 + 0.02107], recall=[0.65679, 0.65679], precision=[0.06568, 0.06568], hit=[0.65679, 0.65679], ndcg=[0.38130, 0.38130]
INFO:root:Epoch 629 [63.1s + 30.3s]: train==[398.23566=398.21460 + 0.02119], recall=[0.65265, 0.65265], precision=[0.06526, 0.06526], hit=[0.65265, 0.65265], ndcg=[0.38115, 0.38115]
INFO:root:Epoch 639 [63.7s + 28.4s]: train==[397.57449=397.55371 + 0.02132], recall=[0.65679, 0.65679], precision=[0.06568, 0.06568], hit=[0.65679, 0.65679], ndcg=[0.38000, 0.38000]
INFO:root:Epoch 649 [62.0s + 30.1s]: train==[397.47488=397.45312 + 0.02144], recall=[0.65629, 0.65629], precision=[0.06563, 0.06563], hit=[0.65629, 0.65629], ndcg=[0.38214, 0.38214]
INFO:root:Epoch 659 [63.5s + 30.6s]: train==[394.63046=394.60883 + 0.02156], recall=[0.65844, 0.65844], precision=[0.06584, 0.06584], hit=[0.65844, 0.65844], ndcg=[0.38229, 0.38229]
INFO:root:Epoch 669 [62.5s + 30.7s]: train==[395.56726=395.54575 + 0.02170], recall=[0.65745, 0.65745], precision=[0.06575, 0.06575], hit=[0.65745, 0.65745], ndcg=[0.38273, 0.38273]
INFO:root:Epoch 679 [63.8s + 31.0s]: train==[393.53534=393.51343 + 0.02182], recall=[0.65397, 0.65397], precision=[0.06540, 0.06540], hit=[0.65397, 0.65397], ndcg=[0.38016, 0.38016]
INFO:root:Epoch 689 [61.8s + 28.5s]: train==[396.66705=396.64548 + 0.02195], recall=[0.65000, 0.65000], precision=[0.06500, 0.06500], hit=[0.65000, 0.65000], ndcg=[0.37648, 0.37648]
INFO:root:Epoch 699 [69.6s + 33.3s]: train==[395.51584=395.49359 + 0.02208], recall=[0.65182, 0.65182], precision=[0.06518, 0.06518], hit=[0.65182, 0.65182], ndcg=[0.38201, 0.38201]
INFO:root:Epoch 709 [63.5s + 30.4s]: train==[394.59793=394.57562 + 0.02220], recall=[0.65861, 0.65861], precision=[0.06586, 0.06586], hit=[0.65861, 0.65861], ndcg=[0.37993, 0.37993]
INFO:root:Epoch 719 [63.7s + 32.5s]: train==[394.14569=394.12305 + 0.02233], recall=[0.65877, 0.65877], precision=[0.06588, 0.06588], hit=[0.65877, 0.65877], ndcg=[0.38285, 0.38285]
INFO:root:Epoch 729 [62.4s + 29.8s]: train==[391.15146=391.12869 + 0.02248], recall=[0.65662, 0.65662], precision=[0.06566, 0.06566], hit=[0.65662, 0.65662], ndcg=[0.38047, 0.38047]
INFO:root:Epoch 739 [60.6s + 30.1s]: train==[394.01474=393.99158 + 0.02263], recall=[0.65232, 0.65232], precision=[0.06523, 0.06523], hit=[0.65232, 0.65232], ndcg=[0.38073, 0.38073]
INFO:root:Epoch 749 [61.6s + 31.0s]: train==[394.39005=394.36682 + 0.02276], recall=[0.65579, 0.65579], precision=[0.06558, 0.06558], hit=[0.65579, 0.65579], ndcg=[0.37960, 0.37960]
INFO:root:Epoch 759 [62.4s + 30.2s]: train==[389.49670=389.47351 + 0.02291], recall=[0.65844, 0.65844], precision=[0.06584, 0.06584], hit=[0.65844, 0.65844], ndcg=[0.38279, 0.38279]
INFO:root:Epoch 769 [63.0s + 29.9s]: train==[392.43503=392.41248 + 0.02303], recall=[0.65166, 0.65166], precision=[0.06517, 0.06517], hit=[0.65166, 0.65166], ndcg=[0.37821, 0.37821]
INFO:root:Epoch 779 [62.1s + 30.3s]: train==[392.90698=392.88412 + 0.02319], recall=[0.65795, 0.65795], precision=[0.06579, 0.06579], hit=[0.65795, 0.65795], ndcg=[0.38080, 0.38080]
INFO:root:Epoch 789 [62.2s + 31.4s]: train==[389.33987=389.31665 + 0.02333], recall=[0.65497, 0.65497], precision=[0.06550, 0.06550], hit=[0.65497, 0.65497], ndcg=[0.38161, 0.38161]
INFO:root:Epoch 799 [62.8s + 30.3s]: train==[391.84937=391.82526 + 0.02350], recall=[0.65563, 0.65563], precision=[0.06556, 0.06556], hit=[0.65563, 0.65563], ndcg=[0.37928, 0.37928]
INFO:root:Epoch 809 [63.6s + 31.4s]: train==[388.66721=388.64380 + 0.02362], recall=[0.65050, 0.65050], precision=[0.06505, 0.06505], hit=[0.65050, 0.65050], ndcg=[0.37866, 0.37866]
INFO:root:Epoch 819 [62.8s + 30.3s]: train==[391.03281=391.00885 + 0.02378], recall=[0.65944, 0.65944], precision=[0.06594, 0.06594], hit=[0.65944, 0.65944], ndcg=[0.38342, 0.38342]
INFO:root:Epoch 829 [62.9s + 31.6s]: train==[386.78448=386.76108 + 0.02394], recall=[0.66109, 0.66109], precision=[0.06611, 0.06611], hit=[0.66109, 0.66109], ndcg=[0.38178, 0.38178]
INFO:root:Best Iter=[52]@[52234.8]	recall=[0.66192], precision=[0.06619], hit=[0.66192], ndcg=[0.38467]
INFO:root:Namespace(Ks='[10]', batch_size=64, data_path='./data/recommendation/', dataset='ml-1m', embed_size=128, epoch=2000, gpu=2, item_density_threshold=0.01, item_threshold=30, layer_size=[128], lmbda=1, local_batch_size=512, local_epoch=20, log_name='run4_1', log_path='/home/qhuaf/graph_pri/logs/', lr=0.0001, mess_dropout=[0.1, 0.1, 0.1], model_name='two_side_graph_run4_1.pkl', num_neighbor=10, num_process=4, pretrain_epoch=300, pri_epoch=200, privacy_protect=False, regs=[1e-05], report=0, save_flag=1, test_flag='part', user_batch_size=512, verbose=1, weights_path='model/')
INFO:root:Epoch 9 [121.9s + 33.0s]: train==[688.68951=688.67346 + 0.01584], recall=[0.25894, 0.25894], precision=[0.02589, 0.02589], hit=[0.25894, 0.25894], ndcg=[0.12334, 0.12334]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 19 [120.1s + 36.7s]: train==[646.49695=646.48090 + 0.01585], recall=[0.47036, 0.47036], precision=[0.04704, 0.04704], hit=[0.47036, 0.47036], ndcg=[0.27035, 0.27035]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 29 [118.4s + 34.8s]: train==[560.62231=560.60645 + 0.01590], recall=[0.58295, 0.58295], precision=[0.05829, 0.05829], hit=[0.58295, 0.58295], ndcg=[0.33684, 0.33684]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 39 [120.1s + 33.7s]: train==[496.96338=496.94702 + 0.01598], recall=[0.61887, 0.61887], precision=[0.06189, 0.06189], hit=[0.61887, 0.61887], ndcg=[0.35882, 0.35882]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 49 [120.9s + 34.6s]: train==[463.20432=463.18851 + 0.01608], recall=[0.63543, 0.63543], precision=[0.06354, 0.06354], hit=[0.63543, 0.63543], ndcg=[0.36735, 0.36735]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 59 [119.9s + 35.4s]: train==[444.24957=444.23322 + 0.01620], recall=[0.64089, 0.64089], precision=[0.06409, 0.06409], hit=[0.64089, 0.64089], ndcg=[0.36926, 0.36926]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 69 [118.9s + 34.9s]: train==[432.41351=432.39685 + 0.01634], recall=[0.64503, 0.64503], precision=[0.06450, 0.06450], hit=[0.64503, 0.64503], ndcg=[0.37475, 0.37475]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 79 [119.2s + 35.0s]: train==[423.33231=423.31549 + 0.01650], recall=[0.65132, 0.65132], precision=[0.06513, 0.06513], hit=[0.65132, 0.65132], ndcg=[0.37679, 0.37679]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 89 [122.1s + 33.9s]: train==[417.55365=417.53723 + 0.01668], recall=[0.65050, 0.65050], precision=[0.06505, 0.06505], hit=[0.65050, 0.65050], ndcg=[0.37519, 0.37519]
INFO:root:Epoch 99 [116.7s + 32.5s]: train==[408.12753=408.11029 + 0.01687], recall=[0.64636, 0.64636], precision=[0.06464, 0.06464], hit=[0.64636, 0.64636], ndcg=[0.37671, 0.37671]
INFO:root:Epoch 109 [118.5s + 35.3s]: train==[403.25369=403.23660 + 0.01708], recall=[0.65099, 0.65099], precision=[0.06510, 0.06510], hit=[0.65099, 0.65099], ndcg=[0.37929, 0.37929]
INFO:root:Epoch 119 [108.1s + 30.6s]: train==[404.39072=404.37305 + 0.01731], recall=[0.65149, 0.65149], precision=[0.06515, 0.06515], hit=[0.65149, 0.65149], ndcg=[0.37660, 0.37660]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 129 [112.9s + 30.6s]: train==[397.18051=397.16296 + 0.01754], recall=[0.65215, 0.65215], precision=[0.06522, 0.06522], hit=[0.65215, 0.65215], ndcg=[0.38125, 0.38125]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 139 [104.6s + 30.7s]: train==[399.43799=399.42041 + 0.01779], recall=[0.65116, 0.65116], precision=[0.06512, 0.06512], hit=[0.65116, 0.65116], ndcg=[0.37961, 0.37961]
INFO:root:Epoch 149 [106.6s + 31.6s]: train==[397.61124=397.59280 + 0.01805], recall=[0.64934, 0.64934], precision=[0.06493, 0.06493], hit=[0.64934, 0.64934], ndcg=[0.37960, 0.37960]
INFO:root:Epoch 159 [109.3s + 31.2s]: train==[395.11182=395.09363 + 0.01832], recall=[0.65149, 0.65149], precision=[0.06515, 0.06515], hit=[0.65149, 0.65149], ndcg=[0.37893, 0.37893]
INFO:root:Epoch 169 [109.9s + 31.7s]: train==[397.83813=397.81934 + 0.01858], recall=[0.65348, 0.65348], precision=[0.06535, 0.06535], hit=[0.65348, 0.65348], ndcg=[0.38141, 0.38141]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 179 [108.6s + 31.6s]: train==[397.10718=397.08798 + 0.01884], recall=[0.65629, 0.65629], precision=[0.06563, 0.06563], hit=[0.65629, 0.65629], ndcg=[0.38001, 0.38001]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 189 [109.0s + 30.3s]: train==[395.06573=395.04669 + 0.01911], recall=[0.64967, 0.64967], precision=[0.06497, 0.06497], hit=[0.64967, 0.64967], ndcg=[0.37713, 0.37713]
INFO:root:Epoch 199 [109.1s + 30.9s]: train==[394.60739=394.58832 + 0.01939], recall=[0.65430, 0.65430], precision=[0.06543, 0.06543], hit=[0.65430, 0.65430], ndcg=[0.37954, 0.37954]
INFO:root:Epoch 209 [106.3s + 32.5s]: train==[396.49817=396.47830 + 0.01966], recall=[0.65298, 0.65298], precision=[0.06530, 0.06530], hit=[0.65298, 0.65298], ndcg=[0.38042, 0.38042]
INFO:root:Epoch 219 [109.9s + 30.4s]: train==[396.08194=396.06241 + 0.01993], recall=[0.65447, 0.65447], precision=[0.06545, 0.06545], hit=[0.65447, 0.65447], ndcg=[0.38058, 0.38058]
INFO:root:Epoch 229 [110.9s + 30.1s]: train==[394.83438=394.81430 + 0.02021], recall=[0.65695, 0.65695], precision=[0.06570, 0.06570], hit=[0.65695, 0.65695], ndcg=[0.38157, 0.38157]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 239 [107.1s + 33.8s]: train==[393.26953=393.24945 + 0.02050], recall=[0.65331, 0.65331], precision=[0.06533, 0.06533], hit=[0.65331, 0.65331], ndcg=[0.37717, 0.37717]
INFO:root:Epoch 249 [113.0s + 31.4s]: train==[395.56671=395.54596 + 0.02080], recall=[0.64983, 0.64983], precision=[0.06498, 0.06498], hit=[0.64983, 0.64983], ndcg=[0.37826, 0.37826]
INFO:root:Epoch 259 [110.0s + 32.2s]: train==[391.92484=391.90375 + 0.02110], recall=[0.65331, 0.65331], precision=[0.06533, 0.06533], hit=[0.65331, 0.65331], ndcg=[0.37692, 0.37692]
INFO:root:Epoch 269 [107.7s + 32.3s]: train==[392.48706=392.46625 + 0.02140], recall=[0.65298, 0.65298], precision=[0.06530, 0.06530], hit=[0.65298, 0.65298], ndcg=[0.37797, 0.37797]
INFO:root:Epoch 279 [107.8s + 31.5s]: train==[392.77423=392.75305 + 0.02171], recall=[0.65331, 0.65331], precision=[0.06533, 0.06533], hit=[0.65331, 0.65331], ndcg=[0.37758, 0.37758]
INFO:root:Epoch 289 [108.8s + 32.1s]: train==[392.79675=392.77484 + 0.02203], recall=[0.65497, 0.65497], precision=[0.06550, 0.06550], hit=[0.65497, 0.65497], ndcg=[0.37860, 0.37860]
INFO:root:Epoch 299 [106.1s + 31.0s]: train==[392.65063=392.62848 + 0.02235], recall=[0.65364, 0.65364], precision=[0.06536, 0.06536], hit=[0.65364, 0.65364], ndcg=[0.38228, 0.38228]
INFO:root:Epoch 309 [106.8s + 31.9s]: train==[391.04193=391.01962 + 0.02268], recall=[0.65745, 0.65745], precision=[0.06575, 0.06575], hit=[0.65745, 0.65745], ndcg=[0.38412, 0.38412]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 319 [107.0s + 30.6s]: train==[391.78412=391.76077 + 0.02302], recall=[0.65464, 0.65464], precision=[0.06546, 0.06546], hit=[0.65464, 0.65464], ndcg=[0.38033, 0.38033]
INFO:root:Epoch 329 [110.0s + 31.8s]: train==[390.66080=390.63766 + 0.02333], recall=[0.65397, 0.65397], precision=[0.06540, 0.06540], hit=[0.65397, 0.65397], ndcg=[0.37839, 0.37839]
INFO:root:Epoch 339 [106.3s + 31.9s]: train==[390.78986=390.76630 + 0.02370], recall=[0.64950, 0.64950], precision=[0.06495, 0.06495], hit=[0.64950, 0.64950], ndcg=[0.37702, 0.37702]
INFO:root:Epoch 349 [110.2s + 30.6s]: train==[390.75766=390.73370 + 0.02407], recall=[0.65348, 0.65348], precision=[0.06535, 0.06535], hit=[0.65348, 0.65348], ndcg=[0.37924, 0.37924]
INFO:root:Epoch 359 [109.1s + 30.9s]: train==[388.65762=388.63330 + 0.02440], recall=[0.65563, 0.65563], precision=[0.06556, 0.06556], hit=[0.65563, 0.65563], ndcg=[0.38118, 0.38118]
INFO:root:Epoch 369 [106.8s + 32.5s]: train==[390.17633=390.15170 + 0.02476], recall=[0.64619, 0.64619], precision=[0.06462, 0.06462], hit=[0.64619, 0.64619], ndcg=[0.37587, 0.37587]
INFO:root:Epoch 379 [106.4s + 31.2s]: train==[390.19046=390.16519 + 0.02513], recall=[0.65695, 0.65695], precision=[0.06570, 0.06570], hit=[0.65695, 0.65695], ndcg=[0.38110, 0.38110]
INFO:root:Epoch 389 [108.9s + 32.1s]: train==[390.33017=390.30466 + 0.02552], recall=[0.65430, 0.65430], precision=[0.06543, 0.06543], hit=[0.65430, 0.65430], ndcg=[0.37997, 0.37997]
INFO:root:Epoch 399 [110.3s + 30.7s]: train==[389.39474=389.36832 + 0.02590], recall=[0.65530, 0.65530], precision=[0.06553, 0.06553], hit=[0.65530, 0.65530], ndcg=[0.38243, 0.38243]
INFO:root:Epoch 409 [106.8s + 30.0s]: train==[389.56747=389.54141 + 0.02629], recall=[0.65050, 0.65050], precision=[0.06505, 0.06505], hit=[0.65050, 0.65050], ndcg=[0.37833, 0.37833]
INFO:root:Epoch 419 [111.5s + 30.4s]: train==[389.75229=389.72598 + 0.02669], recall=[0.65331, 0.65331], precision=[0.06533, 0.06533], hit=[0.65331, 0.65331], ndcg=[0.38085, 0.38085]
INFO:root:Epoch 429 [111.5s + 31.8s]: train==[388.52353=388.49677 + 0.02708], recall=[0.65911, 0.65911], precision=[0.06591, 0.06591], hit=[0.65911, 0.65911], ndcg=[0.38149, 0.38149]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 439 [106.8s + 32.0s]: train==[384.84375=384.81625 + 0.02748], recall=[0.65397, 0.65397], precision=[0.06540, 0.06540], hit=[0.65397, 0.65397], ndcg=[0.37975, 0.37975]
INFO:root:Epoch 449 [112.1s + 29.3s]: train==[387.10684=387.07870 + 0.02787], recall=[0.65944, 0.65944], precision=[0.06594, 0.06594], hit=[0.65944, 0.65944], ndcg=[0.38414, 0.38414]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 459 [109.7s + 30.8s]: train==[386.32092=386.29279 + 0.02828], recall=[0.65646, 0.65646], precision=[0.06565, 0.06565], hit=[0.65646, 0.65646], ndcg=[0.38305, 0.38305]
INFO:root:Epoch 469 [107.6s + 31.4s]: train==[385.48242=385.45377 + 0.02867], recall=[0.65993, 0.65993], precision=[0.06599, 0.06599], hit=[0.65993, 0.65993], ndcg=[0.38316, 0.38316]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 479 [113.3s + 31.8s]: train==[386.14481=386.11588 + 0.02909], recall=[0.65364, 0.65364], precision=[0.06536, 0.06536], hit=[0.65364, 0.65364], ndcg=[0.38009, 0.38009]
INFO:root:Epoch 489 [104.6s + 30.0s]: train==[386.53488=386.50540 + 0.02951], recall=[0.65215, 0.65215], precision=[0.06522, 0.06522], hit=[0.65215, 0.65215], ndcg=[0.37882, 0.37882]
INFO:root:Epoch 499 [103.3s + 29.2s]: train==[385.50406=385.47409 + 0.02991], recall=[0.65546, 0.65546], precision=[0.06555, 0.06555], hit=[0.65546, 0.65546], ndcg=[0.38222, 0.38222]
INFO:root:Epoch 509 [100.5s + 32.3s]: train==[383.95987=383.92953 + 0.03032], recall=[0.65679, 0.65679], precision=[0.06568, 0.06568], hit=[0.65679, 0.65679], ndcg=[0.38296, 0.38296]
INFO:root:Epoch 519 [100.1s + 30.1s]: train==[384.85831=384.82758 + 0.03070], recall=[0.65712, 0.65712], precision=[0.06571, 0.06571], hit=[0.65712, 0.65712], ndcg=[0.38163, 0.38163]
INFO:root:Epoch 529 [104.6s + 30.6s]: train==[383.07547=383.04456 + 0.03114], recall=[0.65546, 0.65546], precision=[0.06555, 0.06555], hit=[0.65546, 0.65546], ndcg=[0.38316, 0.38316]
INFO:root:Epoch 539 [100.9s + 29.0s]: train==[383.48260=383.45096 + 0.03154], recall=[0.65695, 0.65695], precision=[0.06570, 0.06570], hit=[0.65695, 0.65695], ndcg=[0.38313, 0.38313]
INFO:root:Epoch 549 [103.5s + 29.9s]: train==[383.63065=383.59872 + 0.03198], recall=[0.65877, 0.65877], precision=[0.06588, 0.06588], hit=[0.65877, 0.65877], ndcg=[0.38368, 0.38368]
INFO:root:Epoch 559 [101.3s + 31.0s]: train==[381.43750=381.40485 + 0.03243], recall=[0.65745, 0.65745], precision=[0.06575, 0.06575], hit=[0.65745, 0.65745], ndcg=[0.38267, 0.38267]
INFO:root:Epoch 569 [102.8s + 30.2s]: train==[379.66098=379.62805 + 0.03286], recall=[0.65745, 0.65745], precision=[0.06575, 0.06575], hit=[0.65745, 0.65745], ndcg=[0.38153, 0.38153]
INFO:root:Epoch 579 [104.2s + 30.4s]: train==[377.64554=377.61243 + 0.03330], recall=[0.65861, 0.65861], precision=[0.06586, 0.06586], hit=[0.65861, 0.65861], ndcg=[0.38297, 0.38297]
INFO:root:Epoch 589 [103.3s + 33.4s]: train==[377.89603=377.86212 + 0.03371], recall=[0.65629, 0.65629], precision=[0.06563, 0.06563], hit=[0.65629, 0.65629], ndcg=[0.38291, 0.38291]
INFO:root:Epoch 599 [103.3s + 30.1s]: train==[381.60861=381.57474 + 0.03420], recall=[0.66060, 0.66060], precision=[0.06606, 0.06606], hit=[0.66060, 0.66060], ndcg=[0.38521, 0.38521]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 609 [103.3s + 30.5s]: train==[378.02383=377.98889 + 0.03459], recall=[0.65613, 0.65613], precision=[0.06561, 0.06561], hit=[0.65613, 0.65613], ndcg=[0.38184, 0.38184]
INFO:root:Epoch 619 [104.1s + 30.7s]: train==[377.32614=377.29114 + 0.03505], recall=[0.65662, 0.65662], precision=[0.06566, 0.06566], hit=[0.65662, 0.65662], ndcg=[0.38198, 0.38198]
INFO:root:Epoch 629 [102.6s + 31.1s]: train==[379.34476=379.30927 + 0.03552], recall=[0.65944, 0.65944], precision=[0.06594, 0.06594], hit=[0.65944, 0.65944], ndcg=[0.38426, 0.38426]
INFO:root:Epoch 639 [98.0s + 29.8s]: train==[376.92801=376.89169 + 0.03592], recall=[0.65778, 0.65778], precision=[0.06578, 0.06578], hit=[0.65778, 0.65778], ndcg=[0.37920, 0.37920]
INFO:root:Epoch 649 [100.4s + 31.6s]: train==[377.41888=377.38220 + 0.03645], recall=[0.66275, 0.66275], precision=[0.06627, 0.06627], hit=[0.66275, 0.66275], ndcg=[0.38322, 0.38322]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 659 [97.5s + 30.0s]: train==[378.62213=378.58539 + 0.03687], recall=[0.65828, 0.65828], precision=[0.06583, 0.06583], hit=[0.65828, 0.65828], ndcg=[0.38317, 0.38317]
INFO:root:Epoch 669 [104.6s + 30.5s]: train==[374.74448=374.70721 + 0.03731], recall=[0.65861, 0.65861], precision=[0.06586, 0.06586], hit=[0.65861, 0.65861], ndcg=[0.38318, 0.38318]
INFO:root:Epoch 679 [104.3s + 32.1s]: train==[378.52628=378.48819 + 0.03782], recall=[0.65613, 0.65613], precision=[0.06561, 0.06561], hit=[0.65613, 0.65613], ndcg=[0.38262, 0.38262]
INFO:root:Epoch 689 [101.9s + 32.0s]: train==[374.56845=374.53015 + 0.03830], recall=[0.66093, 0.66093], precision=[0.06609, 0.06609], hit=[0.66093, 0.66093], ndcg=[0.38293, 0.38293]
INFO:root:Epoch 699 [100.7s + 30.3s]: train==[375.11554=375.07666 + 0.03878], recall=[0.65960, 0.65960], precision=[0.06596, 0.06596], hit=[0.65960, 0.65960], ndcg=[0.38123, 0.38123]
INFO:root:Epoch 709 [99.6s + 29.5s]: train==[375.43927=375.39996 + 0.03934], recall=[0.65662, 0.65662], precision=[0.06566, 0.06566], hit=[0.65662, 0.65662], ndcg=[0.37994, 0.37994]
INFO:root:Epoch 719 [99.7s + 32.2s]: train==[374.80475=374.76471 + 0.03977], recall=[0.65497, 0.65497], precision=[0.06550, 0.06550], hit=[0.65497, 0.65497], ndcg=[0.38329, 0.38329]
INFO:root:Epoch 729 [105.7s + 28.3s]: train==[373.46579=373.42563 + 0.04025], recall=[0.65232, 0.65232], precision=[0.06523, 0.06523], hit=[0.65232, 0.65232], ndcg=[0.38207, 0.38207]
INFO:root:Epoch 739 [102.6s + 32.5s]: train==[370.67279=370.63208 + 0.04080], recall=[0.66192, 0.66192], precision=[0.06619, 0.06619], hit=[0.66192, 0.66192], ndcg=[0.38379, 0.38379]
INFO:root:Epoch 749 [103.7s + 31.1s]: train==[374.00864=373.96765 + 0.04125], recall=[0.65530, 0.65530], precision=[0.06553, 0.06553], hit=[0.65530, 0.65530], ndcg=[0.38358, 0.38358]
INFO:root:Epoch 759 [103.9s + 31.1s]: train==[373.30963=373.26779 + 0.04172], recall=[0.65563, 0.65563], precision=[0.06556, 0.06556], hit=[0.65563, 0.65563], ndcg=[0.38015, 0.38015]
INFO:root:Epoch 769 [101.7s + 30.1s]: train==[374.58145=374.53955 + 0.04220], recall=[0.65613, 0.65613], precision=[0.06561, 0.06561], hit=[0.65613, 0.65613], ndcg=[0.38243, 0.38243]
INFO:root:Epoch 779 [99.1s + 32.3s]: train==[372.57983=372.53729 + 0.04272], recall=[0.65894, 0.65894], precision=[0.06589, 0.06589], hit=[0.65894, 0.65894], ndcg=[0.38200, 0.38200]
INFO:root:Epoch 789 [102.3s + 29.8s]: train==[373.94095=373.89783 + 0.04325], recall=[0.65513, 0.65513], precision=[0.06551, 0.06551], hit=[0.65513, 0.65513], ndcg=[0.38107, 0.38107]
INFO:root:Epoch 799 [101.6s + 31.6s]: train==[376.40094=376.35675 + 0.04382], recall=[0.65679, 0.65679], precision=[0.06568, 0.06568], hit=[0.65679, 0.65679], ndcg=[0.38030, 0.38030]
INFO:root:Epoch 809 [102.3s + 30.3s]: train==[373.25937=373.21542 + 0.04426], recall=[0.65861, 0.65861], precision=[0.06586, 0.06586], hit=[0.65861, 0.65861], ndcg=[0.38056, 0.38056]
INFO:root:Epoch 819 [102.1s + 29.5s]: train==[375.43112=375.38644 + 0.04475], recall=[0.65646, 0.65646], precision=[0.06565, 0.06565], hit=[0.65646, 0.65646], ndcg=[0.38082, 0.38082]
INFO:root:Epoch 829 [103.4s + 31.6s]: train==[375.46530=375.41992 + 0.04523], recall=[0.65281, 0.65281], precision=[0.06528, 0.06528], hit=[0.65281, 0.65281], ndcg=[0.38057, 0.38057]
INFO:root:Epoch 839 [103.6s + 32.4s]: train==[374.93640=374.89059 + 0.04580], recall=[0.65629, 0.65629], precision=[0.06563, 0.06563], hit=[0.65629, 0.65629], ndcg=[0.37962, 0.37962]
INFO:root:Epoch 849 [100.0s + 29.5s]: train==[371.98868=371.94257 + 0.04627], recall=[0.65944, 0.65944], precision=[0.06594, 0.06594], hit=[0.65944, 0.65944], ndcg=[0.38211, 0.38211]
INFO:root:Epoch 859 [102.5s + 30.6s]: train==[372.93100=372.88373 + 0.04677], recall=[0.65513, 0.65513], precision=[0.06551, 0.06551], hit=[0.65513, 0.65513], ndcg=[0.38088, 0.38088]
INFO:root:Epoch 869 [101.7s + 32.2s]: train==[371.88464=371.83734 + 0.04723], recall=[0.65894, 0.65894], precision=[0.06589, 0.06589], hit=[0.65894, 0.65894], ndcg=[0.38201, 0.38201]
INFO:root:Epoch 879 [100.8s + 31.2s]: train==[371.20270=371.15436 + 0.04776], recall=[0.65877, 0.65877], precision=[0.06588, 0.06588], hit=[0.65877, 0.65877], ndcg=[0.38398, 0.38398]
INFO:root:Epoch 889 [100.7s + 32.0s]: train==[372.88876=372.84064 + 0.04837], recall=[0.65546, 0.65546], precision=[0.06555, 0.06555], hit=[0.65546, 0.65546], ndcg=[0.37945, 0.37945]
INFO:root:Epoch 899 [104.5s + 31.7s]: train==[371.91428=371.86517 + 0.04887], recall=[0.65911, 0.65911], precision=[0.06591, 0.06591], hit=[0.65911, 0.65911], ndcg=[0.38281, 0.38281]
INFO:root:Epoch 909 [99.8s + 32.7s]: train==[369.83536=369.78564 + 0.04936], recall=[0.65530, 0.65530], precision=[0.06553, 0.06553], hit=[0.65530, 0.65530], ndcg=[0.38167, 0.38167]
INFO:root:Epoch 919 [103.7s + 31.5s]: train==[372.64944=372.59970 + 0.04984], recall=[0.65745, 0.65745], precision=[0.06575, 0.06575], hit=[0.65745, 0.65745], ndcg=[0.38343, 0.38343]
INFO:root:Epoch 929 [101.8s + 30.5s]: train==[372.06290=372.01288 + 0.05041], recall=[0.65728, 0.65728], precision=[0.06573, 0.06573], hit=[0.65728, 0.65728], ndcg=[0.38295, 0.38295]
INFO:root:Epoch 939 [101.4s + 30.4s]: train==[372.11020=372.05893 + 0.05090], recall=[0.65464, 0.65464], precision=[0.06546, 0.06546], hit=[0.65464, 0.65464], ndcg=[0.38177, 0.38177]
INFO:root:Epoch 949 [98.6s + 30.5s]: train==[371.06717=371.01550 + 0.05144], recall=[0.65629, 0.65629], precision=[0.06563, 0.06563], hit=[0.65629, 0.65629], ndcg=[0.38240, 0.38240]
INFO:root:Best Iter=[64]@[98978.4]	recall=[0.66275], precision=[0.06627], hit=[0.66275], ndcg=[0.38322]
INFO:root:Namespace(Ks='[10]', batch_size=64, data_path='./data/recommendation/', dataset='ml-1m', embed_size=128, epoch=2000, gpu=2, item_density_threshold=0.01, item_threshold=30, layer_size=[128], lmbda=1, local_batch_size=512, local_epoch=20, log_name='run4_1', log_path='/home/qhuaf/graph_pri/logs/', lr=0.1, mess_dropout=[0.1, 0.1, 0.1], model_name='two_side_graph_run4_1.pkl', num_neighbor=10, num_process=4, pretrain_epoch=300, pri_epoch=200, privacy_protect=False, regs=[1e-05], report=0, save_flag=1, test_flag='part', user_batch_size=512, verbose=1, weights_path='model/')
INFO:root:Namespace(Ks='[10]', batch_size=64, data_path='./data/recommendation/', dataset='ml-1m', embed_size=128, epoch=2000, gpu=1, item_density_threshold=0.01, item_threshold=30, layer_size=[128], lmbda=1, local_batch_size=512, local_epoch=10, log_name='run4_1', log_path='/home/qhuaf/graph_pri/logs/', lr=0.0001, mess_dropout=[0.1, 0.1, 0.1], model_name='two_side_graph_run4_1.pkl', num_neighbor=10, num_process=4, pretrain_epoch=300, pri_epoch=200, privacy_protect=False, regs=[1e-05], report=0, save_flag=1, test_flag='part', user_batch_size=512, verbose=1, weights_path='model/')
INFO:root:Namespace(Ks='[10]', batch_size=64, data_path='./data/recommendation/', dataset='ml-1m', embed_size=128, epoch=2000, gpu=1, item_density_threshold=0.01, item_threshold=30, layer_size=[128], lmbda=1, local_batch_size=512, local_epoch=10, log_name='run4_1', log_path='/home/qhuaf/graph_pri/logs/', lr=0.1, mess_dropout=[0.1, 0.1, 0.1], model_name='two_side_graph_run4_1.pkl', num_neighbor=10, num_process=4, pretrain_epoch=300, pri_epoch=200, privacy_protect=False, regs=[1e-05], report=0, save_flag=1, test_flag='part', user_batch_size=512, verbose=1, weights_path='model/')
INFO:root:Namespace(Ks='[10]', batch_size=64, data_path='./data/recommendation/', dataset='ml-1m', embed_size=128, epoch=2000, gpu=1, item_density_threshold=0.01, item_threshold=30, layer_size=[128], lmbda=1, local_batch_size=512, local_epoch=1, log_name='run4_1', log_path='/home/qhuaf/graph_pri/logs/', lr=0.1, mess_dropout=[0.1, 0.1, 0.1], model_name='two_side_graph_run4_1.pkl', num_neighbor=10, num_process=4, pretrain_epoch=300, pri_epoch=200, privacy_protect=False, regs=[1e-05], report=0, save_flag=1, test_flag='part', user_batch_size=512, verbose=1, weights_path='model/')
INFO:root:Namespace(Ks='[10]', batch_size=64, data_path='./data/recommendation/', dataset='ml-1m', embed_size=128, epoch=2000, gpu=0, item_density_threshold=0.01, item_threshold=30, layer_size=[128], lmbda=1, local_batch_size=512, local_epoch=1, log_name='run4_1', log_path='/home/qhuaf/graph_pri/logs/', lr=0.1, mess_dropout=[0.1, 0.1, 0.1], model_name='two_side_graph_run4_1.pkl', num_neighbor=10, num_process=4, pretrain_epoch=300, pri_epoch=200, privacy_protect=False, regs=[1e-05], report=0, save_flag=1, test_flag='part', user_batch_size=512, verbose=1, weights_path='model/')
INFO:root:Namespace(Ks='[10]', batch_size=64, data_path='./data/recommendation/', dataset='ml-1m', embed_size=128, epoch=2000, gpu=3, item_density_threshold=0.01, item_threshold=30, layer_size=[128], lmbda=1, local_batch_size=512, local_epoch=1, log_name='run4_1', log_path='/home/qhuaf/graph_pri/logs/', lr=0.01, mess_dropout=[0.1, 0.1, 0.1], model_name='two_side_graph_run4_1.pkl', num_neighbor=10, num_process=4, pretrain_epoch=300, pri_epoch=200, privacy_protect=False, regs=[1e-05], report=0, save_flag=1, test_flag='part', user_batch_size=512, verbose=1, weights_path='model/')
INFO:root:Epoch 9 [70.5s + 44.9s]: train==[572.90906=572.89343 + 0.01600], recall=[0.57682, 0.57682], precision=[0.05768, 0.05768], hit=[0.57682, 0.57682], ndcg=[0.34651, 0.34651]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 9 [125.3s + 36.9s]: train==[536.81390=536.79700 + 0.01688], recall=[0.64967, 0.64967], precision=[0.06497, 0.06497], hit=[0.64967, 0.64967], ndcg=[0.37650, 0.37650]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 9 [37.6s + 32.9s]: train==[693.04358=693.02673 + 0.01642], recall=[0.19868, 0.19868], precision=[0.01987, 0.01987], hit=[0.19868, 0.19868], ndcg=[0.09144, 0.09144]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 9 [33.8s + 34.7s]: train==[693.31152=693.29547 + 0.01581], recall=[0.18957, 0.18957], precision=[0.01896, 0.01896], hit=[0.18957, 0.18957], ndcg=[0.08347, 0.08347]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 19 [42.2s + 33.8s]: train==[693.02094=693.00446 + 0.01636], recall=[0.20679, 0.20679], precision=[0.02068, 0.02068], hit=[0.20679, 0.20679], ndcg=[0.09429, 0.09429]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 19 [38.1s + 35.3s]: train==[693.25647=693.24109 + 0.01579], recall=[0.19123, 0.19123], precision=[0.01912, 0.01912], hit=[0.19123, 0.19123], ndcg=[0.08393, 0.08393]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 19 [72.4s + 44.7s]: train==[466.09476=466.07907 + 0.01612], recall=[0.66159, 0.66159], precision=[0.06616, 0.06616], hit=[0.66159, 0.66159], ndcg=[0.38558, 0.38558]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 29 [38.3s + 33.3s]: train==[692.97858=692.96179 + 0.01633], recall=[0.20844, 0.20844], precision=[0.02084, 0.02084], hit=[0.20844, 0.20844], ndcg=[0.09426, 0.09426]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 29 [36.6s + 34.9s]: train==[693.21497=693.19873 + 0.01577], recall=[0.19089, 0.19089], precision=[0.01909, 0.01909], hit=[0.19089, 0.19089], ndcg=[0.08413, 0.08413]
INFO:root:Epoch 39 [36.3s + 33.7s]: train==[692.89020=692.87305 + 0.01631], recall=[0.21109, 0.21109], precision=[0.02111, 0.02111], hit=[0.21109, 0.21109], ndcg=[0.09633, 0.09633]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 39 [35.8s + 34.2s]: train==[693.19128=693.17542 + 0.01576], recall=[0.18990, 0.18990], precision=[0.01899, 0.01899], hit=[0.18990, 0.18990], ndcg=[0.08445, 0.08445]
INFO:root:Epoch 19 [122.8s + 37.0s]: train==[467.75177=467.73312 + 0.01848], recall=[0.66540, 0.66540], precision=[0.06654, 0.06654], hit=[0.66540, 0.66540], ndcg=[0.38756, 0.38756]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 29 [73.8s + 45.8s]: train==[428.15100=428.13449 + 0.01628], recall=[0.67185, 0.67185], precision=[0.06719, 0.06719], hit=[0.67185, 0.67185], ndcg=[0.39230, 0.39230]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 49 [37.6s + 35.5s]: train==[692.83954=692.82471 + 0.01629], recall=[0.21308, 0.21308], precision=[0.02131, 0.02131], hit=[0.21308, 0.21308], ndcg=[0.09589, 0.09589]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 49 [38.1s + 35.5s]: train==[693.19220=693.17615 + 0.01575], recall=[0.18460, 0.18460], precision=[0.01846, 0.01846], hit=[0.18460, 0.18460], ndcg=[0.08116, 0.08116]
INFO:root:Epoch 59 [38.0s + 34.1s]: train==[692.84943=692.83356 + 0.01628], recall=[0.21374, 0.21374], precision=[0.02137, 0.02137], hit=[0.21374, 0.21374], ndcg=[0.09732, 0.09732]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 59 [37.8s + 35.7s]: train==[693.17694=693.16132 + 0.01575], recall=[0.18940, 0.18940], precision=[0.01894, 0.01894], hit=[0.18940, 0.18940], ndcg=[0.08364, 0.08364]
INFO:root:Epoch 39 [73.5s + 44.6s]: train==[421.11954=421.10284 + 0.01651], recall=[0.67036, 0.67036], precision=[0.06704, 0.06704], hit=[0.67036, 0.67036], ndcg=[0.39086, 0.39086]
INFO:root:Epoch 69 [37.1s + 34.6s]: train==[692.79749=692.78162 + 0.01627], recall=[0.21838, 0.21838], precision=[0.02184, 0.02184], hit=[0.21838, 0.21838], ndcg=[0.09847, 0.09847]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 69 [37.2s + 36.9s]: train==[693.17255=693.15649 + 0.01574], recall=[0.18675, 0.18675], precision=[0.01868, 0.01868], hit=[0.18675, 0.18675], ndcg=[0.08343, 0.08343]
INFO:root:Epoch 29 [133.4s + 36.1s]: train==[450.12469=450.10379 + 0.02088], recall=[0.66242, 0.66242], precision=[0.06624, 0.06624], hit=[0.66242, 0.66242], ndcg=[0.38734, 0.38734]
INFO:root:Epoch 79 [38.0s + 34.9s]: train==[692.74023=692.72296 + 0.01628], recall=[0.22334, 0.22334], precision=[0.02233, 0.02233], hit=[0.22334, 0.22334], ndcg=[0.10200, 0.10200]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 79 [37.8s + 37.2s]: train==[693.15710=693.14081 + 0.01574], recall=[0.18576, 0.18576], precision=[0.01858, 0.01858], hit=[0.18576, 0.18576], ndcg=[0.08227, 0.08227]
INFO:root:Epoch 49 [72.4s + 44.7s]: train==[414.80249=414.78592 + 0.01680], recall=[0.66672, 0.66672], precision=[0.06667, 0.06667], hit=[0.66672, 0.66672], ndcg=[0.38735, 0.38735]
INFO:root:Epoch 89 [37.8s + 36.1s]: train==[692.74164=692.72589 + 0.01628], recall=[0.22632, 0.22632], precision=[0.02263, 0.02263], hit=[0.22632, 0.22632], ndcg=[0.10335, 0.10335]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 89 [39.4s + 36.0s]: train==[693.15637=693.14050 + 0.01574], recall=[0.18775, 0.18775], precision=[0.01877, 0.01877], hit=[0.18775, 0.18775], ndcg=[0.08415, 0.08415]
INFO:root:Epoch 99 [37.7s + 36.2s]: train==[692.68427=692.66846 + 0.01628], recall=[0.22997, 0.22997], precision=[0.02300, 0.02300], hit=[0.22997, 0.22997], ndcg=[0.10589, 0.10589]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 99 [39.8s + 38.2s]: train==[693.15875=693.14325 + 0.01573], recall=[0.19040, 0.19040], precision=[0.01904, 0.01904], hit=[0.19040, 0.19040], ndcg=[0.08496, 0.08496]
INFO:root:Epoch 59 [72.9s + 45.5s]: train==[417.63016=417.61310 + 0.01716], recall=[0.66738, 0.66738], precision=[0.06674, 0.06674], hit=[0.66738, 0.66738], ndcg=[0.39050, 0.39050]
INFO:root:Epoch 109 [38.4s + 35.4s]: train==[692.61987=692.60254 + 0.01629], recall=[0.22897, 0.22897], precision=[0.02290, 0.02290], hit=[0.22897, 0.22897], ndcg=[0.10523, 0.10523]
INFO:root:Epoch 109 [39.8s + 36.7s]: train==[693.16571=693.14978 + 0.01573], recall=[0.18858, 0.18858], precision=[0.01886, 0.01886], hit=[0.18858, 0.18858], ndcg=[0.08325, 0.08325]
INFO:root:Epoch 39 [127.4s + 37.8s]: train==[444.43430=444.41034 + 0.02415], recall=[0.66788, 0.66788], precision=[0.06679, 0.06679], hit=[0.66788, 0.66788], ndcg=[0.38727, 0.38727]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 119 [36.1s + 36.3s]: train==[692.55585=692.53992 + 0.01629], recall=[0.23311, 0.23311], precision=[0.02331, 0.02331], hit=[0.23311, 0.23311], ndcg=[0.10686, 0.10686]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 119 [39.2s + 36.3s]: train==[693.15387=693.13757 + 0.01573], recall=[0.19305, 0.19305], precision=[0.01930, 0.01930], hit=[0.19305, 0.19305], ndcg=[0.08602, 0.08602]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 69 [75.2s + 45.2s]: train==[424.59747=424.57965 + 0.01761], recall=[0.67119, 0.67119], precision=[0.06712, 0.06712], hit=[0.67119, 0.67119], ndcg=[0.39135, 0.39135]
INFO:root:Epoch 129 [40.8s + 39.2s]: train==[692.49615=692.48016 + 0.01631], recall=[0.23742, 0.23742], precision=[0.02374, 0.02374], hit=[0.23742, 0.23742], ndcg=[0.11020, 0.11020]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 129 [43.0s + 37.9s]: train==[693.15735=693.14172 + 0.01573], recall=[0.18974, 0.18974], precision=[0.01897, 0.01897], hit=[0.18974, 0.18974], ndcg=[0.08572, 0.08572]
INFO:root:Epoch 139 [38.1s + 36.0s]: train==[692.49042=692.47491 + 0.01631], recall=[0.24354, 0.24354], precision=[0.02435, 0.02435], hit=[0.24354, 0.24354], ndcg=[0.11356, 0.11356]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 139 [40.6s + 35.7s]: train==[693.13623=693.12054 + 0.01573], recall=[0.18907, 0.18907], precision=[0.01891, 0.01891], hit=[0.18907, 0.18907], ndcg=[0.08559, 0.08559]
INFO:root:Epoch 79 [74.3s + 45.2s]: train==[414.98734=414.96945 + 0.01815], recall=[0.66921, 0.66921], precision=[0.06692, 0.06692], hit=[0.66921, 0.66921], ndcg=[0.38877, 0.38877]
INFO:root:Epoch 49 [124.1s + 35.5s]: train==[444.37613=444.34778 + 0.02814], recall=[0.67103, 0.67103], precision=[0.06710, 0.06710], hit=[0.67103, 0.67103], ndcg=[0.38762, 0.38762]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 149 [36.9s + 36.6s]: train==[692.39044=692.37402 + 0.01631], recall=[0.24520, 0.24520], precision=[0.02452, 0.02452], hit=[0.24520, 0.24520], ndcg=[0.11407, 0.11407]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 149 [38.8s + 36.7s]: train==[693.12860=693.11255 + 0.01572], recall=[0.19338, 0.19338], precision=[0.01934, 0.01934], hit=[0.19338, 0.19338], ndcg=[0.08683, 0.08683]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 159 [41.2s + 37.2s]: train==[692.32056=692.30371 + 0.01633], recall=[0.25298, 0.25298], precision=[0.02530, 0.02530], hit=[0.25298, 0.25298], ndcg=[0.11704, 0.11704]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 159 [38.7s + 34.7s]: train==[693.13696=693.12207 + 0.01572], recall=[0.19487, 0.19487], precision=[0.01949, 0.01949], hit=[0.19487, 0.19487], ndcg=[0.08860, 0.08860]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 89 [76.5s + 45.4s]: train==[398.85880=398.83984 + 0.01876], recall=[0.67334, 0.67334], precision=[0.06733, 0.06733], hit=[0.67334, 0.67334], ndcg=[0.39061, 0.39061]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 169 [37.9s + 35.9s]: train==[692.22314=692.20612 + 0.01634], recall=[0.25497, 0.25497], precision=[0.02550, 0.02550], hit=[0.25497, 0.25497], ndcg=[0.11922, 0.11922]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 169 [39.5s + 35.0s]: train==[693.13843=693.12305 + 0.01572], recall=[0.19123, 0.19123], precision=[0.01912, 0.01912], hit=[0.19123, 0.19123], ndcg=[0.08637, 0.08637]
INFO:root:Epoch 179 [37.5s + 35.9s]: train==[692.23810=692.22198 + 0.01637], recall=[0.26060, 0.26060], precision=[0.02606, 0.02606], hit=[0.26060, 0.26060], ndcg=[0.12150, 0.12150]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 179 [39.3s + 35.4s]: train==[693.15277=693.13739 + 0.01572], recall=[0.19288, 0.19288], precision=[0.01929, 0.01929], hit=[0.19288, 0.19288], ndcg=[0.08772, 0.08772]
INFO:root:Epoch 59 [129.2s + 35.5s]: train==[430.95129=430.91837 + 0.03256], recall=[0.66970, 0.66970], precision=[0.06697, 0.06697], hit=[0.66970, 0.66970], ndcg=[0.39030, 0.39030]
INFO:root:Epoch 99 [76.7s + 47.8s]: train==[387.53375=387.51443 + 0.01945], recall=[0.66209, 0.66209], precision=[0.06621, 0.06621], hit=[0.66209, 0.66209], ndcg=[0.38790, 0.38790]
INFO:root:Epoch 189 [38.7s + 36.4s]: train==[692.13940=692.12244 + 0.01638], recall=[0.27152, 0.27152], precision=[0.02715, 0.02715], hit=[0.27152, 0.27152], ndcg=[0.12646, 0.12646]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 189 [39.1s + 36.9s]: train==[693.12140=693.10553 + 0.01572], recall=[0.19387, 0.19387], precision=[0.01939, 0.01939], hit=[0.19387, 0.19387], ndcg=[0.08871, 0.08871]
INFO:root:Epoch 199 [38.1s + 35.8s]: train==[692.01208=691.99579 + 0.01640], recall=[0.27334, 0.27334], precision=[0.02733, 0.02733], hit=[0.27334, 0.27334], ndcg=[0.12690, 0.12690]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 199 [39.7s + 37.0s]: train==[693.13617=693.11969 + 0.01572], recall=[0.19288, 0.19288], precision=[0.01929, 0.01929], hit=[0.19288, 0.19288], ndcg=[0.08673, 0.08673]
INFO:root:Epoch 109 [73.5s + 46.2s]: train==[383.81036=383.79031 + 0.02021], recall=[0.66639, 0.66639], precision=[0.06664, 0.06664], hit=[0.66639, 0.66639], ndcg=[0.38685, 0.38685]
INFO:root:Epoch 209 [38.6s + 35.9s]: train==[691.95227=691.93579 + 0.01641], recall=[0.27616, 0.27616], precision=[0.02762, 0.02762], hit=[0.27616, 0.27616], ndcg=[0.13058, 0.13058]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 209 [38.3s + 37.8s]: train==[693.11914=693.10303 + 0.01572], recall=[0.19570, 0.19570], precision=[0.01957, 0.01957], hit=[0.19570, 0.19570], ndcg=[0.08819, 0.08819]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 69 [128.6s + 35.8s]: train==[427.22577=427.18845 + 0.03739], recall=[0.67003, 0.67003], precision=[0.06700, 0.06700], hit=[0.67003, 0.67003], ndcg=[0.38593, 0.38593]
INFO:root:Epoch 219 [38.4s + 36.7s]: train==[691.87885=691.86261 + 0.01646], recall=[0.28411, 0.28411], precision=[0.02841, 0.02841], hit=[0.28411, 0.28411], ndcg=[0.13329, 0.13329]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 219 [37.4s + 35.8s]: train==[693.10992=693.09369 + 0.01572], recall=[0.19553, 0.19553], precision=[0.01955, 0.01955], hit=[0.19553, 0.19553], ndcg=[0.08847, 0.08847]
INFO:root:Epoch 119 [72.5s + 44.2s]: train==[389.68289=389.66122 + 0.02108], recall=[0.66722, 0.66722], precision=[0.06672, 0.06672], hit=[0.66722, 0.66722], ndcg=[0.38964, 0.38964]
INFO:root:Epoch 229 [37.8s + 35.6s]: train==[691.75098=691.73456 + 0.01649], recall=[0.28874, 0.28874], precision=[0.02887, 0.02887], hit=[0.28874, 0.28874], ndcg=[0.13613, 0.13613]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 229 [38.5s + 35.4s]: train==[693.11188=693.09625 + 0.01572], recall=[0.19669, 0.19669], precision=[0.01967, 0.01967], hit=[0.19669, 0.19669], ndcg=[0.08870, 0.08870]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 239 [38.0s + 35.3s]: train==[691.63275=691.61609 + 0.01651], recall=[0.29172, 0.29172], precision=[0.02917, 0.02917], hit=[0.29172, 0.29172], ndcg=[0.14055, 0.14055]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 239 [41.1s + 36.2s]: train==[693.11206=693.09601 + 0.01572], recall=[0.19503, 0.19503], precision=[0.01950, 0.01950], hit=[0.19503, 0.19503], ndcg=[0.08902, 0.08902]
INFO:root:Epoch 129 [72.6s + 46.7s]: train==[383.52219=383.50064 + 0.02202], recall=[0.66805, 0.66805], precision=[0.06680, 0.06680], hit=[0.66805, 0.66805], ndcg=[0.38846, 0.38846]
INFO:root:Epoch 249 [37.4s + 35.3s]: train==[691.55420=691.53735 + 0.01655], recall=[0.29719, 0.29719], precision=[0.02972, 0.02972], hit=[0.29719, 0.29719], ndcg=[0.14156, 0.14156]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 249 [38.4s + 35.6s]: train==[693.13483=693.11884 + 0.01572], recall=[0.19520, 0.19520], precision=[0.01952, 0.01952], hit=[0.19520, 0.19520], ndcg=[0.08901, 0.08901]
INFO:root:Epoch 79 [124.0s + 37.0s]: train==[420.10223=420.06000 + 0.04234], recall=[0.67185, 0.67185], precision=[0.06719, 0.06719], hit=[0.67185, 0.67185], ndcg=[0.38993, 0.38993]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 259 [38.6s + 35.3s]: train==[691.39453=691.37775 + 0.01660], recall=[0.29752, 0.29752], precision=[0.02975, 0.02975], hit=[0.29752, 0.29752], ndcg=[0.14326, 0.14326]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 259 [38.8s + 36.6s]: train==[693.10858=693.09222 + 0.01572], recall=[0.19520, 0.19520], precision=[0.01952, 0.01952], hit=[0.19520, 0.19520], ndcg=[0.08775, 0.08775]
INFO:root:Epoch 139 [72.4s + 45.0s]: train==[377.97833=377.95523 + 0.02307], recall=[0.67417, 0.67417], precision=[0.06742, 0.06742], hit=[0.67417, 0.67417], ndcg=[0.39330, 0.39330]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 269 [39.8s + 38.4s]: train==[691.24939=691.23297 + 0.01663], recall=[0.30762, 0.30762], precision=[0.03076, 0.03076], hit=[0.30762, 0.30762], ndcg=[0.14860, 0.14860]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 269 [39.8s + 36.5s]: train==[693.10132=693.08624 + 0.01571], recall=[0.19503, 0.19503], precision=[0.01950, 0.01950], hit=[0.19503, 0.19503], ndcg=[0.08876, 0.08876]
INFO:root:Epoch 279 [37.6s + 35.2s]: train==[691.14307=691.12610 + 0.01666], recall=[0.31457, 0.31457], precision=[0.03146, 0.03146], hit=[0.31457, 0.31457], ndcg=[0.15187, 0.15187]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 279 [37.1s + 36.7s]: train==[693.11963=693.10461 + 0.01571], recall=[0.19321, 0.19321], precision=[0.01932, 0.01932], hit=[0.19321, 0.19321], ndcg=[0.08692, 0.08692]
INFO:root:Epoch 149 [71.4s + 45.5s]: train==[369.52048=369.49661 + 0.02415], recall=[0.66838, 0.66838], precision=[0.06684, 0.06684], hit=[0.66838, 0.66838], ndcg=[0.38951, 0.38951]
INFO:root:Epoch 89 [123.5s + 36.8s]: train==[408.63550=408.58795 + 0.04750], recall=[0.67003, 0.67003], precision=[0.06700, 0.06700], hit=[0.67003, 0.67003], ndcg=[0.38814, 0.38814]
INFO:root:Epoch 289 [39.2s + 35.5s]: train==[690.96759=690.95001 + 0.01672], recall=[0.32450, 0.32450], precision=[0.03245, 0.03245], hit=[0.32450, 0.32450], ndcg=[0.15953, 0.15953]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 289 [37.9s + 35.9s]: train==[693.11102=693.09552 + 0.01571], recall=[0.19570, 0.19570], precision=[0.01957, 0.01957], hit=[0.19570, 0.19570], ndcg=[0.08942, 0.08942]
INFO:root:Epoch 299 [42.9s + 38.4s]: train==[690.79047=690.77423 + 0.01679], recall=[0.32649, 0.32649], precision=[0.03265, 0.03265], hit=[0.32649, 0.32649], ndcg=[0.15839, 0.15839]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 299 [37.0s + 35.4s]: train==[693.10278=693.08734 + 0.01571], recall=[0.19719, 0.19719], precision=[0.01972, 0.01972], hit=[0.19719, 0.19719], ndcg=[0.08953, 0.08953]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 159 [71.0s + 44.5s]: train==[369.53711=369.51169 + 0.02527], recall=[0.66507, 0.66507], precision=[0.06651, 0.06651], hit=[0.66507, 0.66507], ndcg=[0.38788, 0.38788]
INFO:root:Epoch 309 [37.8s + 35.3s]: train==[690.63605=690.61902 + 0.01682], recall=[0.33262, 0.33262], precision=[0.03326, 0.03326], hit=[0.33262, 0.33262], ndcg=[0.16346, 0.16346]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 309 [38.9s + 34.9s]: train==[693.11481=693.09894 + 0.01571], recall=[0.19702, 0.19702], precision=[0.01970, 0.01970], hit=[0.19702, 0.19702], ndcg=[0.08821, 0.08821]
INFO:root:Epoch 319 [36.6s + 35.4s]: train==[690.45422=690.43848 + 0.01690], recall=[0.33543, 0.33543], precision=[0.03354, 0.03354], hit=[0.33543, 0.33543], ndcg=[0.16628, 0.16628]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 319 [37.5s + 35.8s]: train==[693.09375=693.07819 + 0.01571], recall=[0.19437, 0.19437], precision=[0.01944, 0.01944], hit=[0.19437, 0.19437], ndcg=[0.08820, 0.08820]
INFO:root:Epoch 99 [121.2s + 36.5s]: train==[402.68564=402.63232 + 0.05268], recall=[0.66755, 0.66755], precision=[0.06675, 0.06675], hit=[0.66755, 0.66755], ndcg=[0.38853, 0.38853]
INFO:root:Epoch 169 [77.0s + 46.3s]: train==[369.79120=369.76465 + 0.02650], recall=[0.67235, 0.67235], precision=[0.06724, 0.06724], hit=[0.67235, 0.67235], ndcg=[0.39193, 0.39193]
INFO:root:Epoch 329 [38.7s + 34.9s]: train==[690.19775=690.18042 + 0.01696], recall=[0.34123, 0.34123], precision=[0.03412, 0.03412], hit=[0.34123, 0.34123], ndcg=[0.17203, 0.17203]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 329 [39.8s + 35.8s]: train==[693.10541=693.08954 + 0.01571], recall=[0.19685, 0.19685], precision=[0.01969, 0.01969], hit=[0.19685, 0.19685], ndcg=[0.08886, 0.08886]
INFO:root:Epoch 339 [36.8s + 34.3s]: train==[689.98828=689.97150 + 0.01705], recall=[0.35298, 0.35298], precision=[0.03530, 0.03530], hit=[0.35298, 0.35298], ndcg=[0.17959, 0.17959]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 339 [37.0s + 36.6s]: train==[693.10559=693.09039 + 0.01571], recall=[0.19752, 0.19752], precision=[0.01975, 0.01975], hit=[0.19752, 0.19752], ndcg=[0.08895, 0.08895]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 179 [72.4s + 43.6s]: train==[366.79004=366.76190 + 0.02772], recall=[0.67152, 0.67152], precision=[0.06715, 0.06715], hit=[0.67152, 0.67152], ndcg=[0.39222, 0.39222]
INFO:root:Epoch 349 [36.6s + 35.1s]: train==[689.68237=689.66608 + 0.01712], recall=[0.35281, 0.35281], precision=[0.03528, 0.03528], hit=[0.35281, 0.35281], ndcg=[0.18298, 0.18298]
INFO:root:Epoch 349 [37.9s + 36.8s]: train==[693.10852=693.09247 + 0.01571], recall=[0.19603, 0.19603], precision=[0.01960, 0.01960], hit=[0.19603, 0.19603], ndcg=[0.08816, 0.08816]
INFO:root:Epoch 109 [137.9s + 36.3s]: train==[389.84830=389.79034 + 0.05796], recall=[0.66738, 0.66738], precision=[0.06674, 0.06674], hit=[0.66738, 0.66738], ndcg=[0.38881, 0.38881]
INFO:root:Epoch 359 [39.1s + 34.9s]: train==[689.38647=689.37012 + 0.01724], recall=[0.35728, 0.35728], precision=[0.03573, 0.03573], hit=[0.35728, 0.35728], ndcg=[0.18594, 0.18594]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 359 [38.1s + 35.7s]: train==[693.11688=693.10114 + 0.01571], recall=[0.19785, 0.19785], precision=[0.01978, 0.01978], hit=[0.19785, 0.19785], ndcg=[0.08917, 0.08917]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 189 [72.9s + 46.0s]: train==[362.76529=362.73608 + 0.02906], recall=[0.66341, 0.66341], precision=[0.06634, 0.06634], hit=[0.66341, 0.66341], ndcg=[0.38595, 0.38595]
INFO:root:Epoch 369 [37.7s + 36.4s]: train==[689.16907=689.15125 + 0.01731], recall=[0.36821, 0.36821], precision=[0.03682, 0.03682], hit=[0.36821, 0.36821], ndcg=[0.19212, 0.19212]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 369 [38.2s + 35.2s]: train==[693.11572=693.09979 + 0.01571], recall=[0.20232, 0.20232], precision=[0.02023, 0.02023], hit=[0.20232, 0.20232], ndcg=[0.09005, 0.09005]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 379 [37.6s + 36.5s]: train==[688.83984=688.82184 + 0.01744], recall=[0.37318, 0.37318], precision=[0.03732, 0.03732], hit=[0.37318, 0.37318], ndcg=[0.19779, 0.19779]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 379 [41.5s + 37.1s]: train==[693.09326=693.07819 + 0.01571], recall=[0.20149, 0.20149], precision=[0.02015, 0.02015], hit=[0.20149, 0.20149], ndcg=[0.09120, 0.09120]
INFO:root:Epoch 199 [71.4s + 45.3s]: train==[358.40720=358.37683 + 0.03046], recall=[0.66606, 0.66606], precision=[0.06661, 0.06661], hit=[0.66606, 0.66606], ndcg=[0.38842, 0.38842]
INFO:root:Epoch 389 [36.8s + 35.5s]: train==[688.52881=688.51074 + 0.01753], recall=[0.38195, 0.38195], precision=[0.03820, 0.03820], hit=[0.38195, 0.38195], ndcg=[0.20358, 0.20358]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 119 [130.0s + 36.8s]: train==[389.22092=389.15814 + 0.06279], recall=[0.66672, 0.66672], precision=[0.06667, 0.06667], hit=[0.66672, 0.66672], ndcg=[0.38757, 0.38757]
INFO:root:Epoch 389 [37.8s + 35.7s]: train==[693.09717=693.08148 + 0.01571], recall=[0.19702, 0.19702], precision=[0.01970, 0.01970], hit=[0.19702, 0.19702], ndcg=[0.08975, 0.08975]
INFO:root:Epoch 399 [37.8s + 35.8s]: train==[688.07745=688.06006 + 0.01767], recall=[0.38725, 0.38725], precision=[0.03873, 0.03873], hit=[0.38725, 0.38725], ndcg=[0.20801, 0.20801]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 399 [39.2s + 35.7s]: train==[693.07928=693.06293 + 0.01571], recall=[0.19934, 0.19934], precision=[0.01993, 0.01993], hit=[0.19934, 0.19934], ndcg=[0.08930, 0.08930]
INFO:root:Epoch 209 [70.2s + 46.0s]: train==[363.30017=363.26825 + 0.03184], recall=[0.67103, 0.67103], precision=[0.06710, 0.06710], hit=[0.67103, 0.67103], ndcg=[0.39349, 0.39349]
INFO:root:Epoch 409 [38.2s + 37.0s]: train==[687.61890=687.60010 + 0.01783], recall=[0.39371, 0.39371], precision=[0.03937, 0.03937], hit=[0.39371, 0.39371], ndcg=[0.21487, 0.21487]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 409 [40.4s + 35.4s]: train==[693.09332=693.07758 + 0.01571], recall=[0.19917, 0.19917], precision=[0.01992, 0.01992], hit=[0.19917, 0.19917], ndcg=[0.08952, 0.08952]
INFO:root:Epoch 419 [37.9s + 35.7s]: train==[687.28278=687.26392 + 0.01796], recall=[0.39901, 0.39901], precision=[0.03990, 0.03990], hit=[0.39901, 0.39901], ndcg=[0.21739, 0.21739]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 419 [37.3s + 35.8s]: train==[693.08051=693.06421 + 0.01571], recall=[0.19818, 0.19818], precision=[0.01982, 0.01982], hit=[0.19818, 0.19818], ndcg=[0.08937, 0.08937]
INFO:root:Epoch 219 [73.2s + 44.7s]: train==[354.88553=354.85223 + 0.03325], recall=[0.66755, 0.66755], precision=[0.06675, 0.06675], hit=[0.66755, 0.66755], ndcg=[0.38890, 0.38890]
INFO:root:Epoch 129 [121.9s + 36.6s]: train==[391.00732=390.93921 + 0.06809], recall=[0.67036, 0.67036], precision=[0.06704, 0.06704], hit=[0.67036, 0.67036], ndcg=[0.39058, 0.39058]
INFO:root:Epoch 429 [39.0s + 36.5s]: train==[686.86542=686.84705 + 0.01814], recall=[0.40298, 0.40298], precision=[0.04030, 0.04030], hit=[0.40298, 0.40298], ndcg=[0.22391, 0.22391]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 429 [38.8s + 37.4s]: train==[693.08191=693.06573 + 0.01571], recall=[0.20298, 0.20298], precision=[0.02030, 0.02030], hit=[0.20298, 0.20298], ndcg=[0.09091, 0.09091]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 439 [45.2s + 38.9s]: train==[686.41974=686.40149 + 0.01830], recall=[0.40778, 0.40778], precision=[0.04078, 0.04078], hit=[0.40778, 0.40778], ndcg=[0.22735, 0.22735]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 439 [38.6s + 35.9s]: train==[693.08881=693.07275 + 0.01571], recall=[0.19884, 0.19884], precision=[0.01988, 0.01988], hit=[0.19884, 0.19884], ndcg=[0.08975, 0.08975]
INFO:root:Epoch 229 [72.0s + 46.5s]: train==[358.56918=358.53433 + 0.03473], recall=[0.66556, 0.66556], precision=[0.06656, 0.06656], hit=[0.66556, 0.66556], ndcg=[0.38978, 0.38978]
INFO:root:Epoch 449 [39.9s + 35.5s]: train==[685.70154=685.68292 + 0.01850], recall=[0.41258, 0.41258], precision=[0.04126, 0.04126], hit=[0.41258, 0.41258], ndcg=[0.23096, 0.23096]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 449 [38.9s + 36.4s]: train==[693.08411=693.06830 + 0.01571], recall=[0.19801, 0.19801], precision=[0.01980, 0.01980], hit=[0.19801, 0.19801], ndcg=[0.08941, 0.08941]
INFO:root:Epoch 459 [39.4s + 36.6s]: train==[685.17236=685.15314 + 0.01870], recall=[0.41970, 0.41970], precision=[0.04197, 0.04197], hit=[0.41970, 0.41970], ndcg=[0.23787, 0.23787]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 139 [125.6s + 35.9s]: train==[384.44537=384.37228 + 0.07301], recall=[0.67632, 0.67632], precision=[0.06763, 0.06763], hit=[0.67632, 0.67632], ndcg=[0.39153, 0.39153]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 459 [39.1s + 36.9s]: train==[693.09357=693.07788 + 0.01571], recall=[0.19801, 0.19801], precision=[0.01980, 0.01980], hit=[0.19801, 0.19801], ndcg=[0.08934, 0.08934]
INFO:root:Epoch 239 [72.2s + 46.7s]: train==[367.23288=367.19675 + 0.03617], recall=[0.66689, 0.66689], precision=[0.06669, 0.06669], hit=[0.66689, 0.66689], ndcg=[0.38926, 0.38926]
INFO:root:Epoch 469 [42.3s + 35.4s]: train==[684.63458=684.61536 + 0.01893], recall=[0.42831, 0.42831], precision=[0.04283, 0.04283], hit=[0.42831, 0.42831], ndcg=[0.24551, 0.24551]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 469 [39.5s + 36.2s]: train==[693.06940=693.05396 + 0.01571], recall=[0.20066, 0.20066], precision=[0.02007, 0.02007], hit=[0.20066, 0.20066], ndcg=[0.08960, 0.08960]
INFO:root:Epoch 479 [37.3s + 35.9s]: train==[683.80927=683.79016 + 0.01917], recall=[0.43079, 0.43079], precision=[0.04308, 0.04308], hit=[0.43079, 0.43079], ndcg=[0.24732, 0.24732]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 479 [39.5s + 36.5s]: train==[693.08038=693.06488 + 0.01571], recall=[0.20116, 0.20116], precision=[0.02012, 0.02012], hit=[0.20116, 0.20116], ndcg=[0.09102, 0.09102]
INFO:root:Epoch 249 [72.8s + 44.2s]: train==[356.27380=356.23608 + 0.03766], recall=[0.67003, 0.67003], precision=[0.06700, 0.06700], hit=[0.67003, 0.67003], ndcg=[0.38951, 0.38951]
INFO:root:Epoch 489 [39.7s + 36.5s]: train==[683.02631=683.00726 + 0.01942], recall=[0.44222, 0.44222], precision=[0.04422, 0.04422], hit=[0.44222, 0.44222], ndcg=[0.25468, 0.25468]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 489 [38.2s + 38.0s]: train==[693.08374=693.06824 + 0.01571], recall=[0.20050, 0.20050], precision=[0.02005, 0.02005], hit=[0.20050, 0.20050], ndcg=[0.09031, 0.09031]
INFO:root:Epoch 149 [138.1s + 36.8s]: train==[376.42526=376.34665 + 0.07828], recall=[0.66358, 0.66358], precision=[0.06636, 0.06636], hit=[0.66358, 0.66358], ndcg=[0.38931, 0.38931]
INFO:root:Epoch 499 [41.2s + 38.5s]: train==[682.37708=682.35657 + 0.01974], recall=[0.44818, 0.44818], precision=[0.04482, 0.04482], hit=[0.44818, 0.44818], ndcg=[0.25993, 0.25993]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 499 [40.7s + 37.3s]: train==[693.08105=693.06519 + 0.01571], recall=[0.20215, 0.20215], precision=[0.02022, 0.02022], hit=[0.20215, 0.20215], ndcg=[0.09191, 0.09191]
INFO:root:Epoch 259 [74.7s + 47.2s]: train==[343.64371=343.60440 + 0.03926], recall=[0.66093, 0.66093], precision=[0.06609, 0.06609], hit=[0.66093, 0.66093], ndcg=[0.38629, 0.38629]
INFO:root:Epoch 509 [41.3s + 37.0s]: train==[681.36938=681.34930 + 0.02006], recall=[0.45331, 0.45331], precision=[0.04533, 0.04533], hit=[0.45331, 0.45331], ndcg=[0.26401, 0.26401]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 509 [39.9s + 37.3s]: train==[693.06360=693.04816 + 0.01571], recall=[0.20066, 0.20066], precision=[0.02007, 0.02007], hit=[0.20066, 0.20066], ndcg=[0.08958, 0.08958]
INFO:root:Epoch 519 [41.6s + 38.5s]: train==[680.76434=680.74365 + 0.02036], recall=[0.45844, 0.45844], precision=[0.04584, 0.04584], hit=[0.45844, 0.45844], ndcg=[0.26738, 0.26738]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 519 [44.3s + 38.9s]: train==[693.07654=693.06128 + 0.01571], recall=[0.20132, 0.20132], precision=[0.02013, 0.02013], hit=[0.20132, 0.20132], ndcg=[0.09233, 0.09233]
INFO:root:Epoch 269 [73.9s + 44.1s]: train==[357.06799=357.02713 + 0.04067], recall=[0.66987, 0.66987], precision=[0.06699, 0.06699], hit=[0.66987, 0.66987], ndcg=[0.38921, 0.38921]
INFO:root:Epoch 529 [37.1s + 35.6s]: train==[679.45197=679.43146 + 0.02072], recall=[0.46606, 0.46606], precision=[0.04661, 0.04661], hit=[0.46606, 0.46606], ndcg=[0.27360, 0.27360]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 159 [127.1s + 35.3s]: train==[369.91394=369.83063 + 0.08316], recall=[0.67202, 0.67202], precision=[0.06720, 0.06720], hit=[0.67202, 0.67202], ndcg=[0.39374, 0.39374]
INFO:root:Epoch 529 [39.4s + 37.8s]: train==[693.09418=693.07874 + 0.01571], recall=[0.20430, 0.20430], precision=[0.02043, 0.02043], hit=[0.20430, 0.20430], ndcg=[0.09187, 0.09187]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 539 [36.2s + 35.5s]: train==[678.42517=678.40375 + 0.02112], recall=[0.47103, 0.47103], precision=[0.04710, 0.04710], hit=[0.47103, 0.47103], ndcg=[0.27774, 0.27774]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 539 [39.5s + 35.6s]: train==[693.06799=693.05267 + 0.01571], recall=[0.20132, 0.20132], precision=[0.02013, 0.02013], hit=[0.20132, 0.20132], ndcg=[0.08981, 0.08981]
INFO:root:Epoch 279 [73.2s + 44.3s]: train==[348.97885=348.93713 + 0.04213], recall=[0.66374, 0.66374], precision=[0.06637, 0.06637], hit=[0.66374, 0.66374], ndcg=[0.39013, 0.39013]
INFO:root:Epoch 549 [38.1s + 36.0s]: train==[677.17065=677.14972 + 0.02154], recall=[0.47748, 0.47748], precision=[0.04775, 0.04775], hit=[0.47748, 0.47748], ndcg=[0.28424, 0.28424]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 549 [40.1s + 36.4s]: train==[693.07477=693.05817 + 0.01571], recall=[0.20646, 0.20646], precision=[0.02065, 0.02065], hit=[0.20646, 0.20646], ndcg=[0.09194, 0.09194]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 559 [37.5s + 36.6s]: train==[675.93805=675.91528 + 0.02200], recall=[0.48825, 0.48825], precision=[0.04882, 0.04882], hit=[0.48825, 0.48825], ndcg=[0.28840, 0.28840]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 559 [39.6s + 35.6s]: train==[693.07117=693.05536 + 0.01571], recall=[0.20315, 0.20315], precision=[0.02031, 0.02031], hit=[0.20315, 0.20315], ndcg=[0.09132, 0.09132]
INFO:root:Epoch 289 [72.8s + 44.1s]: train==[347.65643=347.61215 + 0.04376], recall=[0.67086, 0.67086], precision=[0.06709, 0.06709], hit=[0.67086, 0.67086], ndcg=[0.39094, 0.39094]
INFO:root:Epoch 169 [124.9s + 36.4s]: train==[372.45352=372.36572 + 0.08806], recall=[0.67235, 0.67235], precision=[0.06724, 0.06724], hit=[0.67235, 0.67235], ndcg=[0.39272, 0.39272]
INFO:root:Epoch 569 [39.4s + 35.0s]: train==[674.84845=674.82629 + 0.02249], recall=[0.49238, 0.49238], precision=[0.04924, 0.04924], hit=[0.49238, 0.49238], ndcg=[0.28993, 0.28993]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 569 [38.2s + 36.7s]: train==[693.06952=693.05426 + 0.01571], recall=[0.19801, 0.19801], precision=[0.01980, 0.01980], hit=[0.19801, 0.19801], ndcg=[0.09074, 0.09074]
INFO:root:Epoch 579 [41.9s + 39.0s]: train==[673.20111=673.17841 + 0.02303], recall=[0.49536, 0.49536], precision=[0.04954, 0.04954], hit=[0.49536, 0.49536], ndcg=[0.29514, 0.29514]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 579 [38.3s + 36.5s]: train==[693.07861=693.06348 + 0.01571], recall=[0.20447, 0.20447], precision=[0.02045, 0.02045], hit=[0.20447, 0.20447], ndcg=[0.09219, 0.09219]
INFO:root:Epoch 299 [73.7s + 45.9s]: train==[346.09070=346.04492 + 0.04522], recall=[0.66838, 0.66838], precision=[0.06684, 0.06684], hit=[0.66838, 0.66838], ndcg=[0.38994, 0.38994]
INFO:root:Epoch 589 [37.5s + 35.9s]: train==[671.82062=671.79736 + 0.02358], recall=[0.50298, 0.50298], precision=[0.05030, 0.05030], hit=[0.50298, 0.50298], ndcg=[0.30304, 0.30304]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 589 [38.0s + 35.8s]: train==[693.07617=693.06061 + 0.01571], recall=[0.20414, 0.20414], precision=[0.02041, 0.02041], hit=[0.20414, 0.20414], ndcg=[0.09205, 0.09205]
INFO:root:Epoch 599 [38.0s + 35.0s]: train==[670.32550=670.30066 + 0.02417], recall=[0.51689, 0.51689], precision=[0.05169, 0.05169], hit=[0.51689, 0.51689], ndcg=[0.30661, 0.30661]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 179 [123.5s + 36.0s]: train==[364.33417=364.24100 + 0.09315], recall=[0.67699, 0.67699], precision=[0.06770, 0.06770], hit=[0.67699, 0.67699], ndcg=[0.39219, 0.39219]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 599 [39.2s + 35.5s]: train==[693.08258=693.06641 + 0.01571], recall=[0.20596, 0.20596], precision=[0.02060, 0.02060], hit=[0.20596, 0.20596], ndcg=[0.09300, 0.09300]
INFO:root:Epoch 309 [74.5s + 48.4s]: train==[345.67432=345.62787 + 0.04683], recall=[0.66805, 0.66805], precision=[0.06680, 0.06680], hit=[0.66805, 0.66805], ndcg=[0.38758, 0.38758]
INFO:root:Epoch 609 [42.2s + 35.6s]: train==[668.10736=668.08307 + 0.02488], recall=[0.51689, 0.51689], precision=[0.05169, 0.05169], hit=[0.51689, 0.51689], ndcg=[0.31026, 0.31026]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 609 [38.7s + 35.8s]: train==[693.08801=693.07281 + 0.01571], recall=[0.20613, 0.20613], precision=[0.02061, 0.02061], hit=[0.20613, 0.20613], ndcg=[0.09236, 0.09236]
INFO:root:Epoch 619 [37.5s + 35.9s]: train==[666.25739=666.23181 + 0.02556], recall=[0.52599, 0.52599], precision=[0.05260, 0.05260], hit=[0.52599, 0.52599], ndcg=[0.31178, 0.31178]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 619 [37.3s + 36.4s]: train==[693.06482=693.04932 + 0.01571], recall=[0.20646, 0.20646], precision=[0.02065, 0.02065], hit=[0.20646, 0.20646], ndcg=[0.09265, 0.09265]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 319 [72.4s + 45.0s]: train==[348.94919=348.90076 + 0.04835], recall=[0.66954, 0.66954], precision=[0.06695, 0.06695], hit=[0.66954, 0.66954], ndcg=[0.38935, 0.38935]
INFO:root:Epoch 629 [39.2s + 35.5s]: train==[664.38367=664.35583 + 0.02630], recall=[0.52815, 0.52815], precision=[0.05281, 0.05281], hit=[0.52815, 0.52815], ndcg=[0.31452, 0.31452]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 629 [40.2s + 38.9s]: train==[693.07684=693.06189 + 0.01571], recall=[0.20331, 0.20331], precision=[0.02033, 0.02033], hit=[0.20331, 0.20331], ndcg=[0.09088, 0.09088]
INFO:root:Epoch 189 [131.1s + 36.3s]: train==[364.70746=364.60931 + 0.09826], recall=[0.67467, 0.67467], precision=[0.06747, 0.06747], hit=[0.67467, 0.67467], ndcg=[0.39261, 0.39261]
INFO:root:Epoch 639 [39.1s + 36.3s]: train==[662.65576=662.62891 + 0.02710], recall=[0.53791, 0.53791], precision=[0.05379, 0.05379], hit=[0.53791, 0.53791], ndcg=[0.31904, 0.31904]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 639 [39.9s + 36.2s]: train==[693.07672=693.06073 + 0.01571], recall=[0.20745, 0.20745], precision=[0.02075, 0.02075], hit=[0.20745, 0.20745], ndcg=[0.09205, 0.09205]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 329 [71.0s + 46.3s]: train==[342.68069=342.63083 + 0.04984], recall=[0.66672, 0.66672], precision=[0.06667, 0.06667], hit=[0.66672, 0.66672], ndcg=[0.38706, 0.38706]
INFO:root:Epoch 649 [37.8s + 35.8s]: train==[660.49341=660.46613 + 0.02800], recall=[0.54040, 0.54040], precision=[0.05404, 0.05404], hit=[0.54040, 0.54040], ndcg=[0.32530, 0.32530]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 649 [39.6s + 36.3s]: train==[693.07605=693.05994 + 0.01571], recall=[0.20364, 0.20364], precision=[0.02036, 0.02036], hit=[0.20364, 0.20364], ndcg=[0.09119, 0.09119]
INFO:root:Epoch 659 [36.6s + 36.1s]: train==[657.63525=657.60632 + 0.02889], recall=[0.54503, 0.54503], precision=[0.05450, 0.05450], hit=[0.54503, 0.54503], ndcg=[0.32722, 0.32722]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 659 [40.8s + 40.1s]: train==[693.06537=693.04944 + 0.01571], recall=[0.20430, 0.20430], precision=[0.02043, 0.02043], hit=[0.20430, 0.20430], ndcg=[0.09174, 0.09174]
INFO:root:Epoch 339 [72.4s + 45.3s]: train==[338.44794=338.39648 + 0.05130], recall=[0.66540, 0.66540], precision=[0.06654, 0.06654], hit=[0.66540, 0.66540], ndcg=[0.38903, 0.38903]
INFO:root:Epoch 669 [39.1s + 35.1s]: train==[655.38263=655.35211 + 0.02988], recall=[0.55149, 0.55149], precision=[0.05515, 0.05515], hit=[0.55149, 0.55149], ndcg=[0.32925, 0.32925]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 199 [123.0s + 37.0s]: train==[360.65329=360.54990 + 0.10322], recall=[0.67732, 0.67732], precision=[0.06773, 0.06773], hit=[0.67732, 0.67732], ndcg=[0.39167, 0.39167]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 669 [39.4s + 35.6s]: train==[693.06848=693.05139 + 0.01571], recall=[0.20530, 0.20530], precision=[0.02053, 0.02053], hit=[0.20530, 0.20530], ndcg=[0.09205, 0.09205]
INFO:root:Epoch 679 [38.9s + 37.0s]: train==[652.24109=652.21075 + 0.03094], recall=[0.55546, 0.55546], precision=[0.05555, 0.05555], hit=[0.55546, 0.55546], ndcg=[0.33427, 0.33427]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 679 [38.7s + 36.4s]: train==[693.06323=693.04797 + 0.01571], recall=[0.20613, 0.20613], precision=[0.02061, 0.02061], hit=[0.20613, 0.20613], ndcg=[0.09222, 0.09222]
INFO:root:Epoch 349 [70.0s + 46.2s]: train==[340.14822=340.09613 + 0.05278], recall=[0.66970, 0.66970], precision=[0.06697, 0.06697], hit=[0.66970, 0.66970], ndcg=[0.38933, 0.38933]
INFO:root:Epoch 689 [38.1s + 37.1s]: train==[649.67096=649.63928 + 0.03204], recall=[0.55944, 0.55944], precision=[0.05594, 0.05594], hit=[0.55944, 0.55944], ndcg=[0.33407, 0.33407]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 689 [38.7s + 36.4s]: train==[693.04504=693.02893 + 0.01571], recall=[0.20414, 0.20414], precision=[0.02041, 0.02041], hit=[0.20414, 0.20414], ndcg=[0.09228, 0.09228]
INFO:root:Epoch 699 [39.2s + 36.3s]: train==[647.39282=647.35974 + 0.03320], recall=[0.56341, 0.56341], precision=[0.05634, 0.05634], hit=[0.56341, 0.56341], ndcg=[0.33672, 0.33672]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 699 [37.3s + 36.4s]: train==[693.04980=693.03369 + 0.01571], recall=[0.20348, 0.20348], precision=[0.02035, 0.02035], hit=[0.20348, 0.20348], ndcg=[0.09206, 0.09206]
INFO:root:Epoch 359 [71.8s + 45.2s]: train==[338.12146=338.06650 + 0.05440], recall=[0.66325, 0.66325], precision=[0.06632, 0.06632], hit=[0.66325, 0.66325], ndcg=[0.38936, 0.38936]
INFO:root:Epoch 209 [124.7s + 37.2s]: train==[356.72095=356.61288 + 0.10847], recall=[0.67699, 0.67699], precision=[0.06770, 0.06770], hit=[0.67699, 0.67699], ndcg=[0.39120, 0.39120]
INFO:root:Epoch 709 [39.8s + 36.1s]: train==[644.61627=644.58234 + 0.03442], recall=[0.56507, 0.56507], precision=[0.05651, 0.05651], hit=[0.56507, 0.56507], ndcg=[0.33997, 0.33997]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 709 [38.9s + 36.9s]: train==[693.07593=693.06091 + 0.01571], recall=[0.20844, 0.20844], precision=[0.02084, 0.02084], hit=[0.20844, 0.20844], ndcg=[0.09368, 0.09368]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 719 [42.4s + 38.9s]: train==[640.68091=640.64514 + 0.03567], recall=[0.57119, 0.57119], precision=[0.05712, 0.05712], hit=[0.57119, 0.57119], ndcg=[0.34139, 0.34139]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 719 [37.7s + 35.3s]: train==[693.04553=693.02972 + 0.01571], recall=[0.20911, 0.20911], precision=[0.02091, 0.02091], hit=[0.20911, 0.20911], ndcg=[0.09369, 0.09369]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 369 [71.6s + 45.7s]: train==[334.70145=334.64554 + 0.05585], recall=[0.67136, 0.67136], precision=[0.06714, 0.06714], hit=[0.67136, 0.67136], ndcg=[0.39214, 0.39214]
INFO:root:Epoch 729 [38.4s + 36.5s]: train==[637.45465=637.41882 + 0.03705], recall=[0.57632, 0.57632], precision=[0.05763, 0.05763], hit=[0.57632, 0.57632], ndcg=[0.34285, 0.34285]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 729 [38.7s + 36.7s]: train==[693.05579=693.03992 + 0.01571], recall=[0.20728, 0.20728], precision=[0.02073, 0.02073], hit=[0.20728, 0.20728], ndcg=[0.09226, 0.09226]
INFO:root:Epoch 739 [38.4s + 36.4s]: train==[634.07623=634.03711 + 0.03853], recall=[0.58295, 0.58295], precision=[0.05829, 0.05829], hit=[0.58295, 0.58295], ndcg=[0.34356, 0.34356]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 219 [122.8s + 37.3s]: train==[352.61801=352.50455 + 0.11307], recall=[0.67980, 0.67980], precision=[0.06798, 0.06798], hit=[0.67980, 0.67980], ndcg=[0.39418, 0.39418]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 739 [38.4s + 36.8s]: train==[693.05048=693.03558 + 0.01571], recall=[0.20762, 0.20762], precision=[0.02076, 0.02076], hit=[0.20762, 0.20762], ndcg=[0.09302, 0.09302]
INFO:root:Epoch 379 [68.4s + 48.1s]: train==[340.36044=340.30292 + 0.05734], recall=[0.66921, 0.66921], precision=[0.06692, 0.06692], hit=[0.66921, 0.66921], ndcg=[0.39189, 0.39189]
INFO:root:Epoch 749 [45.3s + 36.5s]: train==[629.99512=629.95435 + 0.04004], recall=[0.58642, 0.58642], precision=[0.05864, 0.05864], hit=[0.58642, 0.58642], ndcg=[0.34728, 0.34728]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 749 [37.2s + 36.0s]: train==[693.06702=693.05157 + 0.01571], recall=[0.20894, 0.20894], precision=[0.02089, 0.02089], hit=[0.20894, 0.20894], ndcg=[0.09349, 0.09349]
INFO:root:Epoch 759 [39.7s + 36.8s]: train==[627.22681=627.18420 + 0.04166], recall=[0.58874, 0.58874], precision=[0.05887, 0.05887], hit=[0.58874, 0.58874], ndcg=[0.35119, 0.35119]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 759 [38.6s + 35.7s]: train==[693.04822=693.03278 + 0.01571], recall=[0.20728, 0.20728], precision=[0.02073, 0.02073], hit=[0.20728, 0.20728], ndcg=[0.09352, 0.09352]
INFO:root:Epoch 389 [69.4s + 46.0s]: train==[337.36398=337.30530 + 0.05879], recall=[0.67301, 0.67301], precision=[0.06730, 0.06730], hit=[0.67301, 0.67301], ndcg=[0.38947, 0.38947]
INFO:root:Epoch 769 [39.4s + 38.2s]: train==[623.15466=623.11108 + 0.04328], recall=[0.59536, 0.59536], precision=[0.05954, 0.05954], hit=[0.59536, 0.59536], ndcg=[0.35502, 0.35502]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 769 [41.3s + 39.3s]: train==[693.06366=693.04871 + 0.01571], recall=[0.20215, 0.20215], precision=[0.02022, 0.02022], hit=[0.20215, 0.20215], ndcg=[0.09084, 0.09084]
INFO:root:Epoch 229 [128.0s + 39.5s]: train==[347.30545=347.18744 + 0.11798], recall=[0.68543, 0.68543], precision=[0.06854, 0.06854], hit=[0.68543, 0.68543], ndcg=[0.39500, 0.39500]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 779 [39.6s + 38.3s]: train==[619.09985=619.05566 + 0.04501], recall=[0.60033, 0.60033], precision=[0.06003, 0.06003], hit=[0.60033, 0.60033], ndcg=[0.35394, 0.35394]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 779 [38.2s + 35.6s]: train==[693.03406=693.01923 + 0.01571], recall=[0.21325, 0.21325], precision=[0.02132, 0.02132], hit=[0.21325, 0.21325], ndcg=[0.09581, 0.09581]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 399 [69.9s + 46.1s]: train==[333.98648=333.92642 + 0.06037], recall=[0.67169, 0.67169], precision=[0.06717, 0.06717], hit=[0.67169, 0.67169], ndcg=[0.39279, 0.39279]
INFO:root:Epoch 789 [37.9s + 37.9s]: train==[615.78101=615.73480 + 0.04678], recall=[0.60447, 0.60447], precision=[0.06045, 0.06045], hit=[0.60447, 0.60447], ndcg=[0.35491, 0.35491]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 789 [38.4s + 36.4s]: train==[693.05621=693.03986 + 0.01571], recall=[0.21109, 0.21109], precision=[0.02111, 0.02111], hit=[0.21109, 0.21109], ndcg=[0.09463, 0.09463]
INFO:root:Epoch 799 [38.0s + 37.3s]: train==[611.75446=611.70581 + 0.04872], recall=[0.60728, 0.60728], precision=[0.06073, 0.06073], hit=[0.60728, 0.60728], ndcg=[0.35765, 0.35765]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 799 [42.0s + 37.5s]: train==[693.04846=693.03223 + 0.01571], recall=[0.20629, 0.20629], precision=[0.02063, 0.02063], hit=[0.20629, 0.20629], ndcg=[0.09341, 0.09341]
INFO:root:Epoch 409 [76.2s + 46.1s]: train==[336.44379=336.38171 + 0.06182], recall=[0.66970, 0.66970], precision=[0.06697, 0.06697], hit=[0.66970, 0.66970], ndcg=[0.38839, 0.38839]
INFO:root:Epoch 809 [38.7s + 37.1s]: train==[606.52551=606.47546 + 0.05056], recall=[0.61291, 0.61291], precision=[0.06129, 0.06129], hit=[0.61291, 0.61291], ndcg=[0.36126, 0.36126]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 239 [123.1s + 37.0s]: train==[346.42670=346.30359 + 0.12315], recall=[0.68278, 0.68278], precision=[0.06828, 0.06828], hit=[0.68278, 0.68278], ndcg=[0.39539, 0.39539]
INFO:root:Epoch 809 [39.1s + 35.5s]: train==[693.04919=693.03387 + 0.01571], recall=[0.20646, 0.20646], precision=[0.02065, 0.02065], hit=[0.20646, 0.20646], ndcg=[0.09337, 0.09337]
INFO:root:Epoch 819 [38.8s + 36.3s]: train==[602.88885=602.83704 + 0.05255], recall=[0.61887, 0.61887], precision=[0.06189, 0.06189], hit=[0.61887, 0.61887], ndcg=[0.36238, 0.36238]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 819 [37.8s + 34.4s]: train==[693.03845=693.02277 + 0.01571], recall=[0.20811, 0.20811], precision=[0.02081, 0.02081], hit=[0.20811, 0.20811], ndcg=[0.09378, 0.09378]
INFO:root:Epoch 419 [72.9s + 46.3s]: train==[332.10382=332.04062 + 0.06346], recall=[0.67185, 0.67185], precision=[0.06719, 0.06719], hit=[0.67185, 0.67185], ndcg=[0.39029, 0.39029]
INFO:root:Epoch 829 [38.4s + 38.7s]: train==[598.95667=598.90222 + 0.05455], recall=[0.61838, 0.61838], precision=[0.06184, 0.06184], hit=[0.61838, 0.61838], ndcg=[0.36697, 0.36697]
INFO:root:Epoch 829 [37.9s + 35.7s]: train==[693.03955=693.02423 + 0.01571], recall=[0.20811, 0.20811], precision=[0.02081, 0.02081], hit=[0.20811, 0.20811], ndcg=[0.09288, 0.09288]
INFO:root:Epoch 839 [39.6s + 38.2s]: train==[593.73834=593.68176 + 0.05669], recall=[0.62252, 0.62252], precision=[0.06225, 0.06225], hit=[0.62252, 0.62252], ndcg=[0.36704, 0.36704]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 839 [38.1s + 35.9s]: train==[693.04669=693.03021 + 0.01571], recall=[0.20447, 0.20447], precision=[0.02045, 0.02045], hit=[0.20447, 0.20447], ndcg=[0.09086, 0.09086]
INFO:root:Epoch 429 [71.3s + 45.7s]: train==[331.94788=331.88260 + 0.06504], recall=[0.66937, 0.66937], precision=[0.06694, 0.06694], hit=[0.66937, 0.66937], ndcg=[0.38947, 0.38947]
INFO:root:Epoch 249 [122.6s + 36.5s]: train==[337.76242=337.63437 + 0.12794], recall=[0.68063, 0.68063], precision=[0.06806, 0.06806], hit=[0.68063, 0.68063], ndcg=[0.39290, 0.39290]
INFO:root:Epoch 849 [38.3s + 35.9s]: train==[590.39795=590.33905 + 0.05892], recall=[0.62268, 0.62268], precision=[0.06227, 0.06227], hit=[0.62268, 0.62268], ndcg=[0.36552, 0.36552]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 849 [38.0s + 36.3s]: train==[693.04840=693.03308 + 0.01571], recall=[0.20745, 0.20745], precision=[0.02075, 0.02075], hit=[0.20745, 0.20745], ndcg=[0.09197, 0.09197]
INFO:root:Epoch 859 [43.2s + 37.2s]: train==[584.96887=584.90778 + 0.06106], recall=[0.62964, 0.62964], precision=[0.06296, 0.06296], hit=[0.62964, 0.62964], ndcg=[0.36706, 0.36706]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 859 [38.1s + 35.3s]: train==[693.03516=693.01892 + 0.01571], recall=[0.20944, 0.20944], precision=[0.02094, 0.02094], hit=[0.20944, 0.20944], ndcg=[0.09372, 0.09372]
INFO:root:Epoch 439 [72.4s + 45.4s]: train==[330.16492=330.09836 + 0.06638], recall=[0.66772, 0.66772], precision=[0.06677, 0.06677], hit=[0.66772, 0.66772], ndcg=[0.39141, 0.39141]
INFO:root:Epoch 869 [39.3s + 35.8s]: train==[581.30884=581.24493 + 0.06342], recall=[0.62765, 0.62765], precision=[0.06276, 0.06276], hit=[0.62765, 0.62765], ndcg=[0.36966, 0.36966]
INFO:root:Epoch 869 [39.2s + 36.8s]: train==[693.03900=693.02368 + 0.01571], recall=[0.21474, 0.21474], precision=[0.02147, 0.02147], hit=[0.21474, 0.21474], ndcg=[0.09652, 0.09652]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 879 [38.4s + 36.3s]: train==[576.66846=576.60236 + 0.06549], recall=[0.63477, 0.63477], precision=[0.06348, 0.06348], hit=[0.63477, 0.63477], ndcg=[0.36994, 0.36994]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 259 [122.9s + 36.2s]: train==[334.72461=334.59171 + 0.13287], recall=[0.68626, 0.68626], precision=[0.06863, 0.06863], hit=[0.68626, 0.68626], ndcg=[0.39560, 0.39560]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 879 [38.8s + 35.0s]: train==[693.04871=693.03351 + 0.01571], recall=[0.20712, 0.20712], precision=[0.02071, 0.02071], hit=[0.20712, 0.20712], ndcg=[0.09322, 0.09322]
INFO:root:Epoch 449 [70.7s + 47.6s]: train==[330.18573=330.11823 + 0.06783], recall=[0.67417, 0.67417], precision=[0.06742, 0.06742], hit=[0.67417, 0.67417], ndcg=[0.39256, 0.39256]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 889 [39.7s + 34.7s]: train==[572.10797=572.04016 + 0.06797], recall=[0.63460, 0.63460], precision=[0.06346, 0.06346], hit=[0.63460, 0.63460], ndcg=[0.37230, 0.37230]
INFO:root:Epoch 889 [39.4s + 36.6s]: train==[693.03577=693.02057 + 0.01571], recall=[0.21010, 0.21010], precision=[0.02101, 0.02101], hit=[0.21010, 0.21010], ndcg=[0.09422, 0.09422]
INFO:root:Epoch 899 [37.7s + 34.9s]: train==[567.50372=567.43347 + 0.07033], recall=[0.63427, 0.63427], precision=[0.06343, 0.06343], hit=[0.63427, 0.63427], ndcg=[0.37238, 0.37238]
INFO:root:Epoch 899 [39.4s + 34.8s]: train==[693.03552=693.01984 + 0.01571], recall=[0.20480, 0.20480], precision=[0.02048, 0.02048], hit=[0.20480, 0.20480], ndcg=[0.09187, 0.09187]
INFO:root:Epoch 459 [72.3s + 46.2s]: train==[328.33258=328.26373 + 0.06929], recall=[0.66540, 0.66540], precision=[0.06654, 0.06654], hit=[0.66540, 0.66540], ndcg=[0.38784, 0.38784]
INFO:root:Epoch 909 [38.8s + 36.1s]: train==[565.33984=565.26617 + 0.07268], recall=[0.63791, 0.63791], precision=[0.06379, 0.06379], hit=[0.63791, 0.63791], ndcg=[0.37387, 0.37387]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 909 [42.1s + 36.7s]: train==[693.02881=693.01379 + 0.01571], recall=[0.21275, 0.21275], precision=[0.02127, 0.02127], hit=[0.21275, 0.21275], ndcg=[0.09485, 0.09485]
INFO:root:Epoch 269 [129.7s + 38.4s]: train==[332.31873=332.18121 + 0.13792], recall=[0.68228, 0.68228], precision=[0.06823, 0.06823], hit=[0.68228, 0.68228], ndcg=[0.39520, 0.39520]
INFO:root:Epoch 919 [38.6s + 36.1s]: train==[558.91510=558.84033 + 0.07510], recall=[0.64222, 0.64222], precision=[0.06422, 0.06422], hit=[0.64222, 0.64222], ndcg=[0.37352, 0.37352]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 919 [37.2s + 34.9s]: train==[693.01630=693.00140 + 0.01571], recall=[0.21457, 0.21457], precision=[0.02146, 0.02146], hit=[0.21457, 0.21457], ndcg=[0.09564, 0.09564]
INFO:root:Epoch 469 [70.8s + 45.7s]: train==[328.71234=328.64099 + 0.07076], recall=[0.67881, 0.67881], precision=[0.06788, 0.06788], hit=[0.67881, 0.67881], ndcg=[0.39407, 0.39407]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 929 [37.7s + 36.0s]: train==[552.43042=552.35236 + 0.07765], recall=[0.64139, 0.64139], precision=[0.06414, 0.06414], hit=[0.64139, 0.64139], ndcg=[0.37440, 0.37440]
INFO:root:Epoch 929 [39.0s + 37.1s]: train==[693.02307=693.00757 + 0.01571], recall=[0.21275, 0.21275], precision=[0.02127, 0.02127], hit=[0.21275, 0.21275], ndcg=[0.09632, 0.09632]
INFO:root:Epoch 939 [39.0s + 34.7s]: train==[548.80872=548.72858 + 0.08006], recall=[0.64536, 0.64536], precision=[0.06454, 0.06454], hit=[0.64536, 0.64536], ndcg=[0.37505, 0.37505]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 939 [40.3s + 35.5s]: train==[693.03784=693.02264 + 0.01571], recall=[0.20745, 0.20745], precision=[0.02075, 0.02075], hit=[0.20745, 0.20745], ndcg=[0.09378, 0.09378]
INFO:root:Epoch 479 [79.1s + 44.8s]: train==[324.88110=324.80850 + 0.07224], recall=[0.66904, 0.66904], precision=[0.06690, 0.06690], hit=[0.66904, 0.66904], ndcg=[0.38564, 0.38564]
INFO:root:Epoch 949 [39.7s + 35.0s]: train==[545.52948=545.44733 + 0.08241], recall=[0.64321, 0.64321], precision=[0.06432, 0.06432], hit=[0.64321, 0.64321], ndcg=[0.37299, 0.37299]
INFO:root:Epoch 279 [125.6s + 37.6s]: train==[331.41238=331.26990 + 0.14254], recall=[0.68642, 0.68642], precision=[0.06864, 0.06864], hit=[0.68642, 0.68642], ndcg=[0.40133, 0.40133]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 949 [37.9s + 36.6s]: train==[693.02881=693.01251 + 0.01571], recall=[0.20993, 0.20993], precision=[0.02099, 0.02099], hit=[0.20993, 0.20993], ndcg=[0.09400, 0.09400]
INFO:root:Epoch 959 [38.0s + 35.8s]: train==[542.30182=542.21680 + 0.08506], recall=[0.64222, 0.64222], precision=[0.06422, 0.06422], hit=[0.64222, 0.64222], ndcg=[0.37442, 0.37442]
INFO:root:Epoch 959 [38.5s + 34.4s]: train==[693.03143=693.01666 + 0.01571], recall=[0.20877, 0.20877], precision=[0.02088, 0.02088], hit=[0.20877, 0.20877], ndcg=[0.09455, 0.09455]
INFO:root:Epoch 489 [72.6s + 45.5s]: train==[325.35501=325.28134 + 0.07374], recall=[0.67119, 0.67119], precision=[0.06712, 0.06712], hit=[0.67119, 0.67119], ndcg=[0.38905, 0.38905]
INFO:root:Epoch 969 [39.4s + 37.7s]: train==[537.17969=537.09235 + 0.08749], recall=[0.64967, 0.64967], precision=[0.06497, 0.06497], hit=[0.64967, 0.64967], ndcg=[0.37863, 0.37863]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 969 [39.0s + 37.0s]: train==[693.02234=693.00702 + 0.01571], recall=[0.21225, 0.21225], precision=[0.02123, 0.02123], hit=[0.21225, 0.21225], ndcg=[0.09457, 0.09457]
INFO:root:Epoch 979 [37.7s + 34.8s]: train==[533.10559=533.01575 + 0.08994], recall=[0.65033, 0.65033], precision=[0.06503, 0.06503], hit=[0.65033, 0.65033], ndcg=[0.37732, 0.37732]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 979 [38.2s + 34.9s]: train==[693.01849=693.00281 + 0.01571], recall=[0.21192, 0.21192], precision=[0.02119, 0.02119], hit=[0.21192, 0.21192], ndcg=[0.09567, 0.09567]
INFO:root:Epoch 499 [71.4s + 44.4s]: train==[320.62253=320.54712 + 0.07518], recall=[0.67351, 0.67351], precision=[0.06735, 0.06735], hit=[0.67351, 0.67351], ndcg=[0.39378, 0.39378]
INFO:root:Epoch 289 [124.1s + 36.6s]: train==[326.98694=326.83911 + 0.14752], recall=[0.69222, 0.69222], precision=[0.06922, 0.06922], hit=[0.69222, 0.69222], ndcg=[0.39965, 0.39965]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 989 [37.1s + 35.3s]: train==[528.28510=528.19250 + 0.09230], recall=[0.64503, 0.64503], precision=[0.06450, 0.06450], hit=[0.64503, 0.64503], ndcg=[0.37787, 0.37787]
INFO:root:Epoch 989 [39.5s + 36.2s]: train==[693.02740=693.01154 + 0.01571], recall=[0.21258, 0.21258], precision=[0.02126, 0.02126], hit=[0.21258, 0.21258], ndcg=[0.09427, 0.09427]
INFO:root:Epoch 999 [40.5s + 37.1s]: train==[525.05121=524.95654 + 0.09463], recall=[0.64801, 0.64801], precision=[0.06480, 0.06480], hit=[0.64801, 0.64801], ndcg=[0.37870, 0.37870]
INFO:root:Epoch 999 [38.9s + 35.1s]: train==[693.02997=693.01440 + 0.01571], recall=[0.21142, 0.21142], precision=[0.02114, 0.02114], hit=[0.21142, 0.21142], ndcg=[0.09420, 0.09420]
INFO:root:Epoch 509 [70.1s + 45.7s]: train==[322.34760=322.27051 + 0.07676], recall=[0.67450, 0.67450], precision=[0.06745, 0.06745], hit=[0.67450, 0.67450], ndcg=[0.39423, 0.39423]
INFO:root:Epoch 1009 [38.2s + 34.8s]: train==[520.60406=520.50641 + 0.09729], recall=[0.64719, 0.64719], precision=[0.06472, 0.06472], hit=[0.64719, 0.64719], ndcg=[0.37746, 0.37746]
INFO:root:Epoch 1009 [38.2s + 37.3s]: train==[693.02057=693.00488 + 0.01571], recall=[0.21175, 0.21175], precision=[0.02118, 0.02118], hit=[0.21175, 0.21175], ndcg=[0.09456, 0.09456]
INFO:root:Epoch 1019 [39.4s + 35.4s]: train==[517.54388=517.44440 + 0.09971], recall=[0.65182, 0.65182], precision=[0.06518, 0.06518], hit=[0.65182, 0.65182], ndcg=[0.37857, 0.37857]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 299 [124.5s + 36.6s]: train==[321.87842=321.72592 + 0.15229], recall=[0.68858, 0.68858], precision=[0.06886, 0.06886], hit=[0.68858, 0.68858], ndcg=[0.39904, 0.39904]
INFO:root:Epoch 1019 [38.3s + 34.0s]: train==[693.01953=693.00385 + 0.01571], recall=[0.21258, 0.21258], precision=[0.02126, 0.02126], hit=[0.21258, 0.21258], ndcg=[0.09544, 0.09544]
INFO:root:Epoch 519 [69.8s + 45.1s]: train==[318.64090=318.56268 + 0.07824], recall=[0.67401, 0.67401], precision=[0.06740, 0.06740], hit=[0.67401, 0.67401], ndcg=[0.39072, 0.39072]
INFO:root:Epoch 1029 [41.2s + 39.0s]: train==[514.22833=514.12616 + 0.10225], recall=[0.65464, 0.65464], precision=[0.06546, 0.06546], hit=[0.65464, 0.65464], ndcg=[0.37965, 0.37965]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1029 [37.8s + 35.1s]: train==[693.01862=693.00269 + 0.01571], recall=[0.21076, 0.21076], precision=[0.02108, 0.02108], hit=[0.21076, 0.21076], ndcg=[0.09522, 0.09522]
INFO:root:Epoch 1039 [38.9s + 34.8s]: train==[510.67999=510.57584 + 0.10454], recall=[0.65281, 0.65281], precision=[0.06528, 0.06528], hit=[0.65281, 0.65281], ndcg=[0.37684, 0.37684]
INFO:root:Epoch 1039 [39.4s + 34.6s]: train==[693.03021=693.01385 + 0.01571], recall=[0.21109, 0.21109], precision=[0.02111, 0.02111], hit=[0.21109, 0.21109], ndcg=[0.09597, 0.09597]
INFO:root:Epoch 529 [72.0s + 45.2s]: train==[321.35202=321.27203 + 0.07970], recall=[0.67450, 0.67450], precision=[0.06745, 0.06745], hit=[0.67450, 0.67450], ndcg=[0.39343, 0.39343]
INFO:root:Epoch 1049 [38.3s + 35.0s]: train==[506.72046=506.61334 + 0.10695], recall=[0.65381, 0.65381], precision=[0.06538, 0.06538], hit=[0.65381, 0.65381], ndcg=[0.37880, 0.37880]
INFO:root:Epoch 1049 [38.7s + 35.0s]: train==[693.01740=693.00140 + 0.01571], recall=[0.21523, 0.21523], precision=[0.02152, 0.02152], hit=[0.21523, 0.21523], ndcg=[0.09553, 0.09553]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 309 [125.4s + 40.0s]: train==[318.08563=317.92825 + 0.15745], recall=[0.68907, 0.68907], precision=[0.06891, 0.06891], hit=[0.68907, 0.68907], ndcg=[0.39983, 0.39983]
INFO:root:Epoch 1059 [39.1s + 34.9s]: train==[502.01761=501.90857 + 0.10905], recall=[0.65762, 0.65762], precision=[0.06576, 0.06576], hit=[0.65762, 0.65762], ndcg=[0.37867, 0.37867]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1059 [37.5s + 35.6s]: train==[693.01630=693.00104 + 0.01571], recall=[0.21490, 0.21490], precision=[0.02149, 0.02149], hit=[0.21490, 0.21490], ndcg=[0.09444, 0.09444]
INFO:root:Epoch 539 [70.9s + 44.9s]: train==[318.80301=318.72198 + 0.08103], recall=[0.67500, 0.67500], precision=[0.06750, 0.06750], hit=[0.67500, 0.67500], ndcg=[0.39324, 0.39324]
INFO:root:Epoch 1069 [37.9s + 35.8s]: train==[499.31378=499.20255 + 0.11144], recall=[0.65728, 0.65728], precision=[0.06573, 0.06573], hit=[0.65728, 0.65728], ndcg=[0.38189, 0.38189]
INFO:root:Epoch 1069 [37.0s + 35.4s]: train==[693.02411=693.00781 + 0.01571], recall=[0.21424, 0.21424], precision=[0.02142, 0.02142], hit=[0.21424, 0.21424], ndcg=[0.09680, 0.09680]
INFO:root:Epoch 1079 [38.8s + 34.7s]: train==[498.97922=498.86581 + 0.11389], recall=[0.65083, 0.65083], precision=[0.06508, 0.06508], hit=[0.65083, 0.65083], ndcg=[0.37830, 0.37830]
INFO:root:Epoch 1079 [39.6s + 39.5s]: train==[693.01562=693.00006 + 0.01571], recall=[0.20894, 0.20894], precision=[0.02089, 0.02089], hit=[0.20894, 0.20894], ndcg=[0.09416, 0.09416]
INFO:root:Epoch 549 [76.4s + 47.1s]: train==[315.78894=315.70663 + 0.08267], recall=[0.67947, 0.67947], precision=[0.06795, 0.06795], hit=[0.67947, 0.67947], ndcg=[0.39588, 0.39588]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1089 [38.6s + 35.5s]: train==[493.59705=493.48111 + 0.11622], recall=[0.65977, 0.65977], precision=[0.06598, 0.06598], hit=[0.65977, 0.65977], ndcg=[0.38114, 0.38114]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 319 [126.2s + 35.6s]: train==[313.56772=313.40561 + 0.16190], recall=[0.69222, 0.69222], precision=[0.06922, 0.06922], hit=[0.69222, 0.69222], ndcg=[0.39989, 0.39989]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1089 [38.2s + 34.8s]: train==[692.99304=692.97662 + 0.01571], recall=[0.21026, 0.21026], precision=[0.02103, 0.02103], hit=[0.21026, 0.21026], ndcg=[0.09473, 0.09473]
INFO:root:Epoch 1099 [39.2s + 35.3s]: train==[490.01263=489.89407 + 0.11837], recall=[0.65728, 0.65728], precision=[0.06573, 0.06573], hit=[0.65728, 0.65728], ndcg=[0.37891, 0.37891]
INFO:root:Epoch 1099 [38.2s + 35.6s]: train==[693.01172=692.99622 + 0.01571], recall=[0.20861, 0.20861], precision=[0.02086, 0.02086], hit=[0.20861, 0.20861], ndcg=[0.09479, 0.09479]
INFO:root:Epoch 559 [73.6s + 45.6s]: train==[313.46564=313.38132 + 0.08402], recall=[0.67467, 0.67467], precision=[0.06747, 0.06747], hit=[0.67467, 0.67467], ndcg=[0.39368, 0.39368]
INFO:root:Epoch 1109 [39.3s + 35.4s]: train==[485.77298=485.65201 + 0.12068], recall=[0.65877, 0.65877], precision=[0.06588, 0.06588], hit=[0.65877, 0.65877], ndcg=[0.38297, 0.38297]
INFO:root:Epoch 1109 [42.8s + 36.9s]: train==[692.99414=692.97839 + 0.01571], recall=[0.21440, 0.21440], precision=[0.02144, 0.02144], hit=[0.21440, 0.21440], ndcg=[0.09537, 0.09537]
INFO:root:Epoch 1119 [37.4s + 37.3s]: train==[482.44711=482.32452 + 0.12289], recall=[0.65695, 0.65695], precision=[0.06570, 0.06570], hit=[0.65695, 0.65695], ndcg=[0.37931, 0.37931]
INFO:root:Epoch 1119 [36.8s + 34.8s]: train==[693.00482=692.98950 + 0.01571], recall=[0.21308, 0.21308], precision=[0.02131, 0.02131], hit=[0.21308, 0.21308], ndcg=[0.09691, 0.09691]
INFO:root:Epoch 329 [126.5s + 36.9s]: train==[310.54025=310.37390 + 0.16694], recall=[0.69834, 0.69834], precision=[0.06983, 0.06983], hit=[0.69834, 0.69834], ndcg=[0.40434, 0.40434]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 569 [72.4s + 45.8s]: train==[311.40692=311.32159 + 0.08541], recall=[0.68013, 0.68013], precision=[0.06801, 0.06801], hit=[0.68013, 0.68013], ndcg=[0.39148, 0.39148]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1129 [38.0s + 35.0s]: train==[480.70804=480.58331 + 0.12479], recall=[0.65331, 0.65331], precision=[0.06533, 0.06533], hit=[0.65331, 0.65331], ndcg=[0.37833, 0.37833]
INFO:root:Epoch 1129 [37.8s + 35.4s]: train==[693.00732=692.99103 + 0.01571], recall=[0.21589, 0.21589], precision=[0.02159, 0.02159], hit=[0.21589, 0.21589], ndcg=[0.09679, 0.09679]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1139 [37.8s + 34.6s]: train==[477.01263=476.88513 + 0.12711], recall=[0.65894, 0.65894], precision=[0.06589, 0.06589], hit=[0.65894, 0.65894], ndcg=[0.38457, 0.38457]
INFO:root:Epoch 1139 [42.7s + 37.2s]: train==[692.99677=692.98120 + 0.01571], recall=[0.21805, 0.21805], precision=[0.02180, 0.02180], hit=[0.21805, 0.21805], ndcg=[0.09715, 0.09715]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 579 [74.2s + 45.4s]: train==[311.11349=311.02661 + 0.08703], recall=[0.68096, 0.68096], precision=[0.06810, 0.06810], hit=[0.68096, 0.68096], ndcg=[0.39559, 0.39559]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1149 [39.7s + 36.0s]: train==[474.20789=474.07864 + 0.12943], recall=[0.65579, 0.65579], precision=[0.06558, 0.06558], hit=[0.65579, 0.65579], ndcg=[0.37992, 0.37992]
INFO:root:Epoch 1149 [38.1s + 35.8s]: train==[692.98315=692.96722 + 0.01571], recall=[0.21722, 0.21722], precision=[0.02172, 0.02172], hit=[0.21722, 0.21722], ndcg=[0.09638, 0.09638]
INFO:root:Epoch 1159 [38.6s + 35.0s]: train==[471.67087=471.54047 + 0.13099], recall=[0.65679, 0.65679], precision=[0.06568, 0.06568], hit=[0.65679, 0.65679], ndcg=[0.37919, 0.37919]
INFO:root:Epoch 339 [123.1s + 36.9s]: train==[310.65698=310.48483 + 0.17165], recall=[0.69719, 0.69719], precision=[0.06972, 0.06972], hit=[0.69719, 0.69719], ndcg=[0.40500, 0.40500]
INFO:root:Epoch 1159 [38.8s + 37.3s]: train==[693.01788=693.00305 + 0.01571], recall=[0.21540, 0.21540], precision=[0.02154, 0.02154], hit=[0.21540, 0.21540], ndcg=[0.09590, 0.09590]
INFO:root:Epoch 589 [72.5s + 44.6s]: train==[314.85364=314.76544 + 0.08841], recall=[0.67401, 0.67401], precision=[0.06740, 0.06740], hit=[0.67401, 0.67401], ndcg=[0.39121, 0.39121]
INFO:root:Epoch 1169 [37.6s + 36.4s]: train==[469.87170=469.73840 + 0.13319], recall=[0.65745, 0.65745], precision=[0.06575, 0.06575], hit=[0.65745, 0.65745], ndcg=[0.38303, 0.38303]
INFO:root:Epoch 1169 [38.6s + 36.0s]: train==[692.99261=692.97766 + 0.01571], recall=[0.21358, 0.21358], precision=[0.02136, 0.02136], hit=[0.21358, 0.21358], ndcg=[0.09516, 0.09516]
INFO:root:Epoch 1179 [37.2s + 35.4s]: train==[468.21402=468.07870 + 0.13507], recall=[0.65811, 0.65811], precision=[0.06581, 0.06581], hit=[0.65811, 0.65811], ndcg=[0.38127, 0.38127]
INFO:root:Epoch 1179 [38.4s + 38.4s]: train==[692.98407=692.96844 + 0.01571], recall=[0.21358, 0.21358], precision=[0.02136, 0.02136], hit=[0.21358, 0.21358], ndcg=[0.09572, 0.09572]
INFO:root:Epoch 599 [74.1s + 45.6s]: train==[309.46112=309.37091 + 0.09005], recall=[0.67947, 0.67947], precision=[0.06795, 0.06795], hit=[0.67947, 0.67947], ndcg=[0.39785, 0.39785]
INFO:root:Epoch 1189 [37.7s + 34.4s]: train==[464.55963=464.42270 + 0.13724], recall=[0.66258, 0.66258], precision=[0.06626, 0.06626], hit=[0.66258, 0.66258], ndcg=[0.38280, 0.38280]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1189 [38.7s + 35.5s]: train==[693.00616=692.99036 + 0.01571], recall=[0.21838, 0.21838], precision=[0.02184, 0.02184], hit=[0.21838, 0.21838], ndcg=[0.09771, 0.09771]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 349 [125.3s + 36.6s]: train==[304.74710=304.57050 + 0.17667], recall=[0.69901, 0.69901], precision=[0.06990, 0.06990], hit=[0.69901, 0.69901], ndcg=[0.40469, 0.40469]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1199 [41.2s + 37.6s]: train==[461.12186=460.98322 + 0.13902], recall=[0.65877, 0.65877], precision=[0.06588, 0.06588], hit=[0.65877, 0.65877], ndcg=[0.38190, 0.38190]
INFO:root:Epoch 1199 [37.9s + 35.5s]: train==[692.98975=692.97363 + 0.01571], recall=[0.21126, 0.21126], precision=[0.02113, 0.02113], hit=[0.21126, 0.21126], ndcg=[0.09413, 0.09413]
INFO:root:Epoch 609 [70.9s + 45.1s]: train==[309.19266=309.10101 + 0.09159], recall=[0.67599, 0.67599], precision=[0.06760, 0.06760], hit=[0.67599, 0.67599], ndcg=[0.39478, 0.39478]
INFO:root:Epoch 1209 [37.8s + 35.1s]: train==[458.61502=458.47379 + 0.14129], recall=[0.65728, 0.65728], precision=[0.06573, 0.06573], hit=[0.65728, 0.65728], ndcg=[0.38214, 0.38214]
INFO:root:Epoch 1209 [38.3s + 35.5s]: train==[693.00055=692.98438 + 0.01571], recall=[0.21275, 0.21275], precision=[0.02127, 0.02127], hit=[0.21275, 0.21275], ndcg=[0.09616, 0.09616]
INFO:root:Epoch 1219 [38.7s + 34.8s]: train==[456.33646=456.19354 + 0.14287], recall=[0.65745, 0.65745], precision=[0.06575, 0.06575], hit=[0.65745, 0.65745], ndcg=[0.38205, 0.38205]
INFO:root:Epoch 1219 [37.5s + 36.4s]: train==[692.99628=692.98029 + 0.01571], recall=[0.21407, 0.21407], precision=[0.02141, 0.02141], hit=[0.21407, 0.21407], ndcg=[0.09710, 0.09710]
INFO:root:Epoch 619 [74.7s + 48.6s]: train==[305.84872=305.75568 + 0.09312], recall=[0.68162, 0.68162], precision=[0.06816, 0.06816], hit=[0.68162, 0.68162], ndcg=[0.39571, 0.39571]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1229 [40.8s + 38.3s]: train==[453.28259=453.13809 + 0.14464], recall=[0.66258, 0.66258], precision=[0.06626, 0.06626], hit=[0.66258, 0.66258], ndcg=[0.38471, 0.38471]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 359 [132.9s + 38.4s]: train==[300.18530=300.00391 + 0.18131], recall=[0.70563, 0.70563], precision=[0.07056, 0.07056], hit=[0.70563, 0.70563], ndcg=[0.40806, 0.40806]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1229 [38.9s + 35.5s]: train==[692.98157=692.96637 + 0.01571], recall=[0.21639, 0.21639], precision=[0.02164, 0.02164], hit=[0.21639, 0.21639], ndcg=[0.09748, 0.09748]
INFO:root:Epoch 1239 [38.0s + 35.6s]: train==[453.77826=453.63242 + 0.14636], recall=[0.65811, 0.65811], precision=[0.06581, 0.06581], hit=[0.65811, 0.65811], ndcg=[0.38388, 0.38388]
INFO:root:Epoch 1239 [36.8s + 37.7s]: train==[692.98920=692.97333 + 0.01571], recall=[0.21192, 0.21192], precision=[0.02119, 0.02119], hit=[0.21192, 0.21192], ndcg=[0.09548, 0.09548]
INFO:root:Epoch 629 [73.8s + 43.6s]: train==[309.65091=309.55630 + 0.09438], recall=[0.68179, 0.68179], precision=[0.06818, 0.06818], hit=[0.68179, 0.68179], ndcg=[0.39723, 0.39723]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1249 [37.2s + 36.0s]: train==[451.92715=451.77890 + 0.14863], recall=[0.65811, 0.65811], precision=[0.06581, 0.06581], hit=[0.65811, 0.65811], ndcg=[0.37903, 0.37903]
INFO:root:Epoch 1249 [38.0s + 34.9s]: train==[692.99115=692.97473 + 0.01571], recall=[0.21424, 0.21424], precision=[0.02142, 0.02142], hit=[0.21424, 0.21424], ndcg=[0.09568, 0.09568]
INFO:root:Epoch 1259 [41.0s + 38.4s]: train==[447.88217=447.73215 + 0.15001], recall=[0.65662, 0.65662], precision=[0.06566, 0.06566], hit=[0.65662, 0.65662], ndcg=[0.38257, 0.38257]
INFO:root:Epoch 1259 [38.7s + 34.8s]: train==[692.97784=692.96210 + 0.01571], recall=[0.21374, 0.21374], precision=[0.02137, 0.02137], hit=[0.21374, 0.21374], ndcg=[0.09705, 0.09705]
INFO:root:Epoch 369 [127.0s + 37.4s]: train==[297.67392=297.48749 + 0.18637], recall=[0.70546, 0.70546], precision=[0.07055, 0.07055], hit=[0.70546, 0.70546], ndcg=[0.40887, 0.40887]
INFO:root:Epoch 639 [75.3s + 44.7s]: train==[306.73380=306.63809 + 0.09601], recall=[0.68295, 0.68295], precision=[0.06829, 0.06829], hit=[0.68295, 0.68295], ndcg=[0.39883, 0.39883]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1269 [39.5s + 34.7s]: train==[443.97733=443.82559 + 0.15194], recall=[0.65662, 0.65662], precision=[0.06566, 0.06566], hit=[0.65662, 0.65662], ndcg=[0.38130, 0.38130]
INFO:root:Epoch 1269 [38.1s + 37.0s]: train==[692.97784=692.96234 + 0.01571], recall=[0.21507, 0.21507], precision=[0.02151, 0.02151], hit=[0.21507, 0.21507], ndcg=[0.09624, 0.09624]
INFO:root:Epoch 1279 [36.4s + 35.8s]: train==[441.28558=441.13196 + 0.15356], recall=[0.65911, 0.65911], precision=[0.06591, 0.06591], hit=[0.65911, 0.65911], ndcg=[0.38179, 0.38179]
INFO:root:Epoch 1279 [38.1s + 38.7s]: train==[692.98694=692.97211 + 0.01571], recall=[0.21656, 0.21656], precision=[0.02166, 0.02166], hit=[0.21656, 0.21656], ndcg=[0.09790, 0.09790]
INFO:root:Epoch 649 [81.0s + 45.4s]: train==[302.98071=302.88315 + 0.09752], recall=[0.68129, 0.68129], precision=[0.06813, 0.06813], hit=[0.68129, 0.68129], ndcg=[0.39712, 0.39712]
INFO:root:Epoch 1289 [40.4s + 36.4s]: train==[442.91495=442.75946 + 0.15504], recall=[0.66440, 0.66440], precision=[0.06644, 0.06644], hit=[0.66440, 0.66440], ndcg=[0.38679, 0.38679]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1289 [37.9s + 35.8s]: train==[692.97552=692.96039 + 0.01571], recall=[0.21474, 0.21474], precision=[0.02147, 0.02147], hit=[0.21474, 0.21474], ndcg=[0.09632, 0.09632]
INFO:root:Epoch 1299 [37.4s + 35.6s]: train==[438.59836=438.44141 + 0.15682], recall=[0.66076, 0.66076], precision=[0.06608, 0.06608], hit=[0.66076, 0.66076], ndcg=[0.38368, 0.38368]
INFO:root:Epoch 379 [123.9s + 36.3s]: train==[294.54242=294.35153 + 0.19109], recall=[0.70728, 0.70728], precision=[0.07073, 0.07073], hit=[0.70728, 0.70728], ndcg=[0.41115, 0.41115]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1299 [38.6s + 36.3s]: train==[692.97058=692.95410 + 0.01571], recall=[0.21573, 0.21573], precision=[0.02157, 0.02157], hit=[0.21573, 0.21573], ndcg=[0.09588, 0.09588]
INFO:root:Epoch 659 [74.4s + 42.9s]: train==[302.76703=302.66827 + 0.09897], recall=[0.68543, 0.68543], precision=[0.06854, 0.06854], hit=[0.68543, 0.68543], ndcg=[0.39887, 0.39887]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1309 [37.1s + 36.5s]: train==[436.45419=436.29611 + 0.15810], recall=[0.66341, 0.66341], precision=[0.06634, 0.06634], hit=[0.66341, 0.66341], ndcg=[0.38687, 0.38687]
INFO:root:Epoch 1309 [39.1s + 37.0s]: train==[692.96686=692.95093 + 0.01571], recall=[0.21490, 0.21490], precision=[0.02149, 0.02149], hit=[0.21490, 0.21490], ndcg=[0.09638, 0.09638]
INFO:root:Epoch 1319 [41.3s + 37.2s]: train==[435.13687=434.97723 + 0.15979], recall=[0.66175, 0.66175], precision=[0.06618, 0.06618], hit=[0.66175, 0.66175], ndcg=[0.38397, 0.38397]
INFO:root:Epoch 1319 [37.9s + 36.2s]: train==[692.96637=692.95129 + 0.01571], recall=[0.21325, 0.21325], precision=[0.02132, 0.02132], hit=[0.21325, 0.21325], ndcg=[0.09607, 0.09607]
INFO:root:Epoch 669 [72.0s + 44.0s]: train==[299.30783=299.20706 + 0.10047], recall=[0.68709, 0.68709], precision=[0.06871, 0.06871], hit=[0.68709, 0.68709], ndcg=[0.39901, 0.39901]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1329 [36.9s + 35.7s]: train==[432.78943=432.62781 + 0.16153], recall=[0.66043, 0.66043], precision=[0.06604, 0.06604], hit=[0.66043, 0.66043], ndcg=[0.38303, 0.38303]
INFO:root:Epoch 1329 [38.4s + 34.1s]: train==[692.98273=692.96667 + 0.01571], recall=[0.21772, 0.21772], precision=[0.02177, 0.02177], hit=[0.21772, 0.21772], ndcg=[0.09691, 0.09691]
INFO:root:Epoch 389 [126.3s + 36.8s]: train==[295.91510=295.71921 + 0.19585], recall=[0.70977, 0.70977], precision=[0.07098, 0.07098], hit=[0.70977, 0.70977], ndcg=[0.41373, 0.41373]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1339 [39.9s + 35.8s]: train==[430.92252=430.75980 + 0.16297], recall=[0.66159, 0.66159], precision=[0.06616, 0.06616], hit=[0.66159, 0.66159], ndcg=[0.38421, 0.38421]
INFO:root:Epoch 1339 [43.2s + 38.5s]: train==[692.96600=692.94995 + 0.01571], recall=[0.21871, 0.21871], precision=[0.02187, 0.02187], hit=[0.21871, 0.21871], ndcg=[0.09803, 0.09803]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 679 [73.5s + 44.0s]: train==[302.73203=302.62994 + 0.10212], recall=[0.68444, 0.68444], precision=[0.06844, 0.06844], hit=[0.68444, 0.68444], ndcg=[0.39695, 0.39695]
INFO:root:Epoch 1349 [40.4s + 36.9s]: train==[427.82889=427.66470 + 0.16441], recall=[0.65679, 0.65679], precision=[0.06568, 0.06568], hit=[0.65679, 0.65679], ndcg=[0.38035, 0.38035]
INFO:root:Epoch 1349 [39.2s + 36.1s]: train==[692.98267=692.96692 + 0.01571], recall=[0.21937, 0.21937], precision=[0.02194, 0.02194], hit=[0.21937, 0.21937], ndcg=[0.09843, 0.09843]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1359 [38.0s + 37.1s]: train==[424.24475=424.07928 + 0.16566], recall=[0.65265, 0.65265], precision=[0.06526, 0.06526], hit=[0.65265, 0.65265], ndcg=[0.37990, 0.37990]
INFO:root:Epoch 1359 [37.7s + 35.7s]: train==[692.98065=692.96490 + 0.01571], recall=[0.21970, 0.21970], precision=[0.02197, 0.02197], hit=[0.21970, 0.21970], ndcg=[0.09956, 0.09956]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 689 [69.9s + 44.0s]: train==[300.68845=300.58521 + 0.10348], recall=[0.68924, 0.68924], precision=[0.06892, 0.06892], hit=[0.68924, 0.68924], ndcg=[0.40201, 0.40201]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1369 [40.4s + 37.5s]: train==[426.19434=426.02673 + 0.16716], recall=[0.65778, 0.65778], precision=[0.06578, 0.06578], hit=[0.65778, 0.65778], ndcg=[0.38141, 0.38141]
INFO:root:Epoch 399 [120.2s + 37.4s]: train==[294.32837=294.12695 + 0.20082], recall=[0.71142, 0.71142], precision=[0.07114, 0.07114], hit=[0.71142, 0.71142], ndcg=[0.41582, 0.41582]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1369 [43.0s + 38.0s]: train==[692.96802=692.95221 + 0.01571], recall=[0.22185, 0.22185], precision=[0.02219, 0.02219], hit=[0.22185, 0.22185], ndcg=[0.09807, 0.09807]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1379 [37.3s + 36.7s]: train==[422.33737=422.16806 + 0.16874], recall=[0.65695, 0.65695], precision=[0.06570, 0.06570], hit=[0.65695, 0.65695], ndcg=[0.38174, 0.38174]
INFO:root:Epoch 1379 [38.6s + 36.1s]: train==[692.96686=692.95105 + 0.01571], recall=[0.21606, 0.21606], precision=[0.02161, 0.02161], hit=[0.21606, 0.21606], ndcg=[0.09656, 0.09656]
INFO:root:Epoch 699 [73.9s + 43.9s]: train==[297.44568=297.34045 + 0.10515], recall=[0.69189, 0.69189], precision=[0.06919, 0.06919], hit=[0.69189, 0.69189], ndcg=[0.40261, 0.40261]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1389 [41.0s + 37.4s]: train==[423.18018=423.01022 + 0.17016], recall=[0.66258, 0.66258], precision=[0.06626, 0.06626], hit=[0.66258, 0.66258], ndcg=[0.38195, 0.38195]
INFO:root:Epoch 1389 [37.9s + 37.0s]: train==[692.95874=692.94269 + 0.01571], recall=[0.21854, 0.21854], precision=[0.02185, 0.02185], hit=[0.21854, 0.21854], ndcg=[0.09786, 0.09786]
INFO:root:Epoch 1399 [39.3s + 39.8s]: train==[417.80728=417.63550 + 0.17131], recall=[0.66060, 0.66060], precision=[0.06606, 0.06606], hit=[0.66060, 0.66060], ndcg=[0.38268, 0.38268]
INFO:root:Epoch 1399 [38.1s + 36.8s]: train==[692.97223=692.95691 + 0.01571], recall=[0.21937, 0.21937], precision=[0.02194, 0.02194], hit=[0.21937, 0.21937], ndcg=[0.09964, 0.09964]
INFO:root:Epoch 409 [131.9s + 37.3s]: train==[289.72815=289.52258 + 0.20569], recall=[0.71921, 0.71921], precision=[0.07192, 0.07192], hit=[0.71921, 0.71921], ndcg=[0.41994, 0.41994]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 709 [71.3s + 44.5s]: train==[297.91464=297.80789 + 0.10669], recall=[0.69735, 0.69735], precision=[0.06974, 0.06974], hit=[0.69735, 0.69735], ndcg=[0.40399, 0.40399]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1409 [38.6s + 36.3s]: train==[416.29739=416.12500 + 0.17263], recall=[0.65927, 0.65927], precision=[0.06593, 0.06593], hit=[0.65927, 0.65927], ndcg=[0.38312, 0.38312]
INFO:root:Epoch 1409 [39.3s + 38.1s]: train==[692.94867=692.93250 + 0.01571], recall=[0.21639, 0.21639], precision=[0.02164, 0.02164], hit=[0.21639, 0.21639], ndcg=[0.09830, 0.09830]
INFO:root:Epoch 1419 [39.4s + 34.9s]: train==[415.23471=415.06012 + 0.17408], recall=[0.65795, 0.65795], precision=[0.06579, 0.06579], hit=[0.65795, 0.65795], ndcg=[0.38228, 0.38228]
INFO:root:Epoch 1419 [39.1s + 35.8s]: train==[692.94562=692.92950 + 0.01572], recall=[0.21474, 0.21474], precision=[0.02147, 0.02147], hit=[0.21474, 0.21474], ndcg=[0.09691, 0.09691]
INFO:root:Epoch 719 [72.2s + 46.9s]: train==[296.83401=296.72565 + 0.10818], recall=[0.68626, 0.68626], precision=[0.06863, 0.06863], hit=[0.68626, 0.68626], ndcg=[0.40121, 0.40121]
INFO:root:Epoch 1429 [42.2s + 39.6s]: train==[412.32785=412.15207 + 0.17607], recall=[0.65662, 0.65662], precision=[0.06566, 0.06566], hit=[0.65662, 0.65662], ndcg=[0.38390, 0.38390]
INFO:root:Epoch 1429 [37.1s + 36.1s]: train==[692.96136=692.94507 + 0.01572], recall=[0.21805, 0.21805], precision=[0.02180, 0.02180], hit=[0.21805, 0.21805], ndcg=[0.09710, 0.09710]
INFO:root:Epoch 1439 [38.5s + 35.2s]: train==[411.73572=411.55899 + 0.17658], recall=[0.66109, 0.66109], precision=[0.06611, 0.06611], hit=[0.66109, 0.66109], ndcg=[0.38129, 0.38129]
INFO:root:Epoch 419 [126.1s + 38.1s]: train==[284.96735=284.75671 + 0.21044], recall=[0.70993, 0.70993], precision=[0.07099, 0.07099], hit=[0.70993, 0.70993], ndcg=[0.41460, 0.41460]
INFO:root:Epoch 1439 [39.4s + 35.9s]: train==[692.97559=692.95905 + 0.01572], recall=[0.21672, 0.21672], precision=[0.02167, 0.02167], hit=[0.21672, 0.21672], ndcg=[0.09694, 0.09694]
INFO:root:Epoch 729 [73.0s + 46.4s]: train==[290.31924=290.20966 + 0.10971], recall=[0.69189, 0.69189], precision=[0.06919, 0.06919], hit=[0.69189, 0.69189], ndcg=[0.40267, 0.40267]
INFO:root:Epoch 1449 [40.3s + 36.4s]: train==[411.88553=411.70801 + 0.17762], recall=[0.66175, 0.66175], precision=[0.06618, 0.06618], hit=[0.66175, 0.66175], ndcg=[0.38267, 0.38267]
INFO:root:Epoch 1449 [38.5s + 39.7s]: train==[692.96021=692.94464 + 0.01572], recall=[0.21937, 0.21937], precision=[0.02194, 0.02194], hit=[0.21937, 0.21937], ndcg=[0.09801, 0.09801]
INFO:root:Epoch 1459 [39.6s + 36.4s]: train==[410.36917=410.19009 + 0.17924], recall=[0.66175, 0.66175], precision=[0.06618, 0.06618], hit=[0.66175, 0.66175], ndcg=[0.38236, 0.38236]
INFO:root:Epoch 1459 [37.6s + 36.3s]: train==[692.93933=692.92249 + 0.01572], recall=[0.22086, 0.22086], precision=[0.02209, 0.02209], hit=[0.22086, 0.22086], ndcg=[0.09997, 0.09997]
INFO:root:Epoch 739 [71.4s + 46.4s]: train==[292.59290=292.48145 + 0.11136], recall=[0.69834, 0.69834], precision=[0.06983, 0.06983], hit=[0.69834, 0.69834], ndcg=[0.40413, 0.40413]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1469 [38.2s + 36.5s]: train==[407.13098=406.95084 + 0.18003], recall=[0.65927, 0.65927], precision=[0.06593, 0.06593], hit=[0.65927, 0.65927], ndcg=[0.37987, 0.37987]
INFO:root:Epoch 429 [124.7s + 37.2s]: train==[284.88046=284.66492 + 0.21540], recall=[0.71656, 0.71656], precision=[0.07166, 0.07166], hit=[0.71656, 0.71656], ndcg=[0.41755, 0.41755]
INFO:root:Epoch 1469 [38.4s + 38.2s]: train==[692.96820=692.95276 + 0.01572], recall=[0.22169, 0.22169], precision=[0.02217, 0.02217], hit=[0.22169, 0.22169], ndcg=[0.09905, 0.09905]
INFO:root:Epoch 1479 [38.0s + 37.2s]: train==[406.64560=406.46387 + 0.18155], recall=[0.65960, 0.65960], precision=[0.06596, 0.06596], hit=[0.65960, 0.65960], ndcg=[0.38365, 0.38365]
INFO:root:Epoch 1479 [42.0s + 40.3s]: train==[692.94897=692.93317 + 0.01572], recall=[0.21821, 0.21821], precision=[0.02182, 0.02182], hit=[0.21821, 0.21821], ndcg=[0.09754, 0.09754]
INFO:root:Epoch 749 [75.7s + 44.9s]: train==[290.88104=290.76791 + 0.11301], recall=[0.69735, 0.69735], precision=[0.06974, 0.06974], hit=[0.69735, 0.69735], ndcg=[0.40595, 0.40595]
INFO:root:Epoch 1489 [38.6s + 35.8s]: train==[407.67868=407.49625 + 0.18251], recall=[0.66656, 0.66656], precision=[0.06666, 0.06666], hit=[0.66656, 0.66656], ndcg=[0.38297, 0.38297]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1489 [37.3s + 35.9s]: train==[692.94586=692.93048 + 0.01572], recall=[0.22053, 0.22053], precision=[0.02205, 0.02205], hit=[0.22053, 0.22053], ndcg=[0.09881, 0.09881]
INFO:root:Epoch 1499 [39.2s + 35.8s]: train==[403.95557=403.77200 + 0.18372], recall=[0.66209, 0.66209], precision=[0.06621, 0.06621], hit=[0.66209, 0.66209], ndcg=[0.38451, 0.38451]
INFO:root:Epoch 1499 [38.6s + 35.6s]: train==[692.94690=692.93079 + 0.01572], recall=[0.21772, 0.21772], precision=[0.02177, 0.02177], hit=[0.21772, 0.21772], ndcg=[0.09640, 0.09640]
INFO:root:Epoch 759 [72.1s + 45.2s]: train==[288.65817=288.54398 + 0.11445], recall=[0.70066, 0.70066], precision=[0.07007, 0.07007], hit=[0.70066, 0.70066], ndcg=[0.40710, 0.40710]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1509 [39.4s + 36.1s]: train==[402.39133=402.20575 + 0.18507], recall=[0.66755, 0.66755], precision=[0.06675, 0.06675], hit=[0.66755, 0.66755], ndcg=[0.38407, 0.38407]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 439 [126.8s + 40.6s]: train==[279.64365=279.42377 + 0.22015], recall=[0.72334, 0.72334], precision=[0.07233, 0.07233], hit=[0.72334, 0.72334], ndcg=[0.42132, 0.42132]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1509 [38.9s + 35.2s]: train==[692.96063=692.94543 + 0.01572], recall=[0.21805, 0.21805], precision=[0.02180, 0.02180], hit=[0.21805, 0.21805], ndcg=[0.09866, 0.09866]
INFO:root:Epoch 1519 [40.1s + 36.2s]: train==[400.65366=400.46729 + 0.18642], recall=[0.66225, 0.66225], precision=[0.06623, 0.06623], hit=[0.66225, 0.66225], ndcg=[0.38557, 0.38557]
INFO:root:Epoch 1519 [38.3s + 36.7s]: train==[692.94055=692.92554 + 0.01572], recall=[0.21954, 0.21954], precision=[0.02195, 0.02195], hit=[0.21954, 0.21954], ndcg=[0.10000, 0.10000]
INFO:root:Epoch 769 [71.4s + 44.1s]: train==[287.26883=287.15280 + 0.11601], recall=[0.70546, 0.70546], precision=[0.07055, 0.07055], hit=[0.70546, 0.70546], ndcg=[0.40446, 0.40446]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1529 [37.7s + 35.8s]: train==[399.00516=398.81760 + 0.18726], recall=[0.66026, 0.66026], precision=[0.06603, 0.06603], hit=[0.66026, 0.66026], ndcg=[0.38283, 0.38283]
INFO:root:Epoch 1529 [39.5s + 37.1s]: train==[692.95044=692.93378 + 0.01572], recall=[0.21887, 0.21887], precision=[0.02189, 0.02189], hit=[0.21887, 0.21887], ndcg=[0.09894, 0.09894]
INFO:root:Epoch 1539 [40.9s + 38.4s]: train==[397.83258=397.64355 + 0.18902], recall=[0.65911, 0.65911], precision=[0.06591, 0.06591], hit=[0.65911, 0.65911], ndcg=[0.38383, 0.38383]
INFO:root:Epoch 449 [123.9s + 35.4s]: train==[276.72742=276.50238 + 0.22489], recall=[0.72500, 0.72500], precision=[0.07250, 0.07250], hit=[0.72500, 0.72500], ndcg=[0.42188, 0.42188]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1539 [38.7s + 38.8s]: train==[692.94910=692.93408 + 0.01572], recall=[0.22401, 0.22401], precision=[0.02240, 0.02240], hit=[0.22401, 0.22401], ndcg=[0.10159, 0.10159]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 779 [70.6s + 45.8s]: train==[286.72964=286.61185 + 0.11761], recall=[0.70480, 0.70480], precision=[0.07048, 0.07048], hit=[0.70480, 0.70480], ndcg=[0.40814, 0.40814]
INFO:root:Epoch 1549 [36.9s + 37.3s]: train==[396.80194=396.61258 + 0.18976], recall=[0.66424, 0.66424], precision=[0.06642, 0.06642], hit=[0.66424, 0.66424], ndcg=[0.38441, 0.38441]
INFO:root:Epoch 1549 [38.4s + 36.2s]: train==[692.93732=692.92163 + 0.01572], recall=[0.21556, 0.21556], precision=[0.02156, 0.02156], hit=[0.21556, 0.21556], ndcg=[0.09745, 0.09745]
INFO:root:Epoch 1559 [39.2s + 36.4s]: train==[400.08752=399.89627 + 0.19077], recall=[0.66175, 0.66175], precision=[0.06618, 0.06618], hit=[0.66175, 0.66175], ndcg=[0.38379, 0.38379]
INFO:root:Epoch 1559 [38.2s + 38.3s]: train==[692.94244=692.92639 + 0.01572], recall=[0.22202, 0.22202], precision=[0.02220, 0.02220], hit=[0.22202, 0.22202], ndcg=[0.09946, 0.09946]
INFO:root:Epoch 789 [72.9s + 46.3s]: train==[289.15680=289.03732 + 0.11914], recall=[0.70017, 0.70017], precision=[0.07002, 0.07002], hit=[0.70017, 0.70017], ndcg=[0.40726, 0.40726]
INFO:root:Epoch 1569 [43.2s + 38.6s]: train==[394.89270=394.70093 + 0.19149], recall=[0.66258, 0.66258], precision=[0.06626, 0.06626], hit=[0.66258, 0.66258], ndcg=[0.38304, 0.38304]
INFO:root:Epoch 1569 [39.2s + 37.0s]: train==[692.93921=692.92328 + 0.01572], recall=[0.22020, 0.22020], precision=[0.02202, 0.02202], hit=[0.22020, 0.22020], ndcg=[0.09942, 0.09942]
INFO:root:Epoch 1579 [38.0s + 35.7s]: train==[394.69247=394.50003 + 0.19265], recall=[0.66457, 0.66457], precision=[0.06646, 0.06646], hit=[0.66457, 0.66457], ndcg=[0.38414, 0.38414]
INFO:root:Epoch 459 [125.3s + 36.6s]: train==[273.86392=273.63455 + 0.22944], recall=[0.72467, 0.72467], precision=[0.07247, 0.07247], hit=[0.72467, 0.72467], ndcg=[0.42292, 0.42292]
INFO:root:Epoch 1579 [39.4s + 35.7s]: train==[692.93561=692.91943 + 0.01572], recall=[0.22566, 0.22566], precision=[0.02257, 0.02257], hit=[0.22566, 0.22566], ndcg=[0.10111, 0.10111]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 799 [68.9s + 45.2s]: train==[288.25269=288.13156 + 0.12100], recall=[0.70960, 0.70960], precision=[0.07096, 0.07096], hit=[0.70960, 0.70960], ndcg=[0.41119, 0.41119]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1589 [38.4s + 35.9s]: train==[392.51736=392.32349 + 0.19383], recall=[0.66308, 0.66308], precision=[0.06631, 0.06631], hit=[0.66308, 0.66308], ndcg=[0.38239, 0.38239]
INFO:root:Epoch 1589 [44.3s + 39.8s]: train==[692.94128=692.92609 + 0.01572], recall=[0.22583, 0.22583], precision=[0.02258, 0.02258], hit=[0.22583, 0.22583], ndcg=[0.09973, 0.09973]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1599 [38.3s + 36.6s]: train==[390.96262=390.76779 + 0.19462], recall=[0.65679, 0.65679], precision=[0.06568, 0.06568], hit=[0.65679, 0.65679], ndcg=[0.38161, 0.38161]
INFO:root:Epoch 1599 [38.4s + 36.1s]: train==[692.93896=692.92297 + 0.01572], recall=[0.22136, 0.22136], precision=[0.02214, 0.02214], hit=[0.22136, 0.22136], ndcg=[0.09897, 0.09897]
INFO:root:Epoch 809 [70.1s + 45.6s]: train==[281.17737=281.05515 + 0.12243], recall=[0.70944, 0.70944], precision=[0.07094, 0.07094], hit=[0.70944, 0.70944], ndcg=[0.41211, 0.41211]
INFO:root:Epoch 1609 [40.6s + 36.8s]: train==[390.56079=390.36533 + 0.19571], recall=[0.66209, 0.66209], precision=[0.06621, 0.06621], hit=[0.66209, 0.66209], ndcg=[0.38330, 0.38330]
INFO:root:Epoch 469 [128.8s + 36.5s]: train==[271.59412=271.36017 + 0.23431], recall=[0.73245, 0.73245], precision=[0.07325, 0.07325], hit=[0.73245, 0.73245], ndcg=[0.42872, 0.42872]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1609 [38.8s + 37.6s]: train==[692.93719=692.92072 + 0.01572], recall=[0.21954, 0.21954], precision=[0.02195, 0.02195], hit=[0.21954, 0.21954], ndcg=[0.09958, 0.09958]
INFO:root:Epoch 1619 [38.6s + 37.0s]: train==[389.39697=389.20004 + 0.19701], recall=[0.66656, 0.66656], precision=[0.06666, 0.06666], hit=[0.66656, 0.66656], ndcg=[0.38456, 0.38456]
INFO:root:Epoch 1619 [37.8s + 34.9s]: train==[692.93091=692.91400 + 0.01572], recall=[0.22285, 0.22285], precision=[0.02228, 0.02228], hit=[0.22285, 0.22285], ndcg=[0.09873, 0.09873]
INFO:root:Epoch 819 [71.6s + 45.0s]: train==[281.45306=281.32913 + 0.12387], recall=[0.71109, 0.71109], precision=[0.07111, 0.07111], hit=[0.71109, 0.71109], ndcg=[0.41250, 0.41250]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1629 [39.0s + 35.7s]: train==[388.79178=388.59366 + 0.19794], recall=[0.65977, 0.65977], precision=[0.06598, 0.06598], hit=[0.65977, 0.65977], ndcg=[0.38416, 0.38416]
INFO:root:Epoch 1629 [38.9s + 37.0s]: train==[692.91467=692.89948 + 0.01572], recall=[0.22219, 0.22219], precision=[0.02222, 0.02222], hit=[0.22219, 0.22219], ndcg=[0.09953, 0.09953]
INFO:root:Epoch 1639 [38.9s + 36.2s]: train==[386.78665=386.58749 + 0.19890], recall=[0.65960, 0.65960], precision=[0.06596, 0.06596], hit=[0.65960, 0.65960], ndcg=[0.38414, 0.38414]
INFO:root:Epoch 1639 [38.5s + 36.9s]: train==[692.92706=692.91071 + 0.01572], recall=[0.21970, 0.21970], precision=[0.02197, 0.02197], hit=[0.21970, 0.21970], ndcg=[0.09889, 0.09889]
INFO:root:Epoch 829 [72.6s + 45.3s]: train==[283.70801=283.58292 + 0.12551], recall=[0.71291, 0.71291], precision=[0.07129, 0.07129], hit=[0.71291, 0.71291], ndcg=[0.41143, 0.41143]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1649 [38.9s + 40.6s]: train==[384.99792=384.79834 + 0.19952], recall=[0.66358, 0.66358], precision=[0.06636, 0.06636], hit=[0.66358, 0.66358], ndcg=[0.38053, 0.38053]
INFO:root:Epoch 479 [127.8s + 39.2s]: train==[266.64856=266.40930 + 0.23932], recall=[0.72417, 0.72417], precision=[0.07242, 0.07242], hit=[0.72417, 0.72417], ndcg=[0.42585, 0.42585]
INFO:root:Epoch 1649 [40.2s + 36.9s]: train==[692.92651=692.91064 + 0.01572], recall=[0.22550, 0.22550], precision=[0.02255, 0.02255], hit=[0.22550, 0.22550], ndcg=[0.10149, 0.10149]
INFO:root:Epoch 1659 [39.3s + 37.1s]: train==[384.60748=384.40692 + 0.20056], recall=[0.66175, 0.66175], precision=[0.06618, 0.06618], hit=[0.66175, 0.66175], ndcg=[0.38261, 0.38261]
INFO:root:Epoch 1659 [39.1s + 36.2s]: train==[692.92157=692.90631 + 0.01572], recall=[0.22185, 0.22185], precision=[0.02219, 0.02219], hit=[0.22185, 0.22185], ndcg=[0.10057, 0.10057]
INFO:root:Epoch 839 [72.1s + 45.6s]: train==[280.11032=279.98303 + 0.12733], recall=[0.71457, 0.71457], precision=[0.07146, 0.07146], hit=[0.71457, 0.71457], ndcg=[0.41381, 0.41381]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1669 [40.3s + 35.7s]: train==[383.39774=383.19553 + 0.20180], recall=[0.66142, 0.66142], precision=[0.06614, 0.06614], hit=[0.66142, 0.66142], ndcg=[0.38462, 0.38462]
INFO:root:Epoch 1669 [40.0s + 36.6s]: train==[692.91119=692.89551 + 0.01572], recall=[0.22467, 0.22467], precision=[0.02247, 0.02247], hit=[0.22467, 0.22467], ndcg=[0.10241, 0.10241]
INFO:root:Epoch 1679 [42.5s + 39.8s]: train==[384.13000=383.92740 + 0.20252], recall=[0.66043, 0.66043], precision=[0.06604, 0.06604], hit=[0.66043, 0.66043], ndcg=[0.38558, 0.38558]
INFO:root:Epoch 489 [131.2s + 34.3s]: train==[266.62320=266.37909 + 0.24435], recall=[0.73245, 0.73245], precision=[0.07325, 0.07325], hit=[0.73245, 0.73245], ndcg=[0.42683, 0.42683]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1679 [38.3s + 37.1s]: train==[692.92096=692.90521 + 0.01572], recall=[0.22368, 0.22368], precision=[0.02237, 0.02237], hit=[0.22368, 0.22368], ndcg=[0.10046, 0.10046]
INFO:root:Epoch 849 [73.3s + 45.2s]: train==[279.61517=279.48605 + 0.12899], recall=[0.71142, 0.71142], precision=[0.07114, 0.07114], hit=[0.71142, 0.71142], ndcg=[0.41760, 0.41760]
INFO:root:Epoch 1689 [38.9s + 35.8s]: train==[382.10840=381.90460 + 0.20383], recall=[0.65894, 0.65894], precision=[0.06589, 0.06589], hit=[0.65894, 0.65894], ndcg=[0.38373, 0.38373]
INFO:root:Epoch 1689 [38.6s + 36.3s]: train==[692.91449=692.89868 + 0.01572], recall=[0.22434, 0.22434], precision=[0.02243, 0.02243], hit=[0.22434, 0.22434], ndcg=[0.10112, 0.10112]
INFO:root:Epoch 1699 [37.8s + 37.7s]: train==[380.67441=380.47043 + 0.20425], recall=[0.66225, 0.66225], precision=[0.06623, 0.06623], hit=[0.66225, 0.66225], ndcg=[0.38382, 0.38382]
INFO:root:Epoch 1699 [45.2s + 36.9s]: train==[692.90204=692.88593 + 0.01572], recall=[0.22070, 0.22070], precision=[0.02207, 0.02207], hit=[0.22070, 0.22070], ndcg=[0.10040, 0.10040]
INFO:root:Epoch 859 [78.0s + 45.7s]: train==[278.25937=278.12875 + 0.13055], recall=[0.71126, 0.71126], precision=[0.07113, 0.07113], hit=[0.71126, 0.71126], ndcg=[0.41321, 0.41321]
INFO:root:Epoch 1709 [39.1s + 35.5s]: train==[380.11942=379.91452 + 0.20506], recall=[0.66374, 0.66374], precision=[0.06637, 0.06637], hit=[0.66374, 0.66374], ndcg=[0.38507, 0.38507]
INFO:root:Epoch 1709 [37.7s + 36.4s]: train==[692.90601=692.89038 + 0.01572], recall=[0.22450, 0.22450], precision=[0.02245, 0.02245], hit=[0.22450, 0.22450], ndcg=[0.09975, 0.09975]
INFO:root:Epoch 1719 [39.2s + 37.4s]: train==[377.55173=377.34589 + 0.20594], recall=[0.66523, 0.66523], precision=[0.06652, 0.06652], hit=[0.66523, 0.66523], ndcg=[0.38398, 0.38398]
INFO:root:Epoch 499 [125.2s + 38.4s]: train==[262.73132=262.48221 + 0.24920], recall=[0.73195, 0.73195], precision=[0.07320, 0.07320], hit=[0.73195, 0.73195], ndcg=[0.42802, 0.42802]
INFO:root:Epoch 1719 [38.2s + 35.9s]: train==[692.91760=692.90210 + 0.01572], recall=[0.22384, 0.22384], precision=[0.02238, 0.02238], hit=[0.22384, 0.22384], ndcg=[0.09947, 0.09947]
INFO:root:Epoch 869 [72.4s + 45.6s]: train==[277.28229=277.14978 + 0.13239], recall=[0.72285, 0.72285], precision=[0.07228, 0.07228], hit=[0.72285, 0.72285], ndcg=[0.41812, 0.41812]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1729 [39.0s + 36.8s]: train==[381.42590=381.21878 + 0.20676], recall=[0.66010, 0.66010], precision=[0.06601, 0.06601], hit=[0.66010, 0.66010], ndcg=[0.38058, 0.38058]
INFO:root:Epoch 1729 [42.4s + 35.7s]: train==[692.92438=692.90833 + 0.01572], recall=[0.22583, 0.22583], precision=[0.02258, 0.02258], hit=[0.22583, 0.22583], ndcg=[0.10135, 0.10135]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1739 [37.9s + 36.6s]: train==[374.90961=374.70166 + 0.20816], recall=[0.66192, 0.66192], precision=[0.06619, 0.06619], hit=[0.66192, 0.66192], ndcg=[0.38136, 0.38136]
INFO:root:Epoch 1739 [38.7s + 35.7s]: train==[692.90973=692.89459 + 0.01573], recall=[0.22715, 0.22715], precision=[0.02272, 0.02272], hit=[0.22715, 0.22715], ndcg=[0.10238, 0.10238]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 879 [72.7s + 45.9s]: train==[273.59814=273.46429 + 0.13384], recall=[0.71689, 0.71689], precision=[0.07169, 0.07169], hit=[0.71689, 0.71689], ndcg=[0.41820, 0.41820]
INFO:root:Epoch 1749 [38.9s + 38.7s]: train==[376.67560=376.46643 + 0.20885], recall=[0.66722, 0.66722], precision=[0.06672, 0.06672], hit=[0.66722, 0.66722], ndcg=[0.38271, 0.38271]
INFO:root:Epoch 509 [124.5s + 36.8s]: train==[259.54553=259.29190 + 0.25389], recall=[0.73642, 0.73642], precision=[0.07364, 0.07364], hit=[0.73642, 0.73642], ndcg=[0.43613, 0.43613]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1749 [37.6s + 37.8s]: train==[692.89880=692.88263 + 0.01573], recall=[0.22434, 0.22434], precision=[0.02243, 0.02243], hit=[0.22434, 0.22434], ndcg=[0.10023, 0.10023]
INFO:root:Epoch 1759 [37.8s + 36.8s]: train==[373.75998=373.55017 + 0.20982], recall=[0.66258, 0.66258], precision=[0.06626, 0.06626], hit=[0.66258, 0.66258], ndcg=[0.38539, 0.38539]
INFO:root:Epoch 1759 [40.6s + 35.0s]: train==[692.88525=692.86987 + 0.01573], recall=[0.22533, 0.22533], precision=[0.02253, 0.02253], hit=[0.22533, 0.22533], ndcg=[0.10157, 0.10157]
INFO:root:Epoch 889 [72.4s + 43.4s]: train==[275.38449=275.24927 + 0.13551], recall=[0.72053, 0.72053], precision=[0.07205, 0.07205], hit=[0.72053, 0.72053], ndcg=[0.41668, 0.41668]
INFO:root:Epoch 1769 [38.5s + 35.9s]: train==[373.67975=373.46887 + 0.21084], recall=[0.65927, 0.65927], precision=[0.06593, 0.06593], hit=[0.65927, 0.65927], ndcg=[0.38081, 0.38081]
INFO:root:Epoch 1769 [39.6s + 37.2s]: train==[692.88770=692.87177 + 0.01573], recall=[0.22417, 0.22417], precision=[0.02242, 0.02242], hit=[0.22417, 0.22417], ndcg=[0.10089, 0.10089]
INFO:root:Epoch 1779 [40.1s + 35.7s]: train==[374.89236=374.68103 + 0.21175], recall=[0.66192, 0.66192], precision=[0.06619, 0.06619], hit=[0.66192, 0.66192], ndcg=[0.38469, 0.38469]
INFO:root:Epoch 1779 [39.2s + 35.2s]: train==[692.90973=692.89404 + 0.01573], recall=[0.21954, 0.21954], precision=[0.02195, 0.02195], hit=[0.21954, 0.21954], ndcg=[0.09963, 0.09963]
INFO:root:Epoch 899 [74.6s + 44.7s]: train==[272.29019=272.15323 + 0.13705], recall=[0.71970, 0.71970], precision=[0.07197, 0.07197], hit=[0.71970, 0.71970], ndcg=[0.42018, 0.42018]
INFO:root:Epoch 1789 [41.6s + 38.4s]: train==[370.51816=370.30539 + 0.21247], recall=[0.66341, 0.66341], precision=[0.06634, 0.06634], hit=[0.66341, 0.66341], ndcg=[0.38433, 0.38433]
INFO:root:Epoch 519 [132.1s + 39.4s]: train==[256.71039=256.45166 + 0.25862], recall=[0.73560, 0.73560], precision=[0.07356, 0.07356], hit=[0.73560, 0.73560], ndcg=[0.43347, 0.43347]
INFO:root:Epoch 1789 [39.0s + 38.4s]: train==[692.88580=692.86963 + 0.01573], recall=[0.22831, 0.22831], precision=[0.02283, 0.02283], hit=[0.22831, 0.22831], ndcg=[0.10286, 0.10286]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1799 [39.0s + 37.2s]: train==[371.65173=371.43832 + 0.21309], recall=[0.66821, 0.66821], precision=[0.06682, 0.06682], hit=[0.66821, 0.66821], ndcg=[0.38877, 0.38877]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1799 [40.1s + 36.1s]: train==[692.89716=692.88190 + 0.01573], recall=[0.22632, 0.22632], precision=[0.02263, 0.02263], hit=[0.22632, 0.22632], ndcg=[0.10203, 0.10203]
INFO:root:Epoch 909 [73.1s + 43.5s]: train==[270.61642=270.47729 + 0.13906], recall=[0.72119, 0.72119], precision=[0.07212, 0.07212], hit=[0.72119, 0.72119], ndcg=[0.42182, 0.42182]
INFO:root:Epoch 1809 [38.2s + 36.0s]: train==[370.21152=369.99777 + 0.21393], recall=[0.65894, 0.65894], precision=[0.06589, 0.06589], hit=[0.65894, 0.65894], ndcg=[0.38144, 0.38144]
INFO:root:Epoch 1809 [40.8s + 43.3s]: train==[692.89349=692.87811 + 0.01573], recall=[0.22483, 0.22483], precision=[0.02248, 0.02248], hit=[0.22483, 0.22483], ndcg=[0.10102, 0.10102]
INFO:root:Epoch 1819 [42.6s + 37.0s]: train==[370.44427=370.22958 + 0.21466], recall=[0.65828, 0.65828], precision=[0.06583, 0.06583], hit=[0.65828, 0.65828], ndcg=[0.38314, 0.38314]
INFO:root:Epoch 529 [127.1s + 36.6s]: train==[254.34352=254.08044 + 0.26297], recall=[0.73675, 0.73675], precision=[0.07368, 0.07368], hit=[0.73675, 0.73675], ndcg=[0.43159, 0.43159]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 919 [71.8s + 45.1s]: train==[271.59113=271.45059 + 0.14065], recall=[0.72384, 0.72384], precision=[0.07238, 0.07238], hit=[0.72384, 0.72384], ndcg=[0.42020, 0.42020]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1819 [39.0s + 38.6s]: train==[692.89178=692.87598 + 0.01573], recall=[0.22533, 0.22533], precision=[0.02253, 0.02253], hit=[0.22533, 0.22533], ndcg=[0.10226, 0.10226]
INFO:root:Epoch 1829 [40.1s + 37.2s]: train==[365.87384=365.65839 + 0.21530], recall=[0.66341, 0.66341], precision=[0.06634, 0.06634], hit=[0.66341, 0.66341], ndcg=[0.38449, 0.38449]
INFO:root:Epoch 1829 [38.9s + 36.1s]: train==[692.89410=692.87842 + 0.01573], recall=[0.22881, 0.22881], precision=[0.02288, 0.02288], hit=[0.22881, 0.22881], ndcg=[0.10213, 0.10213]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1839 [39.4s + 36.7s]: train==[364.18845=363.97198 + 0.21660], recall=[0.65795, 0.65795], precision=[0.06579, 0.06579], hit=[0.65795, 0.65795], ndcg=[0.38108, 0.38108]
INFO:root:Epoch 929 [76.4s + 46.1s]: train==[268.77417=268.63214 + 0.14212], recall=[0.72864, 0.72864], precision=[0.07286, 0.07286], hit=[0.72864, 0.72864], ndcg=[0.42591, 0.42591]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1839 [42.0s + 39.5s]: train==[692.86285=692.84650 + 0.01573], recall=[0.22152, 0.22152], precision=[0.02215, 0.02215], hit=[0.22152, 0.22152], ndcg=[0.09980, 0.09980]
INFO:root:Epoch 1849 [42.0s + 39.9s]: train==[366.64050=366.42349 + 0.21731], recall=[0.65662, 0.65662], precision=[0.06566, 0.06566], hit=[0.65662, 0.65662], ndcg=[0.38189, 0.38189]
INFO:root:Epoch 1849 [39.8s + 38.9s]: train==[692.89807=692.88257 + 0.01573], recall=[0.22864, 0.22864], precision=[0.02286, 0.02286], hit=[0.22864, 0.22864], ndcg=[0.10279, 0.10279]
INFO:root:Epoch 1859 [41.7s + 38.1s]: train==[368.13275=367.91464 + 0.21793], recall=[0.65695, 0.65695], precision=[0.06570, 0.06570], hit=[0.65695, 0.65695], ndcg=[0.38306, 0.38306]
INFO:root:Epoch 539 [127.9s + 39.8s]: train==[253.20042=252.93259 + 0.26795], recall=[0.74172, 0.74172], precision=[0.07417, 0.07417], hit=[0.74172, 0.74172], ndcg=[0.43929, 0.43929]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 939 [73.0s + 45.3s]: train==[270.28015=270.13635 + 0.14383], recall=[0.72798, 0.72798], precision=[0.07280, 0.07280], hit=[0.72798, 0.72798], ndcg=[0.42017, 0.42017]
INFO:root:Epoch 1859 [37.8s + 37.1s]: train==[692.87500=692.85883 + 0.01573], recall=[0.22914, 0.22914], precision=[0.02291, 0.02291], hit=[0.22914, 0.22914], ndcg=[0.10262, 0.10262]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1869 [39.9s + 37.1s]: train==[366.93085=366.71255 + 0.21853], recall=[0.65712, 0.65712], precision=[0.06571, 0.06571], hit=[0.65712, 0.65712], ndcg=[0.38068, 0.38068]
INFO:root:Epoch 1869 [41.0s + 36.9s]: train==[692.88129=692.86572 + 0.01573], recall=[0.22815, 0.22815], precision=[0.02281, 0.02281], hit=[0.22815, 0.22815], ndcg=[0.10390, 0.10390]
INFO:root:Epoch 1879 [38.5s + 38.0s]: train==[364.60016=364.38055 + 0.21961], recall=[0.66043, 0.66043], precision=[0.06604, 0.06604], hit=[0.66043, 0.66043], ndcg=[0.38376, 0.38376]
INFO:root:Epoch 949 [72.8s + 46.4s]: train==[267.92029=267.77484 + 0.14543], recall=[0.73146, 0.73146], precision=[0.07315, 0.07315], hit=[0.73146, 0.73146], ndcg=[0.42231, 0.42231]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1879 [40.8s + 37.5s]: train==[692.89386=692.87769 + 0.01573], recall=[0.22831, 0.22831], precision=[0.02283, 0.02283], hit=[0.22831, 0.22831], ndcg=[0.10345, 0.10345]
INFO:root:Epoch 1889 [38.6s + 36.9s]: train==[363.36496=363.14423 + 0.22039], recall=[0.65911, 0.65911], precision=[0.06591, 0.06591], hit=[0.65911, 0.65911], ndcg=[0.38495, 0.38495]
INFO:root:Epoch 549 [124.1s + 37.2s]: train==[249.74432=249.47104 + 0.27332], recall=[0.74520, 0.74520], precision=[0.07452, 0.07452], hit=[0.74520, 0.74520], ndcg=[0.44083, 0.44083]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1889 [39.3s + 37.2s]: train==[692.90247=692.88702 + 0.01573], recall=[0.22798, 0.22798], precision=[0.02280, 0.02280], hit=[0.22798, 0.22798], ndcg=[0.10255, 0.10255]
INFO:root:Epoch 1899 [41.8s + 39.7s]: train==[362.81769=362.59631 + 0.22111], recall=[0.66159, 0.66159], precision=[0.06616, 0.06616], hit=[0.66159, 0.66159], ndcg=[0.38241, 0.38241]
INFO:root:Epoch 959 [72.9s + 45.4s]: train==[267.98624=267.83911 + 0.14716], recall=[0.73394, 0.73394], precision=[0.07339, 0.07339], hit=[0.73394, 0.73394], ndcg=[0.42630, 0.42630]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1899 [39.2s + 36.8s]: train==[692.87830=692.86230 + 0.01573], recall=[0.23179, 0.23179], precision=[0.02318, 0.02318], hit=[0.23179, 0.23179], ndcg=[0.10323, 0.10323]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1909 [39.8s + 37.4s]: train==[361.90070=361.67969 + 0.22126], recall=[0.66291, 0.66291], precision=[0.06629, 0.06629], hit=[0.66291, 0.66291], ndcg=[0.38660, 0.38660]
INFO:root:Epoch 1909 [38.8s + 37.7s]: train==[692.88000=692.86560 + 0.01573], recall=[0.22235, 0.22235], precision=[0.02224, 0.02224], hit=[0.22235, 0.22235], ndcg=[0.09944, 0.09944]
INFO:root:Epoch 1919 [38.4s + 36.4s]: train==[359.77963=359.55695 + 0.22233], recall=[0.66457, 0.66457], precision=[0.06646, 0.06646], hit=[0.66457, 0.66457], ndcg=[0.38471, 0.38471]
INFO:root:Epoch 969 [74.7s + 44.9s]: train==[262.02820=261.87958 + 0.14908], recall=[0.72997, 0.72997], precision=[0.07300, 0.07300], hit=[0.72997, 0.72997], ndcg=[0.42685, 0.42685]
INFO:root:Epoch 1919 [39.4s + 39.9s]: train==[692.87817=692.86108 + 0.01573], recall=[0.22732, 0.22732], precision=[0.02273, 0.02273], hit=[0.22732, 0.22732], ndcg=[0.10204, 0.10204]
INFO:root:Epoch 1929 [42.6s + 37.2s]: train==[360.96634=360.74246 + 0.22335], recall=[0.66093, 0.66093], precision=[0.06609, 0.06609], hit=[0.66093, 0.66093], ndcg=[0.38344, 0.38344]
INFO:root:Epoch 559 [140.2s + 37.6s]: train==[245.42297=245.14502 + 0.27796], recall=[0.74719, 0.74719], precision=[0.07472, 0.07472], hit=[0.74719, 0.74719], ndcg=[0.44174, 0.44174]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1929 [39.3s + 38.1s]: train==[692.88525=692.86963 + 0.01573], recall=[0.22682, 0.22682], precision=[0.02268, 0.02268], hit=[0.22682, 0.22682], ndcg=[0.10202, 0.10202]
INFO:root:Epoch 1939 [39.1s + 37.1s]: train==[361.04031=360.81647 + 0.22349], recall=[0.66225, 0.66225], precision=[0.06623, 0.06623], hit=[0.66225, 0.66225], ndcg=[0.38448, 0.38448]
INFO:root:Epoch 979 [72.8s + 45.6s]: train==[262.84094=262.69016 + 0.15081], recall=[0.73295, 0.73295], precision=[0.07329, 0.07329], hit=[0.73295, 0.73295], ndcg=[0.42536, 0.42536]
INFO:root:Epoch 1939 [40.5s + 36.8s]: train==[692.87671=692.86115 + 0.01573], recall=[0.22831, 0.22831], precision=[0.02283, 0.02283], hit=[0.22831, 0.22831], ndcg=[0.10279, 0.10279]
INFO:root:Epoch 1949 [41.4s + 39.9s]: train==[359.50232=359.27774 + 0.22488], recall=[0.65861, 0.65861], precision=[0.06586, 0.06586], hit=[0.65861, 0.65861], ndcg=[0.38448, 0.38448]
INFO:root:Epoch 1949 [43.5s + 40.3s]: train==[692.86761=692.85144 + 0.01573], recall=[0.22732, 0.22732], precision=[0.02273, 0.02273], hit=[0.22732, 0.22732], ndcg=[0.10277, 0.10277]
INFO:root:Epoch 1959 [39.5s + 37.7s]: train==[360.42972=360.20392 + 0.22579], recall=[0.66242, 0.66242], precision=[0.06624, 0.06624], hit=[0.66242, 0.66242], ndcg=[0.38568, 0.38568]
INFO:root:Epoch 569 [126.5s + 39.0s]: train==[239.60658=239.32449 + 0.28219], recall=[0.74785, 0.74785], precision=[0.07478, 0.07478], hit=[0.74785, 0.74785], ndcg=[0.44188, 0.44188]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 989 [72.8s + 47.4s]: train==[261.85254=261.70029 + 0.15241], recall=[0.73295, 0.73295], precision=[0.07329, 0.07329], hit=[0.73295, 0.73295], ndcg=[0.42680, 0.42680]
INFO:root:Epoch 1959 [42.6s + 36.5s]: train==[692.85950=692.84436 + 0.01574], recall=[0.22980, 0.22980], precision=[0.02298, 0.02298], hit=[0.22980, 0.22980], ndcg=[0.10349, 0.10349]
INFO:root:Epoch 1969 [38.1s + 37.2s]: train==[358.40604=358.17963 + 0.22609], recall=[0.65977, 0.65977], precision=[0.06598, 0.06598], hit=[0.65977, 0.65977], ndcg=[0.38052, 0.38052]
INFO:root:Epoch 1969 [40.7s + 37.4s]: train==[692.86877=692.85315 + 0.01574], recall=[0.22980, 0.22980], precision=[0.02298, 0.02298], hit=[0.22980, 0.22980], ndcg=[0.10328, 0.10328]
INFO:root:Epoch 1979 [38.6s + 37.1s]: train==[357.47574=357.24841 + 0.22718], recall=[0.66209, 0.66209], precision=[0.06621, 0.06621], hit=[0.66209, 0.66209], ndcg=[0.38443, 0.38443]
INFO:root:Epoch 999 [81.0s + 48.7s]: train==[260.73035=260.57620 + 0.15427], recall=[0.73493, 0.73493], precision=[0.07349, 0.07349], hit=[0.73493, 0.73493], ndcg=[0.42564, 0.42564]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1979 [41.8s + 37.2s]: train==[692.85065=692.83459 + 0.01574], recall=[0.22914, 0.22914], precision=[0.02291, 0.02291], hit=[0.22914, 0.22914], ndcg=[0.10285, 0.10285]
INFO:root:Epoch 1989 [40.4s + 36.9s]: train==[356.69745=356.47006 + 0.22734], recall=[0.66175, 0.66175], precision=[0.06618, 0.06618], hit=[0.66175, 0.66175], ndcg=[0.38114, 0.38114]
INFO:root:Epoch 1989 [38.6s + 37.5s]: train==[692.83978=692.82434 + 0.01574], recall=[0.22897, 0.22897], precision=[0.02290, 0.02290], hit=[0.22897, 0.22897], ndcg=[0.10403, 0.10403]
INFO:root:Epoch 579 [124.5s + 37.5s]: train==[241.20009=240.91260 + 0.28763], recall=[0.74636, 0.74636], precision=[0.07464, 0.07464], hit=[0.74636, 0.74636], ndcg=[0.44018, 0.44018]
INFO:root:Epoch 1999 [38.0s + 38.5s]: train==[355.14444=354.91638 + 0.22772], recall=[0.66275, 0.66275], precision=[0.06627, 0.06627], hit=[0.66275, 0.66275], ndcg=[0.38355, 0.38355]
INFO:root:Best Iter=[179]@[70223.9]	recall=[0.66821], precision=[0.06682], hit=[0.66821], ndcg=[0.38877]
INFO:root:Epoch 1009 [64.7s + 42.3s]: train==[259.20688=259.05072 + 0.15603], recall=[0.73427, 0.73427], precision=[0.07343, 0.07343], hit=[0.73427, 0.73427], ndcg=[0.42911, 0.42911]
INFO:root:Epoch 1999 [34.8s + 34.8s]: train==[692.85651=692.84052 + 0.01574], recall=[0.22599, 0.22599], precision=[0.02260, 0.02260], hit=[0.22599, 0.22599], ndcg=[0.10312, 0.10312]
INFO:root:Best Iter=[189]@[70389.4]	recall=[0.23179], precision=[0.02318], hit=[0.23179], ndcg=[0.10323]
INFO:root:Epoch 1019 [60.9s + 37.6s]: train==[259.95203=259.79443 + 0.15771], recall=[0.73924, 0.73924], precision=[0.07392, 0.07392], hit=[0.73924, 0.73924], ndcg=[0.42916, 0.42916]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 589 [102.1s + 29.9s]: train==[240.00525=239.71342 + 0.29201], recall=[0.75265, 0.75265], precision=[0.07526, 0.07526], hit=[0.75265, 0.75265], ndcg=[0.44340, 0.44340]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1029 [61.0s + 37.5s]: train==[254.62167=254.46204 + 0.15944], recall=[0.73924, 0.73924], precision=[0.07392, 0.07392], hit=[0.73924, 0.73924], ndcg=[0.43053, 0.43053]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1039 [59.9s + 40.4s]: train==[252.27499=252.11388 + 0.16130], recall=[0.74156, 0.74156], precision=[0.07416, 0.07416], hit=[0.74156, 0.74156], ndcg=[0.42865, 0.42865]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 599 [106.3s + 30.4s]: train==[235.58482=235.28778 + 0.29699], recall=[0.75050, 0.75050], precision=[0.07505, 0.07505], hit=[0.75050, 0.75050], ndcg=[0.44561, 0.44561]
INFO:root:Epoch 1049 [62.6s + 39.2s]: train==[253.64603=253.48268 + 0.16334], recall=[0.73858, 0.73858], precision=[0.07386, 0.07386], hit=[0.73858, 0.73858], ndcg=[0.43188, 0.43188]
INFO:root:Epoch 609 [101.6s + 30.8s]: train==[235.14185=234.84074 + 0.30116], recall=[0.75613, 0.75613], precision=[0.07561, 0.07561], hit=[0.75613, 0.75613], ndcg=[0.44698, 0.44698]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1059 [59.8s + 38.8s]: train==[251.09726=250.93246 + 0.16488], recall=[0.74172, 0.74172], precision=[0.07417, 0.07417], hit=[0.74172, 0.74172], ndcg=[0.43309, 0.43309]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1069 [60.5s + 38.0s]: train==[250.38489=250.21829 + 0.16644], recall=[0.74222, 0.74222], precision=[0.07422, 0.07422], hit=[0.74222, 0.74222], ndcg=[0.43631, 0.43631]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 619 [104.8s + 29.2s]: train==[228.88527=228.57909 + 0.30622], recall=[0.74834, 0.74834], precision=[0.07483, 0.07483], hit=[0.74834, 0.74834], ndcg=[0.44569, 0.44569]
INFO:root:Epoch 1079 [59.0s + 40.0s]: train==[250.71703=250.54871 + 0.16836], recall=[0.74139, 0.74139], precision=[0.07414, 0.07414], hit=[0.74139, 0.74139], ndcg=[0.43467, 0.43467]
INFO:root:Epoch 1089 [60.2s + 39.0s]: train==[250.47543=250.30518 + 0.17018], recall=[0.74288, 0.74288], precision=[0.07429, 0.07429], hit=[0.74288, 0.74288], ndcg=[0.43360, 0.43360]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 629 [105.1s + 31.6s]: train==[228.94371=228.63257 + 0.31111], recall=[0.75811, 0.75811], precision=[0.07581, 0.07581], hit=[0.75811, 0.75811], ndcg=[0.45192, 0.45192]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1099 [60.3s + 38.1s]: train==[243.31378=243.14197 + 0.17189], recall=[0.74437, 0.74437], precision=[0.07444, 0.07444], hit=[0.74437, 0.74437], ndcg=[0.43559, 0.43559]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1109 [59.5s + 40.6s]: train==[243.75781=243.58382 + 0.17376], recall=[0.74702, 0.74702], precision=[0.07470, 0.07470], hit=[0.74702, 0.74702], ndcg=[0.43667, 0.43667]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 639 [108.0s + 32.6s]: train==[227.89113=227.57564 + 0.31560], recall=[0.75795, 0.75795], precision=[0.07579, 0.07579], hit=[0.75795, 0.75795], ndcg=[0.44991, 0.44991]
INFO:root:Epoch 1119 [58.8s + 39.6s]: train==[242.86398=242.68881 + 0.17530], recall=[0.75083, 0.75083], precision=[0.07508, 0.07508], hit=[0.75083, 0.75083], ndcg=[0.43829, 0.43829]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 649 [102.6s + 29.7s]: train==[224.55867=224.23851 + 0.32003], recall=[0.75811, 0.75811], precision=[0.07581, 0.07581], hit=[0.75811, 0.75811], ndcg=[0.45189, 0.45189]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1129 [59.7s + 39.5s]: train==[242.75085=242.57304 + 0.17755], recall=[0.75281, 0.75281], precision=[0.07528, 0.07528], hit=[0.75281, 0.75281], ndcg=[0.43836, 0.43836]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1139 [62.5s + 40.7s]: train==[243.46214=243.28304 + 0.17896], recall=[0.74752, 0.74752], precision=[0.07475, 0.07475], hit=[0.74752, 0.74752], ndcg=[0.43871, 0.43871]
INFO:root:Epoch 659 [101.1s + 30.9s]: train==[222.65741=222.33292 + 0.32478], recall=[0.75844, 0.75844], precision=[0.07584, 0.07584], hit=[0.75844, 0.75844], ndcg=[0.45385, 0.45385]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1149 [59.9s + 40.2s]: train==[239.47235=239.29086 + 0.18128], recall=[0.74884, 0.74884], precision=[0.07488, 0.07488], hit=[0.74884, 0.74884], ndcg=[0.43937, 0.43937]
INFO:root:Epoch 1159 [62.0s + 39.2s]: train==[238.20062=238.01784 + 0.18277], recall=[0.74983, 0.74983], precision=[0.07498, 0.07498], hit=[0.74983, 0.74983], ndcg=[0.43836, 0.43836]
INFO:root:Epoch 669 [100.8s + 31.7s]: train==[219.56615=219.23663 + 0.32948], recall=[0.75894, 0.75894], precision=[0.07589, 0.07589], hit=[0.75894, 0.75894], ndcg=[0.45292, 0.45292]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1169 [59.6s + 39.9s]: train==[236.64294=236.45839 + 0.18451], recall=[0.74967, 0.74967], precision=[0.07497, 0.07497], hit=[0.74967, 0.74967], ndcg=[0.43967, 0.43967]
INFO:root:Epoch 1179 [59.9s + 40.1s]: train==[235.84868=235.66260 + 0.18633], recall=[0.75778, 0.75778], precision=[0.07578, 0.07578], hit=[0.75778, 0.75778], ndcg=[0.44223, 0.44223]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 679 [103.6s + 34.4s]: train==[220.70972=220.37637 + 0.33376], recall=[0.76606, 0.76606], precision=[0.07661, 0.07661], hit=[0.76606, 0.76606], ndcg=[0.45716, 0.45716]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1189 [61.4s + 39.7s]: train==[235.47806=235.28999 + 0.18846], recall=[0.75613, 0.75613], precision=[0.07561, 0.07561], hit=[0.75613, 0.75613], ndcg=[0.44398, 0.44398]
INFO:root:Epoch 689 [100.2s + 30.9s]: train==[216.97363=216.63466 + 0.33890], recall=[0.76589, 0.76589], precision=[0.07659, 0.07659], hit=[0.76589, 0.76589], ndcg=[0.45688, 0.45688]
INFO:root:Epoch 1199 [60.5s + 38.8s]: train==[234.88872=234.69879 + 0.18996], recall=[0.75993, 0.75993], precision=[0.07599, 0.07599], hit=[0.75993, 0.75993], ndcg=[0.44727, 0.44727]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1209 [60.6s + 41.3s]: train==[230.61655=230.42458 + 0.19209], recall=[0.75464, 0.75464], precision=[0.07546, 0.07546], hit=[0.75464, 0.75464], ndcg=[0.44329, 0.44329]
INFO:root:Epoch 699 [103.0s + 32.1s]: train==[214.87953=214.53647 + 0.34316], recall=[0.76507, 0.76507], precision=[0.07651, 0.07651], hit=[0.76507, 0.76507], ndcg=[0.45968, 0.45968]
INFO:root:Epoch 1219 [59.9s + 39.2s]: train==[232.90686=232.71361 + 0.19323], recall=[0.75397, 0.75397], precision=[0.07540, 0.07540], hit=[0.75397, 0.75397], ndcg=[0.44765, 0.44765]
INFO:root:Epoch 1229 [58.9s + 39.3s]: train==[232.72649=232.53070 + 0.19601], recall=[0.75679, 0.75679], precision=[0.07568, 0.07568], hit=[0.75679, 0.75679], ndcg=[0.44623, 0.44623]
INFO:root:Epoch 709 [101.0s + 30.4s]: train==[211.49872=211.15085 + 0.34775], recall=[0.76209, 0.76209], precision=[0.07621, 0.07621], hit=[0.76209, 0.76209], ndcg=[0.45758, 0.45758]
INFO:root:Epoch 1239 [63.6s + 41.0s]: train==[230.03558=229.83798 + 0.19741], recall=[0.76093, 0.76093], precision=[0.07609, 0.07609], hit=[0.76093, 0.76093], ndcg=[0.44997, 0.44997]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1249 [59.4s + 37.2s]: train==[228.73460=228.53529 + 0.19925], recall=[0.76159, 0.76159], precision=[0.07616, 0.07616], hit=[0.76159, 0.76159], ndcg=[0.44525, 0.44525]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 719 [104.6s + 30.2s]: train==[210.84488=210.49345 + 0.35130], recall=[0.76854, 0.76854], precision=[0.07685, 0.07685], hit=[0.76854, 0.76854], ndcg=[0.46127, 0.46127]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1259 [64.5s + 42.2s]: train==[229.19843=228.99785 + 0.20067], recall=[0.76573, 0.76573], precision=[0.07657, 0.07657], hit=[0.76573, 0.76573], ndcg=[0.45193, 0.45193]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 729 [133.9s + 36.7s]: train==[207.63550=207.27917 + 0.35637], recall=[0.76374, 0.76374], precision=[0.07637, 0.07637], hit=[0.76374, 0.76374], ndcg=[0.45948, 0.45948]
INFO:root:Epoch 1269 [74.0s + 45.6s]: train==[227.82498=227.62192 + 0.20303], recall=[0.76424, 0.76424], precision=[0.07642, 0.07642], hit=[0.76424, 0.76424], ndcg=[0.44960, 0.44960]
INFO:root:Epoch 1279 [73.5s + 45.6s]: train==[223.66446=223.45952 + 0.20487], recall=[0.76192, 0.76192], precision=[0.07619, 0.07619], hit=[0.76192, 0.76192], ndcg=[0.45012, 0.45012]
INFO:root:Epoch 739 [126.7s + 37.6s]: train==[207.00041=206.63963 + 0.36082], recall=[0.77252, 0.77252], precision=[0.07725, 0.07725], hit=[0.77252, 0.77252], ndcg=[0.46211, 0.46211]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1289 [70.1s + 44.6s]: train==[221.76703=221.56038 + 0.20666], recall=[0.76291, 0.76291], precision=[0.07629, 0.07629], hit=[0.76291, 0.76291], ndcg=[0.44792, 0.44792]
INFO:root:Epoch 1299 [72.4s + 44.0s]: train==[223.60187=223.39302 + 0.20875], recall=[0.76308, 0.76308], precision=[0.07631, 0.07631], hit=[0.76308, 0.76308], ndcg=[0.45256, 0.45256]
INFO:root:Epoch 749 [121.9s + 38.0s]: train==[203.60313=203.23840 + 0.36493], recall=[0.77334, 0.77334], precision=[0.07733, 0.07733], hit=[0.77334, 0.77334], ndcg=[0.46406, 0.46406]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1309 [75.9s + 45.9s]: train==[219.78035=219.56982 + 0.21049], recall=[0.76838, 0.76838], precision=[0.07684, 0.07684], hit=[0.76838, 0.76838], ndcg=[0.45168, 0.45168]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1319 [71.4s + 45.5s]: train==[222.28413=222.07172 + 0.21248], recall=[0.76424, 0.76424], precision=[0.07642, 0.07642], hit=[0.76424, 0.76424], ndcg=[0.44990, 0.44990]
INFO:root:Epoch 759 [123.5s + 35.6s]: train==[200.43527=200.06589 + 0.36937], recall=[0.77070, 0.77070], precision=[0.07707, 0.07707], hit=[0.77070, 0.77070], ndcg=[0.46560, 0.46560]
INFO:root:Epoch 1329 [72.6s + 46.5s]: train==[221.81056=221.59671 + 0.21431], recall=[0.76291, 0.76291], precision=[0.07629, 0.07629], hit=[0.76291, 0.76291], ndcg=[0.44917, 0.44917]
INFO:root:Epoch 1339 [74.5s + 47.5s]: train==[218.05298=217.83728 + 0.21578], recall=[0.76656, 0.76656], precision=[0.07666, 0.07666], hit=[0.76656, 0.76656], ndcg=[0.45358, 0.45358]
INFO:root:Epoch 769 [130.2s + 38.7s]: train==[203.55763=203.18381 + 0.37387], recall=[0.77566, 0.77566], precision=[0.07757, 0.07757], hit=[0.77566, 0.77566], ndcg=[0.46362, 0.46362]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1349 [71.7s + 45.2s]: train==[219.88159=219.66360 + 0.21792], recall=[0.76904, 0.76904], precision=[0.07690, 0.07690], hit=[0.76904, 0.76904], ndcg=[0.45590, 0.45590]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 779 [123.9s + 38.3s]: train==[199.76622=199.38864 + 0.37743], recall=[0.77517, 0.77517], precision=[0.07752, 0.07752], hit=[0.77517, 0.77517], ndcg=[0.46629, 0.46629]
INFO:root:Epoch 1359 [69.4s + 44.5s]: train==[215.05502=214.83522 + 0.21966], recall=[0.76854, 0.76854], precision=[0.07685, 0.07685], hit=[0.76854, 0.76854], ndcg=[0.45546, 0.45546]
INFO:root:Epoch 1369 [73.9s + 46.1s]: train==[217.49756=217.27655 + 0.22118], recall=[0.76921, 0.76921], precision=[0.07692, 0.07692], hit=[0.76921, 0.76921], ndcg=[0.45478, 0.45478]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 789 [122.6s + 37.6s]: train==[198.13811=197.75635 + 0.38180], recall=[0.77450, 0.77450], precision=[0.07745, 0.07745], hit=[0.77450, 0.77450], ndcg=[0.46649, 0.46649]
INFO:root:Epoch 1379 [69.5s + 45.0s]: train==[215.12482=214.90146 + 0.22310], recall=[0.76887, 0.76887], precision=[0.07689, 0.07689], hit=[0.76887, 0.76887], ndcg=[0.45195, 0.45195]
INFO:root:Epoch 1389 [70.1s + 45.6s]: train==[214.11719=213.89157 + 0.22537], recall=[0.77649, 0.77649], precision=[0.07765, 0.07765], hit=[0.77649, 0.77649], ndcg=[0.45794, 0.45794]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 799 [123.8s + 37.0s]: train==[197.36957=196.98373 + 0.38583], recall=[0.77318, 0.77318], precision=[0.07732, 0.07732], hit=[0.77318, 0.77318], ndcg=[0.46702, 0.46702]
INFO:root:Epoch 1399 [75.4s + 43.9s]: train==[214.89282=214.66551 + 0.22723], recall=[0.77815, 0.77815], precision=[0.07781, 0.07781], hit=[0.77815, 0.77815], ndcg=[0.45824, 0.45824]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1409 [73.3s + 45.2s]: train==[215.81721=215.58813 + 0.22894], recall=[0.77351, 0.77351], precision=[0.07735, 0.07735], hit=[0.77351, 0.77351], ndcg=[0.45545, 0.45545]
INFO:root:Epoch 809 [130.6s + 40.8s]: train==[194.91460=194.52451 + 0.39021], recall=[0.77699, 0.77699], precision=[0.07770, 0.07770], hit=[0.77699, 0.77699], ndcg=[0.46915, 0.46915]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1419 [69.8s + 44.7s]: train==[217.76613=217.53564 + 0.23031], recall=[0.77185, 0.77185], precision=[0.07719, 0.07719], hit=[0.77185, 0.77185], ndcg=[0.45752, 0.45752]
INFO:root:Epoch 1429 [69.6s + 44.8s]: train==[214.68063=214.44833 + 0.23257], recall=[0.77632, 0.77632], precision=[0.07763, 0.07763], hit=[0.77632, 0.77632], ndcg=[0.45944, 0.45944]
INFO:root:Epoch 819 [121.5s + 37.1s]: train==[195.03082=194.63600 + 0.39474], recall=[0.77268, 0.77268], precision=[0.07727, 0.07727], hit=[0.77268, 0.77268], ndcg=[0.46863, 0.46863]
INFO:root:Epoch 1439 [68.7s + 44.9s]: train==[214.00697=213.77232 + 0.23457], recall=[0.77947, 0.77947], precision=[0.07795, 0.07795], hit=[0.77947, 0.77947], ndcg=[0.46038, 0.46038]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 829 [125.3s + 37.7s]: train==[192.02814=191.62964 + 0.39838], recall=[0.77980, 0.77980], precision=[0.07798, 0.07798], hit=[0.77980, 0.77980], ndcg=[0.47087, 0.47087]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1449 [68.7s + 45.7s]: train==[214.46950=214.23354 + 0.23605], recall=[0.77666, 0.77666], precision=[0.07767, 0.07767], hit=[0.77666, 0.77666], ndcg=[0.46090, 0.46090]
INFO:root:Epoch 1459 [66.6s + 45.6s]: train==[211.50188=211.26393 + 0.23799], recall=[0.77964, 0.77964], precision=[0.07796, 0.07796], hit=[0.77964, 0.77964], ndcg=[0.45858, 0.45858]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 839 [122.1s + 36.7s]: train==[191.00018=190.59769 + 0.40271], recall=[0.77781, 0.77781], precision=[0.07778, 0.07778], hit=[0.77781, 0.77781], ndcg=[0.47076, 0.47076]
INFO:root:Epoch 1469 [70.0s + 43.9s]: train==[211.79105=211.55116 + 0.23995], recall=[0.77599, 0.77599], precision=[0.07760, 0.07760], hit=[0.77599, 0.77599], ndcg=[0.46138, 0.46138]
INFO:root:Epoch 1479 [68.8s + 45.6s]: train==[210.24649=210.00470 + 0.24178], recall=[0.77517, 0.77517], precision=[0.07752, 0.07752], hit=[0.77517, 0.77517], ndcg=[0.46173, 0.46173]
INFO:root:Epoch 849 [117.9s + 36.9s]: train==[190.81056=190.40459 + 0.40602], recall=[0.78046, 0.78046], precision=[0.07805, 0.07805], hit=[0.78046, 0.78046], ndcg=[0.47334, 0.47334]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1489 [69.5s + 43.6s]: train==[210.26123=210.01794 + 0.24345], recall=[0.77649, 0.77649], precision=[0.07765, 0.07765], hit=[0.77649, 0.77649], ndcg=[0.46096, 0.46096]
INFO:root:Epoch 1499 [68.5s + 44.1s]: train==[206.65459=206.40933 + 0.24514], recall=[0.78063, 0.78063], precision=[0.07806, 0.07806], hit=[0.78063, 0.78063], ndcg=[0.46426, 0.46426]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 859 [128.9s + 37.1s]: train==[191.03091=190.62025 + 0.41072], recall=[0.77864, 0.77864], precision=[0.07786, 0.07786], hit=[0.77864, 0.77864], ndcg=[0.47188, 0.47188]
INFO:root:Epoch 1509 [69.9s + 44.7s]: train==[208.48409=208.23688 + 0.24730], recall=[0.77649, 0.77649], precision=[0.07765, 0.07765], hit=[0.77649, 0.77649], ndcg=[0.46267, 0.46267]
INFO:root:Epoch 869 [121.8s + 38.3s]: train==[187.29422=186.87994 + 0.41434], recall=[0.78195, 0.78195], precision=[0.07820, 0.07820], hit=[0.78195, 0.78195], ndcg=[0.47541, 0.47541]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1519 [71.9s + 48.0s]: train==[207.49200=207.24315 + 0.24881], recall=[0.78179, 0.78179], precision=[0.07818, 0.07818], hit=[0.78179, 0.78179], ndcg=[0.46427, 0.46427]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1529 [73.4s + 47.8s]: train==[203.81693=203.56642 + 0.25066], recall=[0.77914, 0.77914], precision=[0.07791, 0.07791], hit=[0.77914, 0.77914], ndcg=[0.46465, 0.46465]
INFO:root:Epoch 879 [120.6s + 36.5s]: train==[185.44629=185.02806 + 0.41816], recall=[0.78510, 0.78510], precision=[0.07851, 0.07851], hit=[0.78510, 0.78510], ndcg=[0.47942, 0.47942]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1539 [68.7s + 44.5s]: train==[206.67175=206.41945 + 0.25245], recall=[0.78576, 0.78576], precision=[0.07858, 0.07858], hit=[0.78576, 0.78576], ndcg=[0.46749, 0.46749]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1549 [70.2s + 45.0s]: train==[202.47070=202.21640 + 0.25437], recall=[0.78344, 0.78344], precision=[0.07834, 0.07834], hit=[0.78344, 0.78344], ndcg=[0.46750, 0.46750]
INFO:root:Epoch 889 [124.3s + 36.8s]: train==[183.90034=183.47777 + 0.42251], recall=[0.78841, 0.78841], precision=[0.07884, 0.07884], hit=[0.78841, 0.78841], ndcg=[0.47757, 0.47757]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1559 [70.4s + 45.5s]: train==[202.65863=202.40245 + 0.25630], recall=[0.78427, 0.78427], precision=[0.07843, 0.07843], hit=[0.78427, 0.78427], ndcg=[0.46576, 0.46576]
INFO:root:Epoch 1569 [71.9s + 45.6s]: train==[202.03383=201.77623 + 0.25771], recall=[0.78079, 0.78079], precision=[0.07808, 0.07808], hit=[0.78079, 0.78079], ndcg=[0.46555, 0.46555]
INFO:root:Epoch 899 [117.3s + 38.1s]: train==[185.57001=185.14432 + 0.42569], recall=[0.78560, 0.78560], precision=[0.07856, 0.07856], hit=[0.78560, 0.78560], ndcg=[0.47851, 0.47851]
INFO:root:Epoch 1579 [69.8s + 45.8s]: train==[203.37996=203.12003 + 0.26018], recall=[0.78642, 0.78642], precision=[0.07864, 0.07864], hit=[0.78642, 0.78642], ndcg=[0.46750, 0.46750]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1589 [69.3s + 46.4s]: train==[199.54494=199.28337 + 0.26146], recall=[0.78295, 0.78295], precision=[0.07829, 0.07829], hit=[0.78295, 0.78295], ndcg=[0.47148, 0.47148]
INFO:root:Epoch 909 [123.2s + 37.7s]: train==[180.88763=180.45761 + 0.42990], recall=[0.78493, 0.78493], precision=[0.07849, 0.07849], hit=[0.78493, 0.78493], ndcg=[0.47693, 0.47693]
INFO:root:Epoch 1599 [69.6s + 45.0s]: train==[201.27345=201.00996 + 0.26363], recall=[0.78212, 0.78212], precision=[0.07821, 0.07821], hit=[0.78212, 0.78212], ndcg=[0.46835, 0.46835]
INFO:root:Epoch 919 [120.0s + 36.8s]: train==[182.70894=182.27466 + 0.43413], recall=[0.79139, 0.79139], precision=[0.07914, 0.07914], hit=[0.79139, 0.79139], ndcg=[0.48098, 0.48098]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1609 [70.7s + 45.9s]: train==[197.56013=197.29468 + 0.26529], recall=[0.78560, 0.78560], precision=[0.07856, 0.07856], hit=[0.78560, 0.78560], ndcg=[0.47007, 0.47007]
INFO:root:Epoch 1619 [68.9s + 46.1s]: train==[199.23940=198.97232 + 0.26680], recall=[0.78808, 0.78808], precision=[0.07881, 0.07881], hit=[0.78808, 0.78808], ndcg=[0.47069, 0.47069]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 929 [120.6s + 39.1s]: train==[179.13931=178.70206 + 0.43735], recall=[0.78560, 0.78560], precision=[0.07856, 0.07856], hit=[0.78560, 0.78560], ndcg=[0.47831, 0.47831]
INFO:root:Epoch 1629 [71.1s + 46.1s]: train==[198.54990=198.28053 + 0.26922], recall=[0.78675, 0.78675], precision=[0.07868, 0.07868], hit=[0.78675, 0.78675], ndcg=[0.47332, 0.47332]
INFO:root:Epoch 1639 [69.3s + 46.5s]: train==[195.41335=195.14267 + 0.27061], recall=[0.78162, 0.78162], precision=[0.07816, 0.07816], hit=[0.78162, 0.78162], ndcg=[0.46701, 0.46701]
INFO:root:Epoch 939 [123.6s + 37.4s]: train==[178.98668=178.54535 + 0.44118], recall=[0.78940, 0.78940], precision=[0.07894, 0.07894], hit=[0.78940, 0.78940], ndcg=[0.48183, 0.48183]
INFO:root:Epoch 1649 [68.7s + 45.1s]: train==[194.77724=194.50511 + 0.27215], recall=[0.78692, 0.78692], precision=[0.07869, 0.07869], hit=[0.78692, 0.78692], ndcg=[0.47126, 0.47126]
INFO:root:Epoch 1659 [67.9s + 45.4s]: train==[194.47440=194.19998 + 0.27435], recall=[0.78460, 0.78460], precision=[0.07846, 0.07846], hit=[0.78460, 0.78460], ndcg=[0.47347, 0.47347]
INFO:root:Epoch 949 [122.3s + 37.8s]: train==[176.80376=176.35829 + 0.44551], recall=[0.78940, 0.78940], precision=[0.07894, 0.07894], hit=[0.78940, 0.78940], ndcg=[0.48711, 0.48711]
INFO:root:Epoch 1669 [71.8s + 45.8s]: train==[192.18181=191.90553 + 0.27629], recall=[0.78311, 0.78311], precision=[0.07831, 0.07831], hit=[0.78311, 0.78311], ndcg=[0.47184, 0.47184]
INFO:root:Epoch 1679 [68.9s + 44.1s]: train==[193.88672=193.60909 + 0.27740], recall=[0.78477, 0.78477], precision=[0.07848, 0.07848], hit=[0.78477, 0.78477], ndcg=[0.47151, 0.47151]
INFO:root:Epoch 959 [123.9s + 37.0s]: train==[175.73749=175.28838 + 0.44912], recall=[0.79354, 0.79354], precision=[0.07935, 0.07935], hit=[0.79354, 0.79354], ndcg=[0.48419, 0.48419]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1689 [69.1s + 41.4s]: train==[191.71146=191.43198 + 0.27939], recall=[0.79007, 0.79007], precision=[0.07901, 0.07901], hit=[0.79007, 0.79007], ndcg=[0.47820, 0.47820]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 969 [113.7s + 33.8s]: train==[175.42900=174.97656 + 0.45235], recall=[0.78858, 0.78858], precision=[0.07886, 0.07886], hit=[0.78858, 0.78858], ndcg=[0.48298, 0.48298]
INFO:root:Epoch 1699 [65.1s + 41.9s]: train==[192.33911=192.05823 + 0.28087], recall=[0.78692, 0.78692], precision=[0.07869, 0.07869], hit=[0.78692, 0.78692], ndcg=[0.47279, 0.47279]
INFO:root:Epoch 1709 [63.9s + 42.2s]: train==[190.00964=189.72719 + 0.28273], recall=[0.78576, 0.78576], precision=[0.07858, 0.07858], hit=[0.78576, 0.78576], ndcg=[0.47455, 0.47455]
INFO:root:Epoch 979 [112.0s + 34.5s]: train==[173.99611=173.54082 + 0.45527], recall=[0.79189, 0.79189], precision=[0.07919, 0.07919], hit=[0.79189, 0.79189], ndcg=[0.48609, 0.48609]
INFO:root:Epoch 1719 [64.2s + 44.3s]: train==[188.84006=188.55544 + 0.28457], recall=[0.78841, 0.78841], precision=[0.07884, 0.07884], hit=[0.78841, 0.78841], ndcg=[0.47821, 0.47821]
INFO:root:Epoch 1729 [65.4s + 43.9s]: train==[191.57008=191.28397 + 0.28611], recall=[0.79172, 0.79172], precision=[0.07917, 0.07917], hit=[0.79172, 0.79172], ndcg=[0.47991, 0.47991]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 989 [112.7s + 34.9s]: train==[173.06241=172.60339 + 0.45904], recall=[0.79354, 0.79354], precision=[0.07935, 0.07935], hit=[0.79354, 0.79354], ndcg=[0.48748, 0.48748]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1739 [63.3s + 42.3s]: train==[187.58246=187.29399 + 0.28822], recall=[0.78874, 0.78874], precision=[0.07887, 0.07887], hit=[0.78874, 0.78874], ndcg=[0.47756, 0.47756]
INFO:root:Epoch 1749 [62.8s + 42.4s]: train==[187.37317=187.08315 + 0.28982], recall=[0.78775, 0.78775], precision=[0.07877, 0.07877], hit=[0.78775, 0.78775], ndcg=[0.47989, 0.47989]
INFO:root:Epoch 999 [114.1s + 35.0s]: train==[171.17976=170.71700 + 0.46276], recall=[0.79238, 0.79238], precision=[0.07924, 0.07924], hit=[0.79238, 0.79238], ndcg=[0.48517, 0.48517]
INFO:root:Epoch 1759 [62.7s + 44.7s]: train==[184.45485=184.16304 + 0.29200], recall=[0.79354, 0.79354], precision=[0.07935, 0.07935], hit=[0.79354, 0.79354], ndcg=[0.47677, 0.47677]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1009 [113.4s + 33.1s]: train==[170.13414=169.66728 + 0.46676], recall=[0.79089, 0.79089], precision=[0.07909, 0.07909], hit=[0.79089, 0.79089], ndcg=[0.48304, 0.48304]
INFO:root:Epoch 1769 [64.2s + 43.4s]: train==[184.91599=184.62260 + 0.29342], recall=[0.79106, 0.79106], precision=[0.07911, 0.07911], hit=[0.79106, 0.79106], ndcg=[0.47970, 0.47970]
INFO:root:Epoch 1779 [64.0s + 42.3s]: train==[182.83405=182.53937 + 0.29472], recall=[0.79139, 0.79139], precision=[0.07914, 0.07914], hit=[0.79139, 0.79139], ndcg=[0.47578, 0.47578]
INFO:root:Epoch 1019 [112.2s + 33.0s]: train==[172.57033=172.09952 + 0.47096], recall=[0.79636, 0.79636], precision=[0.07964, 0.07964], hit=[0.79636, 0.79636], ndcg=[0.49022, 0.49022]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1789 [62.5s + 42.4s]: train==[182.51367=182.21735 + 0.29653], recall=[0.79205, 0.79205], precision=[0.07921, 0.07921], hit=[0.79205, 0.79205], ndcg=[0.47855, 0.47855]
INFO:root:Epoch 1799 [62.7s + 42.6s]: train==[183.00308=182.70461 + 0.29856], recall=[0.79189, 0.79189], precision=[0.07919, 0.07919], hit=[0.79189, 0.79189], ndcg=[0.48032, 0.48032]
INFO:root:Epoch 1029 [113.1s + 35.3s]: train==[169.18655=168.71233 + 0.47410], recall=[0.79172, 0.79172], precision=[0.07917, 0.07917], hit=[0.79172, 0.79172], ndcg=[0.48789, 0.48789]
INFO:root:Epoch 1809 [64.0s + 42.5s]: train==[184.61990=184.32014 + 0.29986], recall=[0.78725, 0.78725], precision=[0.07873, 0.07873], hit=[0.78725, 0.78725], ndcg=[0.47532, 0.47532]
INFO:root:Epoch 1819 [63.9s + 42.8s]: train==[181.49792=181.19604 + 0.30179], recall=[0.79139, 0.79139], precision=[0.07914, 0.07914], hit=[0.79139, 0.79139], ndcg=[0.48075, 0.48075]
INFO:root:Epoch 1039 [109.4s + 33.1s]: train==[166.96053=166.48254 + 0.47796], recall=[0.79454, 0.79454], precision=[0.07945, 0.07945], hit=[0.79454, 0.79454], ndcg=[0.48505, 0.48505]
INFO:root:Epoch 1829 [64.8s + 43.2s]: train==[180.48964=180.18614 + 0.30344], recall=[0.79669, 0.79669], precision=[0.07967, 0.07967], hit=[0.79669, 0.79669], ndcg=[0.48082, 0.48082]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1049 [109.4s + 32.7s]: train==[165.99167=165.51042 + 0.48082], recall=[0.79421, 0.79421], precision=[0.07942, 0.07942], hit=[0.79421, 0.79421], ndcg=[0.48994, 0.48994]
INFO:root:Epoch 1839 [63.5s + 42.9s]: train==[180.90294=180.59811 + 0.30499], recall=[0.79487, 0.79487], precision=[0.07949, 0.07949], hit=[0.79487, 0.79487], ndcg=[0.47947, 0.47947]
INFO:root:Epoch 1849 [62.9s + 43.4s]: train==[179.33237=179.02541 + 0.30685], recall=[0.79719, 0.79719], precision=[0.07972, 0.07972], hit=[0.79719, 0.79719], ndcg=[0.48109, 0.48109]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1059 [109.6s + 33.1s]: train==[166.70769=166.22354 + 0.48419], recall=[0.79868, 0.79868], precision=[0.07987, 0.07987], hit=[0.79868, 0.79868], ndcg=[0.49169, 0.49169]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1859 [62.6s + 42.0s]: train==[177.61511=177.30682 + 0.30819], recall=[0.79801, 0.79801], precision=[0.07980, 0.07980], hit=[0.79801, 0.79801], ndcg=[0.48555, 0.48555]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1869 [63.7s + 43.0s]: train==[179.04338=178.73366 + 0.30968], recall=[0.79619, 0.79619], precision=[0.07962, 0.07962], hit=[0.79619, 0.79619], ndcg=[0.48530, 0.48530]
INFO:root:Epoch 1069 [110.9s + 32.6s]: train==[165.18425=164.69568 + 0.48848], recall=[0.80116, 0.80116], precision=[0.08012, 0.08012], hit=[0.80116, 0.80116], ndcg=[0.49348, 0.49348]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1879 [64.2s + 40.5s]: train==[177.99565=177.68394 + 0.31191], recall=[0.79570, 0.79570], precision=[0.07957, 0.07957], hit=[0.79570, 0.79570], ndcg=[0.48110, 0.48110]
INFO:root:Epoch 1889 [62.1s + 41.6s]: train==[178.21060=177.89702 + 0.31361], recall=[0.79073, 0.79073], precision=[0.07907, 0.07907], hit=[0.79073, 0.79073], ndcg=[0.47873, 0.47873]
INFO:root:Epoch 1079 [115.2s + 33.8s]: train==[167.13675=166.64482 + 0.49197], recall=[0.79719, 0.79719], precision=[0.07972, 0.07972], hit=[0.79719, 0.79719], ndcg=[0.49246, 0.49246]
INFO:root:Epoch 1899 [65.2s + 42.9s]: train==[173.63208=173.31683 + 0.31532], recall=[0.79685, 0.79685], precision=[0.07969, 0.07969], hit=[0.79685, 0.79685], ndcg=[0.48502, 0.48502]
INFO:root:Epoch 1089 [112.8s + 33.5s]: train==[160.66357=160.16832 + 0.49525], recall=[0.79834, 0.79834], precision=[0.07983, 0.07983], hit=[0.79834, 0.79834], ndcg=[0.49176, 0.49176]
INFO:root:Epoch 1909 [65.3s + 43.1s]: train==[174.32196=174.00536 + 0.31659], recall=[0.79868, 0.79868], precision=[0.07987, 0.07987], hit=[0.79868, 0.79868], ndcg=[0.48341, 0.48341]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1919 [65.2s + 43.3s]: train==[174.72415=174.40616 + 0.31806], recall=[0.79288, 0.79288], precision=[0.07929, 0.07929], hit=[0.79288, 0.79288], ndcg=[0.48556, 0.48556]
INFO:root:Epoch 1099 [112.6s + 33.3s]: train==[160.15616=159.65787 + 0.49822], recall=[0.79967, 0.79967], precision=[0.07997, 0.07997], hit=[0.79967, 0.79967], ndcg=[0.49300, 0.49300]
INFO:root:Epoch 1929 [66.2s + 43.1s]: train==[174.74547=174.42450 + 0.32083], recall=[0.79636, 0.79636], precision=[0.07964, 0.07964], hit=[0.79636, 0.79636], ndcg=[0.48571, 0.48571]
INFO:root:Epoch 1939 [64.4s + 42.7s]: train==[174.35112=174.02968 + 0.32132], recall=[0.79685, 0.79685], precision=[0.07969, 0.07969], hit=[0.79685, 0.79685], ndcg=[0.48313, 0.48313]
INFO:root:Epoch 1109 [110.9s + 33.8s]: train==[160.20705=159.70547 + 0.50162], recall=[0.80397, 0.80397], precision=[0.08040, 0.08040], hit=[0.80397, 0.80397], ndcg=[0.49736, 0.49736]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1949 [61.8s + 42.1s]: train==[172.70877=172.38493 + 0.32390], recall=[0.79272, 0.79272], precision=[0.07927, 0.07927], hit=[0.79272, 0.79272], ndcg=[0.48546, 0.48546]
INFO:root:Epoch 1959 [62.5s + 42.3s]: train==[172.88351=172.55858 + 0.32500], recall=[0.79884, 0.79884], precision=[0.07988, 0.07988], hit=[0.79884, 0.79884], ndcg=[0.48605, 0.48605]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1119 [111.9s + 32.6s]: train==[160.33611=159.83153 + 0.50461], recall=[0.79983, 0.79983], precision=[0.07998, 0.07998], hit=[0.79983, 0.79983], ndcg=[0.49487, 0.49487]
INFO:root:Epoch 1969 [65.4s + 42.2s]: train==[170.92590=170.59959 + 0.32610], recall=[0.79553, 0.79553], precision=[0.07955, 0.07955], hit=[0.79553, 0.79553], ndcg=[0.48983, 0.48983]
INFO:root:Epoch 1979 [62.2s + 43.0s]: train==[171.91866=171.59044 + 0.32812], recall=[0.79868, 0.79868], precision=[0.07987, 0.07987], hit=[0.79868, 0.79868], ndcg=[0.48716, 0.48716]
INFO:root:Epoch 1129 [110.3s + 33.7s]: train==[162.26762=161.75833 + 0.50927], recall=[0.80629, 0.80629], precision=[0.08063, 0.08063], hit=[0.80629, 0.80629], ndcg=[0.49558, 0.49558]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1989 [63.1s + 42.5s]: train==[170.51859=170.18896 + 0.32976], recall=[0.79636, 0.79636], precision=[0.07964, 0.07964], hit=[0.79636, 0.79636], ndcg=[0.48325, 0.48325]
INFO:root:Epoch 1139 [109.3s + 33.2s]: train==[159.07803=158.56642 + 0.51165], recall=[0.80166, 0.80166], precision=[0.08017, 0.08017], hit=[0.80166, 0.80166], ndcg=[0.49767, 0.49767]
INFO:root:Epoch 1999 [66.9s + 43.0s]: train==[169.90718=169.57634 + 0.33095], recall=[0.79834, 0.79834], precision=[0.07983, 0.07983], hit=[0.79834, 0.79834], ndcg=[0.48829, 0.48829]
INFO:root:Best Iter=[195]@[133731.7]	recall=[0.79884], precision=[0.07988], hit=[0.79884], ndcg=[0.48605]
INFO:root:Epoch 1149 [104.6s + 32.2s]: train==[156.62741=156.11244 + 0.51502], recall=[0.80066, 0.80066], precision=[0.08007, 0.08007], hit=[0.80066, 0.80066], ndcg=[0.49693, 0.49693]
INFO:root:Epoch 1159 [103.9s + 31.1s]: train==[155.70003=155.18126 + 0.51863], recall=[0.80232, 0.80232], precision=[0.08023, 0.08023], hit=[0.80232, 0.80232], ndcg=[0.49678, 0.49678]
INFO:root:Epoch 1169 [104.9s + 31.4s]: train==[156.78896=156.26791 + 0.52099], recall=[0.80679, 0.80679], precision=[0.08068, 0.08068], hit=[0.80679, 0.80679], ndcg=[0.49958, 0.49958]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1179 [102.8s + 32.4s]: train==[156.17719=155.65187 + 0.52521], recall=[0.80066, 0.80066], precision=[0.08007, 0.08007], hit=[0.80066, 0.80066], ndcg=[0.49606, 0.49606]
INFO:root:Epoch 1189 [105.7s + 30.1s]: train==[155.66174=155.13295 + 0.52872], recall=[0.80712, 0.80712], precision=[0.08071, 0.08071], hit=[0.80712, 0.80712], ndcg=[0.50122, 0.50122]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1199 [98.6s + 31.2s]: train==[153.15851=152.62750 + 0.53101], recall=[0.80646, 0.80646], precision=[0.08065, 0.08065], hit=[0.80646, 0.80646], ndcg=[0.50252, 0.50252]
INFO:root:Epoch 1209 [96.0s + 31.1s]: train==[153.49286=152.95824 + 0.53472], recall=[0.80960, 0.80960], precision=[0.08096, 0.08096], hit=[0.80960, 0.80960], ndcg=[0.50087, 0.50087]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1219 [100.0s + 31.3s]: train==[152.15781=151.62013 + 0.53764], recall=[0.80397, 0.80397], precision=[0.08040, 0.08040], hit=[0.80397, 0.80397], ndcg=[0.50083, 0.50083]
INFO:root:Epoch 1229 [97.1s + 29.9s]: train==[151.07228=150.53183 + 0.54055], recall=[0.80281, 0.80281], precision=[0.08028, 0.08028], hit=[0.80281, 0.80281], ndcg=[0.49960, 0.49960]
INFO:root:Epoch 1239 [98.9s + 30.1s]: train==[151.14397=150.59947 + 0.54445], recall=[0.80315, 0.80315], precision=[0.08031, 0.08031], hit=[0.80315, 0.80315], ndcg=[0.50345, 0.50345]
INFO:root:Epoch 1249 [98.0s + 31.1s]: train==[148.14114=147.59401 + 0.54692], recall=[0.80944, 0.80944], precision=[0.08094, 0.08094], hit=[0.80944, 0.80944], ndcg=[0.50600, 0.50600]
INFO:root:Epoch 1259 [99.3s + 31.1s]: train==[149.50406=148.95288 + 0.55116], recall=[0.80695, 0.80695], precision=[0.08070, 0.08070], hit=[0.80695, 0.80695], ndcg=[0.50308, 0.50308]
INFO:root:Epoch 1269 [96.9s + 31.6s]: train==[147.88300=147.32988 + 0.55318], recall=[0.80877, 0.80877], precision=[0.08088, 0.08088], hit=[0.80877, 0.80877], ndcg=[0.50149, 0.50149]
INFO:root:Epoch 1279 [98.4s + 31.8s]: train==[148.06876=147.51242 + 0.55614], recall=[0.80728, 0.80728], precision=[0.08073, 0.08073], hit=[0.80728, 0.80728], ndcg=[0.50434, 0.50434]
INFO:root:Epoch 1289 [98.1s + 31.1s]: train==[147.98965=147.43036 + 0.55927], recall=[0.80745, 0.80745], precision=[0.08075, 0.08075], hit=[0.80745, 0.80745], ndcg=[0.50794, 0.50794]
INFO:root:Epoch 1299 [96.1s + 28.4s]: train==[148.36981=147.80719 + 0.56258], recall=[0.80728, 0.80728], precision=[0.08073, 0.08073], hit=[0.80728, 0.80728], ndcg=[0.50271, 0.50271]
INFO:root:Epoch 1309 [102.1s + 30.8s]: train==[143.15422=142.58803 + 0.56625], recall=[0.81076, 0.81076], precision=[0.08108, 0.08108], hit=[0.81076, 0.81076], ndcg=[0.50837, 0.50837]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1319 [98.1s + 30.7s]: train==[144.88885=144.32039 + 0.56858], recall=[0.81026, 0.81026], precision=[0.08103, 0.08103], hit=[0.81026, 0.81026], ndcg=[0.50709, 0.50709]
INFO:root:Epoch 1329 [98.6s + 32.6s]: train==[143.08926=142.51675 + 0.57253], recall=[0.81457, 0.81457], precision=[0.08146, 0.08146], hit=[0.81457, 0.81457], ndcg=[0.51058, 0.51058]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1339 [100.4s + 30.3s]: train==[142.95312=142.37851 + 0.57464], recall=[0.81209, 0.81209], precision=[0.08121, 0.08121], hit=[0.81209, 0.81209], ndcg=[0.51029, 0.51029]
INFO:root:Epoch 1349 [98.0s + 31.4s]: train==[144.98807=144.40990 + 0.57819], recall=[0.81209, 0.81209], precision=[0.08121, 0.08121], hit=[0.81209, 0.81209], ndcg=[0.51055, 0.51055]
INFO:root:Epoch 1359 [99.8s + 32.1s]: train==[143.13414=142.55356 + 0.58052], recall=[0.80993, 0.80993], precision=[0.08099, 0.08099], hit=[0.80993, 0.80993], ndcg=[0.50874, 0.50874]
INFO:root:Epoch 1369 [96.9s + 31.3s]: train==[140.89081=140.30609 + 0.58486], recall=[0.81457, 0.81457], precision=[0.08146, 0.08146], hit=[0.81457, 0.81457], ndcg=[0.51249, 0.51249]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1379 [97.0s + 30.7s]: train==[140.95779=140.37117 + 0.58659], recall=[0.81424, 0.81424], precision=[0.08142, 0.08142], hit=[0.81424, 0.81424], ndcg=[0.50963, 0.50963]
INFO:root:Epoch 1389 [98.3s + 30.3s]: train==[143.56268=142.97282 + 0.59000], recall=[0.81507, 0.81507], precision=[0.08151, 0.08151], hit=[0.81507, 0.81507], ndcg=[0.51297, 0.51297]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1399 [96.7s + 31.5s]: train==[140.70589=140.11320 + 0.59279], recall=[0.81358, 0.81358], precision=[0.08136, 0.08136], hit=[0.81358, 0.81358], ndcg=[0.51096, 0.51096]
INFO:root:Epoch 1409 [98.5s + 32.6s]: train==[140.12573=139.53053 + 0.59512], recall=[0.81457, 0.81457], precision=[0.08146, 0.08146], hit=[0.81457, 0.81457], ndcg=[0.51103, 0.51103]
INFO:root:Epoch 1419 [97.3s + 28.2s]: train==[138.48372=137.88486 + 0.59880], recall=[0.81076, 0.81076], precision=[0.08108, 0.08108], hit=[0.81076, 0.81076], ndcg=[0.51123, 0.51123]
INFO:root:Epoch 1429 [101.7s + 30.0s]: train==[136.53159=135.93030 + 0.60145], recall=[0.81242, 0.81242], precision=[0.08124, 0.08124], hit=[0.81242, 0.81242], ndcg=[0.51218, 0.51218]
INFO:root:Epoch 1439 [95.0s + 30.9s]: train==[134.91753=134.31306 + 0.60445], recall=[0.81242, 0.81242], precision=[0.08124, 0.08124], hit=[0.81242, 0.81242], ndcg=[0.51551, 0.51551]
INFO:root:Epoch 1449 [98.7s + 29.9s]: train==[136.18144=135.57391 + 0.60750], recall=[0.81772, 0.81772], precision=[0.08177, 0.08177], hit=[0.81772, 0.81772], ndcg=[0.51649, 0.51649]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1459 [99.8s + 32.6s]: train==[135.08578=134.47656 + 0.60917], recall=[0.81424, 0.81424], precision=[0.08142, 0.08142], hit=[0.81424, 0.81424], ndcg=[0.51308, 0.51308]
INFO:root:Epoch 1469 [99.7s + 31.9s]: train==[133.55766=132.94453 + 0.61313], recall=[0.82086, 0.82086], precision=[0.08209, 0.08209], hit=[0.82086, 0.82086], ndcg=[0.51667, 0.51667]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1479 [100.2s + 30.1s]: train==[135.55275=134.93658 + 0.61606], recall=[0.81887, 0.81887], precision=[0.08189, 0.08189], hit=[0.81887, 0.81887], ndcg=[0.51816, 0.51816]
INFO:root:Epoch 1489 [100.3s + 29.8s]: train==[134.24657=133.62827 + 0.61839], recall=[0.81656, 0.81656], precision=[0.08166, 0.08166], hit=[0.81656, 0.81656], ndcg=[0.51723, 0.51723]
INFO:root:Epoch 1499 [98.3s + 32.3s]: train==[133.54271=132.92160 + 0.62112], recall=[0.82202, 0.82202], precision=[0.08220, 0.08220], hit=[0.82202, 0.82202], ndcg=[0.51879, 0.51879]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1509 [99.9s + 32.3s]: train==[134.09344=133.46948 + 0.62378], recall=[0.82036, 0.82036], precision=[0.08204, 0.08204], hit=[0.82036, 0.82036], ndcg=[0.51988, 0.51988]
INFO:root:Epoch 1519 [98.3s + 30.1s]: train==[132.36281=131.73631 + 0.62654], recall=[0.81755, 0.81755], precision=[0.08175, 0.08175], hit=[0.81755, 0.81755], ndcg=[0.51686, 0.51686]
INFO:root:Epoch 1529 [102.0s + 28.3s]: train==[132.98390=132.35416 + 0.62979], recall=[0.81987, 0.81987], precision=[0.08199, 0.08199], hit=[0.81987, 0.81987], ndcg=[0.51774, 0.51774]
INFO:root:Epoch 1539 [98.0s + 28.9s]: train==[132.77684=132.14449 + 0.63238], recall=[0.81954, 0.81954], precision=[0.08195, 0.08195], hit=[0.81954, 0.81954], ndcg=[0.52376, 0.52376]
INFO:root:Epoch 1549 [96.1s + 29.3s]: train==[133.92908=133.29396 + 0.63518], recall=[0.81887, 0.81887], precision=[0.08189, 0.08189], hit=[0.81887, 0.81887], ndcg=[0.52021, 0.52021]
INFO:root:Epoch 1559 [97.2s + 31.1s]: train==[132.64981=132.01221 + 0.63753], recall=[0.81921, 0.81921], precision=[0.08192, 0.08192], hit=[0.81921, 0.81921], ndcg=[0.51953, 0.51953]
INFO:root:Epoch 1569 [96.1s + 31.4s]: train==[130.13097=129.48956 + 0.64140], recall=[0.82285, 0.82285], precision=[0.08228, 0.08228], hit=[0.82285, 0.82285], ndcg=[0.52162, 0.52162]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1579 [95.8s + 30.7s]: train==[130.08382=129.44038 + 0.64342], recall=[0.82036, 0.82036], precision=[0.08204, 0.08204], hit=[0.82036, 0.82036], ndcg=[0.52007, 0.52007]
INFO:root:Epoch 1589 [99.9s + 31.0s]: train==[129.53970=128.89314 + 0.64644], recall=[0.81954, 0.81954], precision=[0.08195, 0.08195], hit=[0.81954, 0.81954], ndcg=[0.52160, 0.52160]
INFO:root:Epoch 1599 [98.9s + 29.8s]: train==[129.60622=128.95711 + 0.64912], recall=[0.82136, 0.82136], precision=[0.08214, 0.08214], hit=[0.82136, 0.82136], ndcg=[0.52043, 0.52043]
INFO:root:Epoch 1609 [98.9s + 28.7s]: train==[128.30824=127.65793 + 0.65040], recall=[0.82252, 0.82252], precision=[0.08225, 0.08225], hit=[0.82252, 0.82252], ndcg=[0.51857, 0.51857]
INFO:root:Epoch 1619 [98.1s + 28.9s]: train==[127.69167=127.03752 + 0.65404], recall=[0.82252, 0.82252], precision=[0.08225, 0.08225], hit=[0.82252, 0.82252], ndcg=[0.52516, 0.52516]
INFO:root:Epoch 1629 [99.5s + 29.8s]: train==[126.92276=126.26646 + 0.65632], recall=[0.82301, 0.82301], precision=[0.08230, 0.08230], hit=[0.82301, 0.82301], ndcg=[0.52525, 0.52525]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1639 [97.3s + 31.8s]: train==[129.77115=129.11151 + 0.65961], recall=[0.82351, 0.82351], precision=[0.08235, 0.08235], hit=[0.82351, 0.82351], ndcg=[0.52500, 0.52500]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1649 [101.1s + 29.3s]: train==[127.53664=126.87459 + 0.66201], recall=[0.82599, 0.82599], precision=[0.08260, 0.08260], hit=[0.82599, 0.82599], ndcg=[0.52306, 0.52306]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1659 [101.9s + 30.2s]: train==[125.48027=124.81447 + 0.66577], recall=[0.82285, 0.82285], precision=[0.08228, 0.08228], hit=[0.82285, 0.82285], ndcg=[0.52555, 0.52555]
INFO:root:Epoch 1669 [94.2s + 29.6s]: train==[125.62087=124.95390 + 0.66697], recall=[0.82401, 0.82401], precision=[0.08240, 0.08240], hit=[0.82401, 0.82401], ndcg=[0.52713, 0.52713]
INFO:root:Epoch 1679 [97.7s + 30.8s]: train==[125.88591=125.21442 + 0.67151], recall=[0.82368, 0.82368], precision=[0.08237, 0.08237], hit=[0.82368, 0.82368], ndcg=[0.52790, 0.52790]
INFO:root:Epoch 1689 [98.5s + 31.1s]: train==[119.99513=119.32198 + 0.67319], recall=[0.82384, 0.82384], precision=[0.08238, 0.08238], hit=[0.82384, 0.82384], ndcg=[0.52849, 0.52849]
INFO:root:Epoch 1699 [98.8s + 32.1s]: train==[124.22191=123.54691 + 0.67491], recall=[0.82401, 0.82401], precision=[0.08240, 0.08240], hit=[0.82401, 0.82401], ndcg=[0.52284, 0.52284]
INFO:root:Epoch 1709 [101.7s + 31.1s]: train==[124.80011=124.12175 + 0.67829], recall=[0.82533, 0.82533], precision=[0.08253, 0.08253], hit=[0.82533, 0.82533], ndcg=[0.52677, 0.52677]
INFO:root:Epoch 1719 [104.5s + 29.5s]: train==[120.67854=119.99690 + 0.68161], recall=[0.82781, 0.82781], precision=[0.08278, 0.08278], hit=[0.82781, 0.82781], ndcg=[0.52827, 0.52827]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1729 [98.5s + 30.2s]: train==[124.34241=123.65886 + 0.68343], recall=[0.82583, 0.82583], precision=[0.08258, 0.08258], hit=[0.82583, 0.82583], ndcg=[0.52385, 0.52385]
INFO:root:Epoch 1739 [98.3s + 31.6s]: train==[120.47365=119.78821 + 0.68544], recall=[0.82434, 0.82434], precision=[0.08243, 0.08243], hit=[0.82434, 0.82434], ndcg=[0.52836, 0.52836]
INFO:root:Epoch 1749 [99.9s + 31.2s]: train==[122.65275=121.96338 + 0.68931], recall=[0.82715, 0.82715], precision=[0.08272, 0.08272], hit=[0.82715, 0.82715], ndcg=[0.52831, 0.52831]
INFO:root:Epoch 1759 [100.0s + 31.9s]: train==[120.38014=119.68847 + 0.69170], recall=[0.83146, 0.83146], precision=[0.08315, 0.08315], hit=[0.83146, 0.83146], ndcg=[0.53289, 0.53289]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1769 [96.5s + 30.0s]: train==[123.44211=122.74783 + 0.69431], recall=[0.82815, 0.82815], precision=[0.08281, 0.08281], hit=[0.82815, 0.82815], ndcg=[0.52894, 0.52894]
INFO:root:Epoch 1779 [98.6s + 31.8s]: train==[120.53893=119.84228 + 0.69648], recall=[0.82483, 0.82483], precision=[0.08248, 0.08248], hit=[0.82483, 0.82483], ndcg=[0.52955, 0.52955]
INFO:root:Epoch 1789 [97.0s + 31.2s]: train==[120.37476=119.67590 + 0.69890], recall=[0.82997, 0.82997], precision=[0.08300, 0.08300], hit=[0.82997, 0.82997], ndcg=[0.53087, 0.53087]
INFO:root:Epoch 1799 [95.9s + 31.0s]: train==[119.81345=119.11180 + 0.70164], recall=[0.82798, 0.82798], precision=[0.08280, 0.08280], hit=[0.82798, 0.82798], ndcg=[0.53173, 0.53173]
INFO:root:Epoch 1809 [99.8s + 29.8s]: train==[122.94926=122.24563 + 0.70364], recall=[0.82732, 0.82732], precision=[0.08273, 0.08273], hit=[0.82732, 0.82732], ndcg=[0.53127, 0.53127]
INFO:root:Epoch 1819 [98.9s + 32.9s]: train==[121.39049=120.68360 + 0.70707], recall=[0.82715, 0.82715], precision=[0.08272, 0.08272], hit=[0.82715, 0.82715], ndcg=[0.52946, 0.52946]
INFO:root:Epoch 1829 [96.2s + 31.0s]: train==[117.83529=117.12639 + 0.70884], recall=[0.82632, 0.82632], precision=[0.08263, 0.08263], hit=[0.82632, 0.82632], ndcg=[0.52802, 0.52802]
INFO:root:Epoch 1839 [98.6s + 31.8s]: train==[116.50648=115.79413 + 0.71244], recall=[0.83046, 0.83046], precision=[0.08305, 0.08305], hit=[0.83046, 0.83046], ndcg=[0.53164, 0.53164]
INFO:root:Epoch 1849 [98.2s + 30.7s]: train==[117.44108=116.72665 + 0.71458], recall=[0.82517, 0.82517], precision=[0.08252, 0.08252], hit=[0.82517, 0.82517], ndcg=[0.52721, 0.52721]
INFO:root:Epoch 1859 [101.9s + 30.5s]: train==[120.70916=119.99308 + 0.71617], recall=[0.83079, 0.83079], precision=[0.08308, 0.08308], hit=[0.83079, 0.83079], ndcg=[0.53043, 0.53043]
INFO:root:Epoch 1869 [99.7s + 31.8s]: train==[117.26909=116.54963 + 0.71941], recall=[0.82666, 0.82666], precision=[0.08267, 0.08267], hit=[0.82666, 0.82666], ndcg=[0.53135, 0.53135]
INFO:root:Epoch 1879 [100.5s + 31.9s]: train==[117.55659=116.83430 + 0.72236], recall=[0.82715, 0.82715], precision=[0.08272, 0.08272], hit=[0.82715, 0.82715], ndcg=[0.53183, 0.53183]
INFO:root:Epoch 1889 [98.2s + 30.4s]: train==[117.12596=116.40245 + 0.72355], recall=[0.82897, 0.82897], precision=[0.08290, 0.08290], hit=[0.82897, 0.82897], ndcg=[0.53193, 0.53193]
INFO:root:Epoch 1899 [100.4s + 31.2s]: train==[116.42245=115.69591 + 0.72663], recall=[0.83245, 0.83245], precision=[0.08325, 0.08325], hit=[0.83245, 0.83245], ndcg=[0.53513, 0.53513]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1909 [98.8s + 30.4s]: train==[116.08074=115.35120 + 0.72959], recall=[0.83262, 0.83262], precision=[0.08326, 0.08326], hit=[0.83262, 0.83262], ndcg=[0.53105, 0.53105]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1919 [99.3s + 31.1s]: train==[115.14056=114.40853 + 0.73203], recall=[0.83262, 0.83262], precision=[0.08326, 0.08326], hit=[0.83262, 0.83262], ndcg=[0.53306, 0.53306]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1929 [97.1s + 32.0s]: train==[116.57951=115.84576 + 0.73374], recall=[0.82831, 0.82831], precision=[0.08283, 0.08283], hit=[0.82831, 0.82831], ndcg=[0.52998, 0.52998]
INFO:root:Epoch 1939 [98.1s + 31.4s]: train==[115.10612=114.36966 + 0.73661], recall=[0.83046, 0.83046], precision=[0.08305, 0.08305], hit=[0.83046, 0.83046], ndcg=[0.53349, 0.53349]
INFO:root:Epoch 1949 [99.2s + 29.6s]: train==[114.54061=113.80199 + 0.73870], recall=[0.83262, 0.83262], precision=[0.08326, 0.08326], hit=[0.83262, 0.83262], ndcg=[0.53544, 0.53544]
INFO:root:save the weights in path: model/two_side_graph_run4_1.pkl
INFO:root:Epoch 1959 [97.6s + 32.1s]: train==[114.80674=114.06464 + 0.74218], recall=[0.82748, 0.82748], precision=[0.08275, 0.08275], hit=[0.82748, 0.82748], ndcg=[0.53497, 0.53497]
INFO:root:Epoch 1969 [97.9s + 30.5s]: train==[115.05270=114.30920 + 0.74356], recall=[0.82997, 0.82997], precision=[0.08300, 0.08300], hit=[0.82997, 0.82997], ndcg=[0.53495, 0.53495]
INFO:root:Epoch 1979 [97.9s + 32.9s]: train==[112.65231=111.90527 + 0.74700], recall=[0.83046, 0.83046], precision=[0.08305, 0.08305], hit=[0.83046, 0.83046], ndcg=[0.53393, 0.53393]
INFO:root:Epoch 1989 [102.0s + 30.0s]: train==[115.28986=114.54079 + 0.74914], recall=[0.83046, 0.83046], precision=[0.08305, 0.08305], hit=[0.83046, 0.83046], ndcg=[0.53248, 0.53248]
INFO:root:Epoch 1999 [99.1s + 31.0s]: train==[112.20594=111.45448 + 0.75149], recall=[0.83063, 0.83063], precision=[0.08306, 0.08306], hit=[0.83063, 0.83063], ndcg=[0.53563, 0.53563]
INFO:root:Best Iter=[190]@[216549.1]	recall=[0.83262], precision=[0.08326], hit=[0.83262], ndcg=[0.53105]
INFO:root:Namespace(Ks='[10]', batch_size=64, data_path='./data/recommendation/', dataset='ml-1m', embed_size=128, epoch=2000, gpu=1, item_density_threshold=0.01, item_threshold=30, layer_size=[128], lmbda=1, local_batch_size=512, local_epoch=30, log_name='run4_1', log_path='/home/qhuaf/graph_pri/logs/', lr=0.0001, mess_dropout=[0.1, 0.1, 0.1], model_name='two_side_graph', num_neighbor=10, num_process=4, pretrain_epoch=300, pri_epoch=200, privacy_protect=False, regs=[1e-05], report=0, save_flag=1, save_name='new_program_test.pkl', test_flag='part', user_batch_size=512, verbose=1, weights_path='model/')
INFO:root:Namespace(Ks='[10]', batch_size=64, data_path='./data/recommendation/', dataset='ml-1m', embed_size=128, epoch=2000, gpu=1, item_density_threshold=0.01, item_threshold=30, layer_size=[128], lmbda=1, local_batch_size=512, local_epoch=30, log_name='run4_1', log_path='/home/qhuaf/graph_pri/logs/', lr=0.0001, mess_dropout=[0.1, 0.1, 0.1], model_name='two_side_graph', num_neighbor=10, num_process=4, pretrain_epoch=300, pri_epoch=200, privacy_protect=False, regs=[1e-05], report=0, save_flag=1, save_name='new_program_test.pkl', test_flag='part', user_batch_size=512, verbose=1, weights_path='model/')
INFO:root:Namespace(Ks='[10]', batch_size=64, data_path='./data/recommendation/', dataset='ml-1m', embed_size=128, epoch=2000, gpu=1, item_density_threshold=0.01, item_threshold=30, layer_size=[128], lmbda=1, local_batch_size=512, local_epoch=30, log_name='run4_1', log_path='/home/qhuaf/graph_pri/logs/', lr=0.0001, mess_dropout=[0.1, 0.1, 0.1], model_name='two_side_graph', num_neighbor=10, num_process=4, pretrain_epoch=300, pri_epoch=200, privacy_protect=False, regs=[1e-05], report=0, save_flag=1, save_name='new_program_test.pkl', test_flag='part', user_batch_size=512, verbose=1, weights_path='model/')
INFO:root:Namespace(Ks='[10]', batch_size=64, data_path='./data/recommendation/', dataset='ml-1m', embed_size=128, epoch=2000, gpu=3, item_density_threshold=0.01, item_threshold=30, layer_size=[128], lmbda=1, local_batch_size=512, local_epoch=30, log_name='run4_1', log_path='/home/qhuaf/graph_pri/logs/', lr=0.0001, mess_dropout=[0.1, 0.1, 0.1], model_name='two_side_graph', num_neighbor=10, num_process=4, pretrain_epoch=300, pri_epoch=200, privacy_protect=False, regs=[1e-05], report=0, save_flag=1, save_name='new_program_test.pkl', test_flag='part', user_batch_size=512, verbose=1, weights_path='model/')
INFO:root:Namespace(Ks='[10]', batch_size=64, data_path='./data/recommendation/', dataset='ml-1m', embed_size=128, epoch=2000, gpu=3, item_density_threshold=0.01, item_threshold=30, layer_size=[128], lmbda=1, local_batch_size=512, local_epoch=30, log_name='run4_1', log_path='/home/qhuaf/graph_pri/logs/', lr=0.0001, mess_dropout=[0.1, 0.1, 0.1], model_name='two_side_graph', num_neighbor=10, num_process=4, pretrain_epoch=300, pri_epoch=200, privacy_protect=False, regs=[1e-05], report=0, save_flag=1, save_name='new_program_test.pkl', test_flag='part', user_batch_size=512, verbose=1, weights_path='model/')
INFO:root:Namespace(Ks='[10]', batch_size=64, data_path='./data/recommendation/', dataset='ml-1m', embed_size=128, epoch=2000, gpu=3, item_density_threshold=0.01, item_threshold=30, layer_size=[128], lmbda=1, local_batch_size=512, local_epoch=30, log_name='run4_1', log_path='/home/qhuaf/graph_pri/logs/', lr=0.1, mess_dropout=[0.1, 0.1, 0.1], model_name='two_side_graph', num_neighbor=10, num_process=4, pretrain_epoch=300, pri_epoch=200, privacy_protect=False, regs=[1e-05], report=0, save_flag=1, save_name='new_program_test.pkl', test_flag='part', user_batch_size=512, verbose=1, weights_path='model/')
INFO:root:Namespace(Ks='[10]', batch_size=64, data_path='./data/recommendation/', dataset='ml-1m', dp_clip=8, dp_delta=1e-05, dp_eps=8.0, dp_mechanism='laplace', embed_size=128, epoch=2000, gpu=2, item_density_threshold=0.01, item_threshold=30, layer_size=[128], lmbda=1, local_batch_size=512, local_epoch=30, log_name='run4_1', log_path='/home/qhuaf/graph_pri/logs/', lr=0.1, mess_dropout=[0.1, 0.1, 0.1], model_name='two_side_graph_run4_1.pkl', num_neighbor=10, num_process=4, pretrain_epoch=300, pri_epoch=200, privacy_protect=False, privacy_ratio=0.2, privacy_tradeoff=1, regs=[1e-05], report=0, save_flag=1, save_name='model.pkl', test_flag='part', user_batch_size=512, verbose=1, weights_path='model/')
INFO:root:Namespace(Ks='[10]', batch_size=64, data_path='./data/recommendation/', dataset='ml-1m', dp_clip=8, dp_delta=1e-05, dp_eps=8.0, dp_mechanism='laplace', embed_size=128, epoch=2000, gpu=2, item_density_threshold=0.01, item_threshold=30, layer_size=[128], lmbda=1, local_batch_size=512, local_epoch=30, log_name='run4_1', log_path='/home/qhuaf/graph_pri/logs/', lr=0.1, mess_dropout=[0.1, 0.1, 0.1], model_name='two_side_graph', num_neighbor=10, num_process=4, pretrain_epoch=300, pri_epoch=200, privacy_protect=False, privacy_ratio=0.2, privacy_tradeoff=1, regs=[1e-05], report=0, save_flag=1, save_name='run4_1_no_pri.pkl', test_flag='part', user_batch_size=512, verbose=1, weights_path='model/')
INFO:root:Namespace(Ks='[10]', batch_size=64, data_path='./data/recommendation/', dataset='ml-1m', dp_clip=8, dp_delta=1e-05, dp_eps=8.0, dp_mechanism='laplace', embed_size=128, epoch=2000, gpu=2, item_density_threshold=0.01, item_threshold=30, layer_size=[128], lmbda=1, local_batch_size=512, local_epoch=30, log_name='run4_1', log_path='/home/qhuaf/graph_pri/logs/', lr=0.1, mess_dropout=[0.1, 0.1, 0.1], model_name='two_side_graph', num_neighbor=10, num_process=4, pretrain_epoch=300, pri_epoch=200, privacy_protect=False, privacy_ratio=0.2, privacy_tradeoff=1, regs=[1e-05], report=0, save_flag=1, save_name='run4_1_no_pri.pkl', test_flag='part', user_batch_size=512, verbose=1, weights_path='model/')
INFO:root:Epoch 9 [196.5s + 28.9s]: train==[536.86163=536.84265 + 0.01927], recall=[0.64222, 0.64222], precision=[0.06422, 0.06422], hit=[0.64222, 0.64222], ndcg=[0.37824, 0.37824]
INFO:root:save the weights in path: model/run4_1_no_pri.pkl
INFO:root:Epoch 19 [197.0s + 29.3s]: train==[480.52615=480.50085 + 0.02540], recall=[0.66093, 0.66093], precision=[0.06609, 0.06609], hit=[0.66093, 0.66093], ndcg=[0.38922, 0.38922]
INFO:root:save the weights in path: model/run4_1_no_pri.pkl
INFO:root:Epoch 29 [192.8s + 29.5s]: train==[462.69907=462.66516 + 0.03349], recall=[0.67103, 0.67103], precision=[0.06710, 0.06710], hit=[0.67103, 0.67103], ndcg=[0.38845, 0.38845]
INFO:root:save the weights in path: model/run4_1_no_pri.pkl
INFO:root:Epoch 39 [200.5s + 29.9s]: train==[439.00665=438.96393 + 0.04282], recall=[0.66904, 0.66904], precision=[0.06690, 0.06690], hit=[0.66904, 0.66904], ndcg=[0.38985, 0.38985]
INFO:root:Epoch 49 [200.9s + 27.6s]: train==[428.14301=428.09067 + 0.05243], recall=[0.66291, 0.66291], precision=[0.06629, 0.06629], hit=[0.66291, 0.66291], ndcg=[0.38833, 0.38833]
INFO:root:Epoch 59 [196.1s + 30.8s]: train==[416.97552=416.91333 + 0.06227], recall=[0.66424, 0.66424], precision=[0.06642, 0.06642], hit=[0.66424, 0.66424], ndcg=[0.38446, 0.38446]
INFO:root:Epoch 69 [192.5s + 28.4s]: train==[404.43814=404.36569 + 0.07228], recall=[0.66391, 0.66391], precision=[0.06639, 0.06639], hit=[0.66391, 0.66391], ndcg=[0.38516, 0.38516]
INFO:root:Epoch 79 [200.3s + 27.4s]: train==[397.48688=397.40527 + 0.08184], recall=[0.67219, 0.67219], precision=[0.06722, 0.06722], hit=[0.67219, 0.67219], ndcg=[0.39036, 0.39036]
INFO:root:save the weights in path: model/run4_1_no_pri.pkl
INFO:root:Epoch 89 [199.3s + 28.6s]: train==[385.43433=385.34308 + 0.09161], recall=[0.66904, 0.66904], precision=[0.06690, 0.06690], hit=[0.66904, 0.66904], ndcg=[0.39191, 0.39191]
INFO:root:Epoch 99 [202.9s + 31.1s]: train==[382.55801=382.45700 + 0.10133], recall=[0.66904, 0.66904], precision=[0.06690, 0.06690], hit=[0.66904, 0.66904], ndcg=[0.38887, 0.38887]
INFO:root:Epoch 109 [197.7s + 28.4s]: train==[371.04666=370.93637 + 0.11040], recall=[0.67334, 0.67334], precision=[0.06733, 0.06733], hit=[0.67334, 0.67334], ndcg=[0.39393, 0.39393]
INFO:root:save the weights in path: model/run4_1_no_pri.pkl
INFO:root:Epoch 119 [199.9s + 28.7s]: train==[367.80042=367.68121 + 0.11926], recall=[0.66970, 0.66970], precision=[0.06697, 0.06697], hit=[0.66970, 0.66970], ndcg=[0.39274, 0.39274]
INFO:root:Epoch 129 [203.0s + 30.5s]: train==[357.61865=357.48969 + 0.12896], recall=[0.68030, 0.68030], precision=[0.06803, 0.06803], hit=[0.68030, 0.68030], ndcg=[0.39582, 0.39582]
INFO:root:save the weights in path: model/run4_1_no_pri.pkl
INFO:root:Epoch 139 [200.6s + 28.8s]: train==[349.58646=349.44873 + 0.13812], recall=[0.68079, 0.68079], precision=[0.06808, 0.06808], hit=[0.68079, 0.68079], ndcg=[0.39503, 0.39503]
INFO:root:save the weights in path: model/run4_1_no_pri.pkl
INFO:root:Epoch 149 [192.9s + 28.8s]: train==[348.28760=348.14108 + 0.14658], recall=[0.67997, 0.67997], precision=[0.06800, 0.06800], hit=[0.67997, 0.67997], ndcg=[0.39150, 0.39150]
INFO:root:Epoch 159 [177.7s + 29.0s]: train==[339.70621=339.55045 + 0.15565], recall=[0.68179, 0.68179], precision=[0.06818, 0.06818], hit=[0.68179, 0.68179], ndcg=[0.40081, 0.40081]
INFO:root:save the weights in path: model/run4_1_no_pri.pkl
INFO:root:Epoch 169 [176.5s + 28.3s]: train==[335.61508=335.44968 + 0.16470], recall=[0.68477, 0.68477], precision=[0.06848, 0.06848], hit=[0.68477, 0.68477], ndcg=[0.39939, 0.39939]
INFO:root:save the weights in path: model/run4_1_no_pri.pkl
INFO:root:Epoch 179 [177.4s + 31.3s]: train==[327.79224=327.61929 + 0.17324], recall=[0.69321, 0.69321], precision=[0.06932, 0.06932], hit=[0.69321, 0.69321], ndcg=[0.40065, 0.40065]
INFO:root:save the weights in path: model/run4_1_no_pri.pkl
INFO:root:Epoch 189 [180.4s + 29.3s]: train==[328.81641=328.63452 + 0.18183], recall=[0.69834, 0.69834], precision=[0.06983, 0.06983], hit=[0.69834, 0.69834], ndcg=[0.40407, 0.40407]
INFO:root:save the weights in path: model/run4_1_no_pri.pkl
INFO:root:Epoch 199 [179.1s + 28.7s]: train==[317.80914=317.61850 + 0.19044], recall=[0.69868, 0.69868], precision=[0.06987, 0.06987], hit=[0.69868, 0.69868], ndcg=[0.40808, 0.40808]
INFO:root:save the weights in path: model/run4_1_no_pri.pkl
INFO:root:Epoch 209 [187.3s + 31.3s]: train==[314.82831=314.63034 + 0.19828], recall=[0.69702, 0.69702], precision=[0.06970, 0.06970], hit=[0.69702, 0.69702], ndcg=[0.40586, 0.40586]
INFO:root:Epoch 219 [190.8s + 29.3s]: train==[310.41025=310.20374 + 0.20636], recall=[0.69735, 0.69735], precision=[0.06974, 0.06974], hit=[0.69735, 0.69735], ndcg=[0.40787, 0.40787]
INFO:root:Epoch 229 [182.4s + 30.9s]: train==[308.33603=308.12073 + 0.21522], recall=[0.69950, 0.69950], precision=[0.06995, 0.06995], hit=[0.69950, 0.69950], ndcg=[0.41042, 0.41042]
INFO:root:save the weights in path: model/run4_1_no_pri.pkl
INFO:root:Epoch 239 [181.8s + 30.4s]: train==[304.54742=304.32452 + 0.22311], recall=[0.71159, 0.71159], precision=[0.07116, 0.07116], hit=[0.71159, 0.71159], ndcg=[0.41795, 0.41795]
INFO:root:save the weights in path: model/run4_1_no_pri.pkl
INFO:root:Epoch 249 [181.9s + 30.6s]: train==[300.87006=300.63846 + 0.23133], recall=[0.70745, 0.70745], precision=[0.07075, 0.07075], hit=[0.70745, 0.70745], ndcg=[0.41768, 0.41768]
INFO:root:Epoch 259 [184.7s + 28.0s]: train==[292.39383=292.15515 + 0.23908], recall=[0.71076, 0.71076], precision=[0.07108, 0.07108], hit=[0.71076, 0.71076], ndcg=[0.41730, 0.41730]
INFO:root:Epoch 269 [183.9s + 31.3s]: train==[290.16455=289.91769 + 0.24698], recall=[0.71970, 0.71970], precision=[0.07197, 0.07197], hit=[0.71970, 0.71970], ndcg=[0.41971, 0.41971]
INFO:root:save the weights in path: model/run4_1_no_pri.pkl
INFO:root:Epoch 279 [179.2s + 30.1s]: train==[284.74103=284.48584 + 0.25498], recall=[0.72086, 0.72086], precision=[0.07209, 0.07209], hit=[0.72086, 0.72086], ndcg=[0.42198, 0.42198]
INFO:root:save the weights in path: model/run4_1_no_pri.pkl
INFO:root:Epoch 289 [179.8s + 28.6s]: train==[279.16281=278.89926 + 0.26305], recall=[0.71722, 0.71722], precision=[0.07172, 0.07172], hit=[0.71722, 0.71722], ndcg=[0.42356, 0.42356]
INFO:root:Epoch 299 [180.3s + 30.4s]: train==[276.80478=276.53384 + 0.27069], recall=[0.72202, 0.72202], precision=[0.07220, 0.07220], hit=[0.72202, 0.72202], ndcg=[0.42564, 0.42564]
INFO:root:save the weights in path: model/run4_1_no_pri.pkl
INFO:root:Epoch 309 [177.5s + 27.0s]: train==[278.41312=278.13480 + 0.27822], recall=[0.72599, 0.72599], precision=[0.07260, 0.07260], hit=[0.72599, 0.72599], ndcg=[0.42396, 0.42396]
INFO:root:save the weights in path: model/run4_1_no_pri.pkl
INFO:root:Epoch 319 [185.1s + 28.2s]: train==[271.33755=271.05106 + 0.28632], recall=[0.72715, 0.72715], precision=[0.07272, 0.07272], hit=[0.72715, 0.72715], ndcg=[0.42764, 0.42764]
INFO:root:save the weights in path: model/run4_1_no_pri.pkl
INFO:root:Epoch 329 [179.7s + 29.3s]: train==[265.54132=265.24771 + 0.29358], recall=[0.72930, 0.72930], precision=[0.07293, 0.07293], hit=[0.72930, 0.72930], ndcg=[0.42659, 0.42659]
INFO:root:save the weights in path: model/run4_1_no_pri.pkl
INFO:root:Epoch 339 [178.7s + 28.6s]: train==[263.63934=263.33829 + 0.30132], recall=[0.73030, 0.73030], precision=[0.07303, 0.07303], hit=[0.73030, 0.73030], ndcg=[0.43342, 0.43342]
INFO:root:save the weights in path: model/run4_1_no_pri.pkl
INFO:root:Epoch 349 [183.6s + 30.1s]: train==[258.05698=257.74820 + 0.30883], recall=[0.73477, 0.73477], precision=[0.07348, 0.07348], hit=[0.73477, 0.73477], ndcg=[0.43514, 0.43514]
INFO:root:save the weights in path: model/run4_1_no_pri.pkl
INFO:root:Epoch 359 [177.2s + 26.7s]: train==[253.50224=253.18611 + 0.31620], recall=[0.73444, 0.73444], precision=[0.07344, 0.07344], hit=[0.73444, 0.73444], ndcg=[0.43804, 0.43804]
INFO:root:Epoch 369 [181.3s + 29.1s]: train==[250.79224=250.46841 + 0.32389], recall=[0.74189, 0.74189], precision=[0.07419, 0.07419], hit=[0.74189, 0.74189], ndcg=[0.43735, 0.43735]
INFO:root:save the weights in path: model/run4_1_no_pri.pkl
INFO:root:Epoch 379 [179.1s + 27.8s]: train==[248.20355=247.87279 + 0.33090], recall=[0.73411, 0.73411], precision=[0.07341, 0.07341], hit=[0.73411, 0.73411], ndcg=[0.43943, 0.43943]
INFO:root:Epoch 389 [182.5s + 28.0s]: train==[246.44301=246.10519 + 0.33783], recall=[0.74338, 0.74338], precision=[0.07434, 0.07434], hit=[0.74338, 0.74338], ndcg=[0.44265, 0.44265]
INFO:root:save the weights in path: model/run4_1_no_pri.pkl
INFO:root:Epoch 399 [178.6s + 28.1s]: train==[245.54535=245.20062 + 0.34483], recall=[0.74156, 0.74156], precision=[0.07416, 0.07416], hit=[0.74156, 0.74156], ndcg=[0.44150, 0.44150]
INFO:root:Epoch 409 [183.8s + 27.5s]: train==[236.38051=236.02811 + 0.35225], recall=[0.74387, 0.74387], precision=[0.07439, 0.07439], hit=[0.74387, 0.74387], ndcg=[0.44476, 0.44476]
INFO:root:save the weights in path: model/run4_1_no_pri.pkl
INFO:root:Epoch 419 [182.2s + 28.2s]: train==[239.05942=238.70032 + 0.35919], recall=[0.74702, 0.74702], precision=[0.07470, 0.07470], hit=[0.74702, 0.74702], ndcg=[0.44569, 0.44569]
INFO:root:save the weights in path: model/run4_1_no_pri.pkl
INFO:root:Epoch 429 [187.2s + 30.2s]: train==[233.04272=232.67680 + 0.36586], recall=[0.74553, 0.74553], precision=[0.07455, 0.07455], hit=[0.74553, 0.74553], ndcg=[0.44400, 0.44400]
INFO:root:Epoch 439 [168.9s + 29.1s]: train==[231.64798=231.27544 + 0.37220], recall=[0.75315, 0.75315], precision=[0.07531, 0.07531], hit=[0.75315, 0.75315], ndcg=[0.44744, 0.44744]
INFO:root:save the weights in path: model/run4_1_no_pri.pkl
INFO:root:Epoch 449 [163.1s + 28.8s]: train==[225.18219=224.80209 + 0.38024], recall=[0.75513, 0.75513], precision=[0.07551, 0.07551], hit=[0.75513, 0.75513], ndcg=[0.45014, 0.45014]
INFO:root:save the weights in path: model/run4_1_no_pri.pkl
INFO:root:Epoch 459 [168.6s + 30.5s]: train==[226.94569=226.55856 + 0.38713], recall=[0.74884, 0.74884], precision=[0.07488, 0.07488], hit=[0.74884, 0.74884], ndcg=[0.44971, 0.44971]
INFO:root:Epoch 469 [171.7s + 28.7s]: train==[223.21823=222.82541 + 0.39315], recall=[0.75579, 0.75579], precision=[0.07558, 0.07558], hit=[0.75579, 0.75579], ndcg=[0.44794, 0.44794]
INFO:root:save the weights in path: model/run4_1_no_pri.pkl
INFO:root:Epoch 479 [188.3s + 29.2s]: train==[220.57268=220.17307 + 0.39976], recall=[0.75546, 0.75546], precision=[0.07555, 0.07555], hit=[0.75546, 0.75546], ndcg=[0.45158, 0.45158]
INFO:root:Epoch 489 [179.8s + 31.6s]: train==[217.22081=216.81398 + 0.40687], recall=[0.75745, 0.75745], precision=[0.07575, 0.07575], hit=[0.75745, 0.75745], ndcg=[0.45331, 0.45331]
INFO:root:save the weights in path: model/run4_1_no_pri.pkl
INFO:root:Epoch 499 [180.3s + 28.6s]: train==[215.02756=214.61433 + 0.41330], recall=[0.76093, 0.76093], precision=[0.07609, 0.07609], hit=[0.76093, 0.76093], ndcg=[0.45579, 0.45579]
INFO:root:save the weights in path: model/run4_1_no_pri.pkl
INFO:root:Epoch 509 [182.0s + 29.4s]: train==[214.58655=214.16763 + 0.41894], recall=[0.76523, 0.76523], precision=[0.07652, 0.07652], hit=[0.76523, 0.76523], ndcg=[0.45888, 0.45888]
INFO:root:save the weights in path: model/run4_1_no_pri.pkl
INFO:root:Epoch 519 [183.8s + 28.6s]: train==[209.21307=208.78827 + 0.42481], recall=[0.76391, 0.76391], precision=[0.07639, 0.07639], hit=[0.76391, 0.76391], ndcg=[0.45802, 0.45802]
INFO:root:Epoch 529 [181.7s + 27.6s]: train==[208.11772=207.68652 + 0.43129], recall=[0.76490, 0.76490], precision=[0.07649, 0.07649], hit=[0.76490, 0.76490], ndcg=[0.46017, 0.46017]
INFO:root:Epoch 539 [181.7s + 28.2s]: train==[209.41531=208.97850 + 0.43713], recall=[0.76440, 0.76440], precision=[0.07644, 0.07644], hit=[0.76440, 0.76440], ndcg=[0.46278, 0.46278]
INFO:root:Epoch 549 [181.0s + 30.9s]: train==[205.59305=205.15005 + 0.44296], recall=[0.76722, 0.76722], precision=[0.07672, 0.07672], hit=[0.76722, 0.76722], ndcg=[0.46393, 0.46393]
INFO:root:save the weights in path: model/run4_1_no_pri.pkl
INFO:root:Epoch 559 [180.0s + 29.8s]: train==[200.93953=200.49002 + 0.44941], recall=[0.77020, 0.77020], precision=[0.07702, 0.07702], hit=[0.77020, 0.77020], ndcg=[0.46490, 0.46490]
INFO:root:save the weights in path: model/run4_1_no_pri.pkl
INFO:root:Epoch 569 [186.4s + 29.2s]: train==[202.90988=202.45515 + 0.45479], recall=[0.76589, 0.76589], precision=[0.07659, 0.07659], hit=[0.76589, 0.76589], ndcg=[0.46580, 0.46580]
INFO:root:Epoch 579 [184.4s + 30.6s]: train==[199.46169=199.00085 + 0.46091], recall=[0.76672, 0.76672], precision=[0.07667, 0.07667], hit=[0.76672, 0.76672], ndcg=[0.46387, 0.46387]
INFO:root:Epoch 589 [181.2s + 26.6s]: train==[198.44377=197.97681 + 0.46689], recall=[0.77517, 0.77517], precision=[0.07752, 0.07752], hit=[0.77517, 0.77517], ndcg=[0.46959, 0.46959]
INFO:root:save the weights in path: model/run4_1_no_pri.pkl
INFO:root:Epoch 599 [182.0s + 28.0s]: train==[193.27393=192.80081 + 0.47282], recall=[0.77070, 0.77070], precision=[0.07707, 0.07707], hit=[0.77070, 0.77070], ndcg=[0.46883, 0.46883]
INFO:root:Epoch 609 [183.8s + 28.1s]: train==[192.36201=191.88326 + 0.47869], recall=[0.77219, 0.77219], precision=[0.07722, 0.07722], hit=[0.77219, 0.77219], ndcg=[0.47063, 0.47063]
INFO:root:Epoch 619 [178.1s + 29.3s]: train==[193.76366=193.28023 + 0.48347], recall=[0.77997, 0.77997], precision=[0.07800, 0.07800], hit=[0.77997, 0.77997], ndcg=[0.47601, 0.47601]
INFO:root:save the weights in path: model/run4_1_no_pri.pkl
INFO:root:Epoch 629 [187.3s + 29.1s]: train==[187.89439=187.40485 + 0.48953], recall=[0.77748, 0.77748], precision=[0.07775, 0.07775], hit=[0.77748, 0.77748], ndcg=[0.47362, 0.47362]
INFO:root:Epoch 639 [183.2s + 28.7s]: train==[191.31818=190.82295 + 0.49536], recall=[0.78228, 0.78228], precision=[0.07823, 0.07823], hit=[0.78228, 0.78228], ndcg=[0.47918, 0.47918]
INFO:root:save the weights in path: model/run4_1_no_pri.pkl
INFO:root:Epoch 649 [167.2s + 28.8s]: train==[188.25877=187.75815 + 0.50083], recall=[0.78377, 0.78377], precision=[0.07838, 0.07838], hit=[0.78377, 0.78377], ndcg=[0.47480, 0.47480]
INFO:root:save the weights in path: model/run4_1_no_pri.pkl
INFO:root:Epoch 659 [159.9s + 28.7s]: train==[187.07530=186.56947 + 0.50586], recall=[0.78228, 0.78228], precision=[0.07823, 0.07823], hit=[0.78228, 0.78228], ndcg=[0.47354, 0.47354]
INFO:root:Epoch 669 [160.4s + 30.5s]: train==[184.43823=183.92711 + 0.51109], recall=[0.78526, 0.78526], precision=[0.07853, 0.07853], hit=[0.78526, 0.78526], ndcg=[0.47683, 0.47683]
INFO:root:save the weights in path: model/run4_1_no_pri.pkl
INFO:root:Epoch 679 [164.2s + 29.0s]: train==[181.51750=181.00165 + 0.51603], recall=[0.78262, 0.78262], precision=[0.07826, 0.07826], hit=[0.78262, 0.78262], ndcg=[0.48082, 0.48082]
INFO:root:Epoch 689 [152.7s + 27.5s]: train==[180.57817=180.05759 + 0.52055], recall=[0.78162, 0.78162], precision=[0.07816, 0.07816], hit=[0.78162, 0.78162], ndcg=[0.48149, 0.48149]
INFO:root:Epoch 699 [164.8s + 29.7s]: train==[179.36575=178.83923 + 0.52657], recall=[0.78841, 0.78841], precision=[0.07884, 0.07884], hit=[0.78841, 0.78841], ndcg=[0.48194, 0.48194]
INFO:root:save the weights in path: model/run4_1_no_pri.pkl
INFO:root:Epoch 709 [157.2s + 30.0s]: train==[178.69847=178.16690 + 0.53178], recall=[0.78344, 0.78344], precision=[0.07834, 0.07834], hit=[0.78344, 0.78344], ndcg=[0.48001, 0.48001]
INFO:root:Epoch 719 [178.3s + 29.6s]: train==[176.72354=176.18640 + 0.53697], recall=[0.78924, 0.78924], precision=[0.07892, 0.07892], hit=[0.78924, 0.78924], ndcg=[0.48242, 0.48242]
INFO:root:save the weights in path: model/run4_1_no_pri.pkl
INFO:root:Epoch 729 [175.7s + 29.5s]: train==[174.98590=174.44354 + 0.54243], recall=[0.79106, 0.79106], precision=[0.07911, 0.07911], hit=[0.79106, 0.79106], ndcg=[0.48899, 0.48899]
INFO:root:save the weights in path: model/run4_1_no_pri.pkl
INFO:root:Epoch 739 [178.7s + 30.1s]: train==[174.99951=174.45232 + 0.54714], recall=[0.79321, 0.79321], precision=[0.07932, 0.07932], hit=[0.79321, 0.79321], ndcg=[0.48738, 0.48738]
INFO:root:save the weights in path: model/run4_1_no_pri.pkl
INFO:root:Epoch 749 [180.7s + 27.2s]: train==[173.32730=172.77559 + 0.55182], recall=[0.78825, 0.78825], precision=[0.07882, 0.07882], hit=[0.78825, 0.78825], ndcg=[0.48917, 0.48917]
INFO:root:Epoch 759 [180.0s + 29.1s]: train==[172.94705=172.39038 + 0.55673], recall=[0.79189, 0.79189], precision=[0.07919, 0.07919], hit=[0.79189, 0.79189], ndcg=[0.48599, 0.48599]
INFO:root:Epoch 769 [180.2s + 28.2s]: train==[170.70471=170.14276 + 0.56193], recall=[0.79652, 0.79652], precision=[0.07965, 0.07965], hit=[0.79652, 0.79652], ndcg=[0.49046, 0.49046]
INFO:root:save the weights in path: model/run4_1_no_pri.pkl
INFO:root:Epoch 779 [188.2s + 26.8s]: train==[172.57274=172.00682 + 0.56591], recall=[0.79719, 0.79719], precision=[0.07972, 0.07972], hit=[0.79719, 0.79719], ndcg=[0.48930, 0.48930]
INFO:root:save the weights in path: model/run4_1_no_pri.pkl
INFO:root:Epoch 789 [180.0s + 30.9s]: train==[167.39912=166.82733 + 0.57189], recall=[0.79669, 0.79669], precision=[0.07967, 0.07967], hit=[0.79669, 0.79669], ndcg=[0.48728, 0.48728]
INFO:root:Epoch 799 [180.1s + 29.5s]: train==[166.44545=165.86955 + 0.57601], recall=[0.80099, 0.80099], precision=[0.08010, 0.08010], hit=[0.80099, 0.80099], ndcg=[0.49441, 0.49441]
INFO:root:save the weights in path: model/run4_1_no_pri.pkl
INFO:root:Epoch 809 [185.9s + 29.3s]: train==[165.46565=164.88533 + 0.58044], recall=[0.79222, 0.79222], precision=[0.07922, 0.07922], hit=[0.79222, 0.79222], ndcg=[0.49099, 0.49099]
INFO:root:Epoch 819 [193.7s + 28.9s]: train==[163.24921=162.66327 + 0.58578], recall=[0.79685, 0.79685], precision=[0.07969, 0.07969], hit=[0.79685, 0.79685], ndcg=[0.49064, 0.49064]
INFO:root:Epoch 829 [181.4s + 29.8s]: train==[164.71625=164.12648 + 0.58978], recall=[0.79636, 0.79636], precision=[0.07964, 0.07964], hit=[0.79636, 0.79636], ndcg=[0.49516, 0.49516]
INFO:root:Epoch 839 [184.7s + 28.4s]: train==[162.32883=161.73445 + 0.59457], recall=[0.80232, 0.80232], precision=[0.08023, 0.08023], hit=[0.80232, 0.80232], ndcg=[0.49734, 0.49734]
INFO:root:save the weights in path: model/run4_1_no_pri.pkl
INFO:root:Epoch 849 [169.7s + 29.0s]: train==[161.56656=160.96687 + 0.59969], recall=[0.79917, 0.79917], precision=[0.07992, 0.07992], hit=[0.79917, 0.79917], ndcg=[0.49817, 0.49817]
INFO:root:Epoch 859 [176.5s + 29.0s]: train==[160.85847=160.25293 + 0.60558], recall=[0.80414, 0.80414], precision=[0.08041, 0.08041], hit=[0.80414, 0.80414], ndcg=[0.50032, 0.50032]
INFO:root:save the weights in path: model/run4_1_no_pri.pkl
INFO:root:Epoch 869 [180.6s + 28.0s]: train==[158.53008=157.92274 + 0.60730], recall=[0.80116, 0.80116], precision=[0.08012, 0.08012], hit=[0.80116, 0.80116], ndcg=[0.49838, 0.49838]
INFO:root:Epoch 879 [177.7s + 29.1s]: train==[158.15829=157.54567 + 0.61257], recall=[0.80050, 0.80050], precision=[0.08005, 0.08005], hit=[0.80050, 0.80050], ndcg=[0.49729, 0.49729]
INFO:root:Epoch 889 [186.5s + 30.3s]: train==[159.02275=158.40572 + 0.61701], recall=[0.80000, 0.80000], precision=[0.08000, 0.08000], hit=[0.80000, 0.80000], ndcg=[0.49572, 0.49572]
INFO:root:Epoch 899 [175.6s + 30.1s]: train==[153.62280=153.00040 + 0.62238], recall=[0.80248, 0.80248], precision=[0.08025, 0.08025], hit=[0.80248, 0.80248], ndcg=[0.49899, 0.49899]
INFO:root:Epoch 909 [176.4s + 29.7s]: train==[157.25662=156.63033 + 0.62635], recall=[0.80579, 0.80579], precision=[0.08058, 0.08058], hit=[0.80579, 0.80579], ndcg=[0.50100, 0.50100]
INFO:root:save the weights in path: model/run4_1_no_pri.pkl
INFO:root:Epoch 919 [177.0s + 29.5s]: train==[155.66882=155.03687 + 0.63192], recall=[0.80679, 0.80679], precision=[0.08068, 0.08068], hit=[0.80679, 0.80679], ndcg=[0.50314, 0.50314]
INFO:root:save the weights in path: model/run4_1_no_pri.pkl
INFO:root:Epoch 929 [189.7s + 31.2s]: train==[154.70244=154.06664 + 0.63570], recall=[0.80265, 0.80265], precision=[0.08026, 0.08026], hit=[0.80265, 0.80265], ndcg=[0.49967, 0.49967]
INFO:root:Epoch 939 [182.2s + 29.5s]: train==[152.55289=151.91447 + 0.63851], recall=[0.80877, 0.80877], precision=[0.08088, 0.08088], hit=[0.80877, 0.80877], ndcg=[0.49908, 0.49908]
INFO:root:save the weights in path: model/run4_1_no_pri.pkl
INFO:root:Epoch 949 [185.6s + 28.0s]: train==[154.29826=153.65564 + 0.64259], recall=[0.80331, 0.80331], precision=[0.08033, 0.08033], hit=[0.80331, 0.80331], ndcg=[0.50342, 0.50342]
INFO:root:Epoch 959 [177.4s + 29.0s]: train==[149.94141=149.29340 + 0.64805], recall=[0.80944, 0.80944], precision=[0.08094, 0.08094], hit=[0.80944, 0.80944], ndcg=[0.50598, 0.50598]
INFO:root:save the weights in path: model/run4_1_no_pri.pkl
INFO:root:Epoch 969 [182.6s + 29.8s]: train==[151.06337=150.41209 + 0.65148], recall=[0.80778, 0.80778], precision=[0.08078, 0.08078], hit=[0.80778, 0.80778], ndcg=[0.50536, 0.50536]
INFO:root:Epoch 979 [178.1s + 29.9s]: train==[149.29704=148.64037 + 0.65667], recall=[0.81209, 0.81209], precision=[0.08121, 0.08121], hit=[0.81209, 0.81209], ndcg=[0.50665, 0.50665]
INFO:root:save the weights in path: model/run4_1_no_pri.pkl
INFO:root:Epoch 989 [181.9s + 29.5s]: train==[148.31583=147.65578 + 0.66006], recall=[0.80944, 0.80944], precision=[0.08094, 0.08094], hit=[0.80944, 0.80944], ndcg=[0.50716, 0.50716]
INFO:root:Epoch 999 [178.7s + 30.0s]: train==[149.06769=148.40332 + 0.66422], recall=[0.81010, 0.81010], precision=[0.08101, 0.08101], hit=[0.81010, 0.81010], ndcg=[0.50549, 0.50549]
INFO:root:Epoch 1009 [178.1s + 28.8s]: train==[144.34077=143.67130 + 0.66955], recall=[0.81325, 0.81325], precision=[0.08132, 0.08132], hit=[0.81325, 0.81325], ndcg=[0.50904, 0.50904]
INFO:root:save the weights in path: model/run4_1_no_pri.pkl
INFO:root:Epoch 1019 [185.1s + 30.6s]: train==[147.03186=146.35956 + 0.67238], recall=[0.81093, 0.81093], precision=[0.08109, 0.08109], hit=[0.81093, 0.81093], ndcg=[0.51191, 0.51191]
INFO:root:Epoch 1029 [182.4s + 29.5s]: train==[146.32210=145.64526 + 0.67682], recall=[0.80844, 0.80844], precision=[0.08084, 0.08084], hit=[0.80844, 0.80844], ndcg=[0.50990, 0.50990]
INFO:root:Epoch 1039 [180.1s + 28.9s]: train==[145.40195=144.72072 + 0.68111], recall=[0.81325, 0.81325], precision=[0.08132, 0.08132], hit=[0.81325, 0.81325], ndcg=[0.51008, 0.51008]
INFO:root:save the weights in path: model/run4_1_no_pri.pkl
INFO:root:Epoch 1049 [180.1s + 27.9s]: train==[145.36044=144.67604 + 0.68432], recall=[0.81341, 0.81341], precision=[0.08134, 0.08134], hit=[0.81341, 0.81341], ndcg=[0.50909, 0.50909]
INFO:root:save the weights in path: model/run4_1_no_pri.pkl
INFO:root:Epoch 1059 [173.7s + 29.5s]: train==[143.98869=143.29930 + 0.68945], recall=[0.81374, 0.81374], precision=[0.08137, 0.08137], hit=[0.81374, 0.81374], ndcg=[0.51087, 0.51087]
INFO:root:save the weights in path: model/run4_1_no_pri.pkl
INFO:root:Epoch 1069 [183.1s + 28.9s]: train==[143.15074=142.45753 + 0.69305], recall=[0.81755, 0.81755], precision=[0.08175, 0.08175], hit=[0.81755, 0.81755], ndcg=[0.51172, 0.51172]
INFO:root:save the weights in path: model/run4_1_no_pri.pkl
INFO:root:Epoch 1079 [182.5s + 30.7s]: train==[141.62541=140.92807 + 0.69727], recall=[0.81738, 0.81738], precision=[0.08174, 0.08174], hit=[0.81738, 0.81738], ndcg=[0.51577, 0.51577]
INFO:root:Epoch 1089 [178.0s + 31.3s]: train==[143.43512=142.73494 + 0.70019], recall=[0.81722, 0.81722], precision=[0.08172, 0.08172], hit=[0.81722, 0.81722], ndcg=[0.51475, 0.51475]
INFO:root:Epoch 1099 [176.4s + 29.9s]: train==[142.14857=141.44405 + 0.70460], recall=[0.81755, 0.81755], precision=[0.08175, 0.08175], hit=[0.81755, 0.81755], ndcg=[0.51285, 0.51285]
INFO:root:save the weights in path: model/run4_1_no_pri.pkl
INFO:root:Epoch 1109 [181.4s + 30.5s]: train==[141.77487=141.06616 + 0.70871], recall=[0.81623, 0.81623], precision=[0.08162, 0.08162], hit=[0.81623, 0.81623], ndcg=[0.51431, 0.51431]
INFO:root:Epoch 1119 [185.6s + 30.1s]: train==[140.69458=139.98155 + 0.71302], recall=[0.81937, 0.81937], precision=[0.08194, 0.08194], hit=[0.81937, 0.81937], ndcg=[0.51470, 0.51470]
INFO:root:save the weights in path: model/run4_1_no_pri.pkl
INFO:root:Epoch 1129 [181.3s + 30.2s]: train==[137.31941=136.60182 + 0.71761], recall=[0.81523, 0.81523], precision=[0.08152, 0.08152], hit=[0.81523, 0.81523], ndcg=[0.51352, 0.51352]
INFO:root:Epoch 1139 [170.8s + 28.9s]: train==[139.02321=138.30281 + 0.72046], recall=[0.81755, 0.81755], precision=[0.08175, 0.08175], hit=[0.81755, 0.81755], ndcg=[0.51510, 0.51510]
INFO:root:Epoch 1149 [157.8s + 29.7s]: train==[137.96693=137.24242 + 0.72448], recall=[0.82185, 0.82185], precision=[0.08219, 0.08219], hit=[0.82185, 0.82185], ndcg=[0.51983, 0.51983]
INFO:root:save the weights in path: model/run4_1_no_pri.pkl
INFO:root:Epoch 1159 [159.7s + 28.8s]: train==[136.07489=135.34647 + 0.72848], recall=[0.81921, 0.81921], precision=[0.08192, 0.08192], hit=[0.81921, 0.81921], ndcg=[0.51658, 0.51658]
INFO:root:Epoch 1169 [159.2s + 28.3s]: train==[136.66672=135.93498 + 0.73162], recall=[0.81738, 0.81738], precision=[0.08174, 0.08174], hit=[0.81738, 0.81738], ndcg=[0.51569, 0.51569]
INFO:root:Epoch 1179 [165.8s + 29.4s]: train==[136.83070=136.09534 + 0.73534], recall=[0.81937, 0.81937], precision=[0.08194, 0.08194], hit=[0.81937, 0.81937], ndcg=[0.51702, 0.51702]
INFO:root:Epoch 1189 [169.2s + 28.1s]: train==[134.50545=133.76579 + 0.73948], recall=[0.81921, 0.81921], precision=[0.08192, 0.08192], hit=[0.81921, 0.81921], ndcg=[0.52316, 0.52316]
INFO:root:Epoch 1199 [173.4s + 29.5s]: train==[136.56224=135.81885 + 0.74343], recall=[0.82119, 0.82119], precision=[0.08212, 0.08212], hit=[0.82119, 0.82119], ndcg=[0.52067, 0.52067]
INFO:root:Epoch 1209 [167.0s + 27.7s]: train==[135.06390=134.31769 + 0.74631], recall=[0.82169, 0.82169], precision=[0.08217, 0.08217], hit=[0.82169, 0.82169], ndcg=[0.52093, 0.52093]
INFO:root:Epoch 1219 [163.3s + 29.6s]: train==[131.94341=131.19313 + 0.75028], recall=[0.82152, 0.82152], precision=[0.08215, 0.08215], hit=[0.82152, 0.82152], ndcg=[0.52386, 0.52386]
INFO:root:Epoch 1229 [172.3s + 30.2s]: train==[130.04025=129.28560 + 0.75468], recall=[0.82268, 0.82268], precision=[0.08227, 0.08227], hit=[0.82268, 0.82268], ndcg=[0.51949, 0.51949]
INFO:root:save the weights in path: model/run4_1_no_pri.pkl
INFO:root:Epoch 1239 [176.1s + 28.9s]: train==[133.21831=132.45982 + 0.75852], recall=[0.82086, 0.82086], precision=[0.08209, 0.08209], hit=[0.82086, 0.82086], ndcg=[0.52191, 0.52191]
INFO:root:Epoch 1249 [184.0s + 29.6s]: train==[132.78453=132.02347 + 0.76106], recall=[0.82169, 0.82169], precision=[0.08217, 0.08217], hit=[0.82169, 0.82169], ndcg=[0.51926, 0.51926]
INFO:root:Epoch 1259 [180.1s + 29.2s]: train==[128.92943=128.16359 + 0.76579], recall=[0.82185, 0.82185], precision=[0.08219, 0.08219], hit=[0.82185, 0.82185], ndcg=[0.52088, 0.52088]
INFO:root:Epoch 1269 [184.6s + 30.3s]: train==[130.01593=129.24657 + 0.76939], recall=[0.82384, 0.82384], precision=[0.08238, 0.08238], hit=[0.82384, 0.82384], ndcg=[0.52589, 0.52589]
INFO:root:save the weights in path: model/run4_1_no_pri.pkl
INFO:root:Epoch 1279 [177.0s + 28.6s]: train==[128.41898=127.64633 + 0.77258], recall=[0.82632, 0.82632], precision=[0.08263, 0.08263], hit=[0.82632, 0.82632], ndcg=[0.52538, 0.52538]
INFO:root:save the weights in path: model/run4_1_no_pri.pkl
INFO:root:Epoch 1289 [183.3s + 30.2s]: train==[128.68854=127.91323 + 0.77535], recall=[0.82318, 0.82318], precision=[0.08232, 0.08232], hit=[0.82318, 0.82318], ndcg=[0.52220, 0.52220]
INFO:root:Epoch 1299 [187.6s + 30.8s]: train==[127.66579=126.88691 + 0.77887], recall=[0.82235, 0.82235], precision=[0.08224, 0.08224], hit=[0.82235, 0.82235], ndcg=[0.52456, 0.52456]
INFO:root:Epoch 1309 [182.5s + 27.9s]: train==[130.59578=129.81306 + 0.78267], recall=[0.82401, 0.82401], precision=[0.08240, 0.08240], hit=[0.82401, 0.82401], ndcg=[0.52464, 0.52464]
INFO:root:Epoch 1319 [184.6s + 27.6s]: train==[127.42119=126.63531 + 0.78594], recall=[0.82450, 0.82450], precision=[0.08245, 0.08245], hit=[0.82450, 0.82450], ndcg=[0.52451, 0.52451]
INFO:root:Epoch 1329 [187.4s + 28.8s]: train==[126.21263=125.42208 + 0.79054], recall=[0.82252, 0.82252], precision=[0.08225, 0.08225], hit=[0.82252, 0.82252], ndcg=[0.52588, 0.52588]
INFO:root:Epoch 1339 [176.5s + 28.5s]: train==[125.94930=125.15643 + 0.79285], recall=[0.82467, 0.82467], precision=[0.08247, 0.08247], hit=[0.82467, 0.82467], ndcg=[0.52758, 0.52758]
INFO:root:Epoch 1349 [184.3s + 30.4s]: train==[127.43651=126.63972 + 0.79684], recall=[0.82947, 0.82947], precision=[0.08295, 0.08295], hit=[0.82947, 0.82947], ndcg=[0.52682, 0.52682]
INFO:root:save the weights in path: model/run4_1_no_pri.pkl
INFO:root:Epoch 1359 [183.7s + 29.2s]: train==[125.15145=124.35112 + 0.80028], recall=[0.82450, 0.82450], precision=[0.08245, 0.08245], hit=[0.82450, 0.82450], ndcg=[0.52460, 0.52460]
INFO:root:Epoch 1369 [184.8s + 30.0s]: train==[123.74541=122.94089 + 0.80457], recall=[0.82715, 0.82715], precision=[0.08272, 0.08272], hit=[0.82715, 0.82715], ndcg=[0.52938, 0.52938]
INFO:root:Epoch 1379 [176.8s + 31.6s]: train==[123.69814=122.89101 + 0.80712], recall=[0.82649, 0.82649], precision=[0.08265, 0.08265], hit=[0.82649, 0.82649], ndcg=[0.52905, 0.52905]
INFO:root:Epoch 1389 [179.3s + 31.4s]: train==[124.11426=123.30312 + 0.81105], recall=[0.82649, 0.82649], precision=[0.08265, 0.08265], hit=[0.82649, 0.82649], ndcg=[0.52750, 0.52750]
INFO:root:Epoch 1399 [184.4s + 28.9s]: train==[123.51231=122.69808 + 0.81426], recall=[0.82997, 0.82997], precision=[0.08300, 0.08300], hit=[0.82997, 0.82997], ndcg=[0.53190, 0.53190]
INFO:root:save the weights in path: model/run4_1_no_pri.pkl
INFO:root:Epoch 1409 [184.6s + 30.4s]: train==[123.32841=122.51151 + 0.81675], recall=[0.83030, 0.83030], precision=[0.08303, 0.08303], hit=[0.83030, 0.83030], ndcg=[0.53123, 0.53123]
INFO:root:save the weights in path: model/run4_1_no_pri.pkl
INFO:root:Epoch 1419 [181.5s + 29.4s]: train==[122.93348=122.11234 + 0.82116], recall=[0.83328, 0.83328], precision=[0.08333, 0.08333], hit=[0.83328, 0.83328], ndcg=[0.53527, 0.53527]
INFO:root:save the weights in path: model/run4_1_no_pri.pkl
INFO:root:Epoch 1429 [183.3s + 27.9s]: train==[123.20808=122.38381 + 0.82425], recall=[0.82897, 0.82897], precision=[0.08290, 0.08290], hit=[0.82897, 0.82897], ndcg=[0.53128, 0.53128]
INFO:root:Epoch 1439 [182.6s + 29.8s]: train==[120.87205=120.04404 + 0.82804], recall=[0.83030, 0.83030], precision=[0.08303, 0.08303], hit=[0.83030, 0.83030], ndcg=[0.53189, 0.53189]
INFO:root:Epoch 1449 [185.4s + 29.8s]: train==[120.44605=119.61598 + 0.83007], recall=[0.83526, 0.83526], precision=[0.08353, 0.08353], hit=[0.83526, 0.83526], ndcg=[0.53603, 0.53603]
INFO:root:save the weights in path: model/run4_1_no_pri.pkl
INFO:root:Epoch 1459 [179.7s + 30.4s]: train==[119.41281=118.57864 + 0.83419], recall=[0.83195, 0.83195], precision=[0.08320, 0.08320], hit=[0.83195, 0.83195], ndcg=[0.53348, 0.53348]
INFO:root:Epoch 1469 [179.8s + 30.4s]: train==[120.25370=119.41653 + 0.83730], recall=[0.82947, 0.82947], precision=[0.08295, 0.08295], hit=[0.82947, 0.82947], ndcg=[0.53045, 0.53045]
INFO:root:Epoch 1479 [182.0s + 29.0s]: train==[119.77406=118.93206 + 0.84190], recall=[0.83212, 0.83212], precision=[0.08321, 0.08321], hit=[0.83212, 0.83212], ndcg=[0.53413, 0.53413]
INFO:root:Epoch 1489 [183.6s + 27.6s]: train==[120.06578=119.22150 + 0.84446], recall=[0.83195, 0.83195], precision=[0.08320, 0.08320], hit=[0.83195, 0.83195], ndcg=[0.53144, 0.53144]
INFO:root:Epoch 1499 [180.2s + 28.3s]: train==[118.37614=117.52731 + 0.84891], recall=[0.83096, 0.83096], precision=[0.08310, 0.08310], hit=[0.83096, 0.83096], ndcg=[0.53204, 0.53204]
INFO:root:Epoch 1509 [182.2s + 32.8s]: train==[116.75916=115.90828 + 0.85086], recall=[0.82517, 0.82517], precision=[0.08252, 0.08252], hit=[0.82517, 0.82517], ndcg=[0.53253, 0.53253]
INFO:root:Epoch 1519 [176.2s + 29.8s]: train==[116.86786=116.01356 + 0.85427], recall=[0.82798, 0.82798], precision=[0.08280, 0.08280], hit=[0.82798, 0.82798], ndcg=[0.53209, 0.53209]
INFO:root:Epoch 1529 [184.8s + 29.3s]: train==[115.74068=114.88234 + 0.85831], recall=[0.82500, 0.82500], precision=[0.08250, 0.08250], hit=[0.82500, 0.82500], ndcg=[0.53374, 0.53374]
INFO:root:Epoch 1539 [187.7s + 30.0s]: train==[115.64024=114.77953 + 0.86066], recall=[0.83113, 0.83113], precision=[0.08311, 0.08311], hit=[0.83113, 0.83113], ndcg=[0.53686, 0.53686]
INFO:root:Epoch 1549 [183.3s + 30.0s]: train==[116.75201=115.88762 + 0.86442], recall=[0.83079, 0.83079], precision=[0.08308, 0.08308], hit=[0.83079, 0.83079], ndcg=[0.53292, 0.53292]
INFO:root:Epoch 1559 [175.3s + 29.4s]: train==[114.37769=113.51134 + 0.86640], recall=[0.82881, 0.82881], precision=[0.08288, 0.08288], hit=[0.82881, 0.82881], ndcg=[0.53541, 0.53541]
INFO:root:Epoch 1569 [181.6s + 29.0s]: train==[114.64063=113.77085 + 0.86971], recall=[0.83162, 0.83162], precision=[0.08316, 0.08316], hit=[0.83162, 0.83162], ndcg=[0.53605, 0.53605]
INFO:root:Epoch 1579 [181.2s + 28.2s]: train==[113.06158=112.18703 + 0.87443], recall=[0.82765, 0.82765], precision=[0.08276, 0.08276], hit=[0.82765, 0.82765], ndcg=[0.53516, 0.53516]
INFO:root:Epoch 1589 [184.2s + 32.1s]: train==[113.17339=112.29778 + 0.87558], recall=[0.83311, 0.83311], precision=[0.08331, 0.08331], hit=[0.83311, 0.83311], ndcg=[0.53837, 0.53837]
INFO:root:Epoch 1599 [176.9s + 29.1s]: train==[116.51142=115.63165 + 0.87992], recall=[0.83411, 0.83411], precision=[0.08341, 0.08341], hit=[0.83411, 0.83411], ndcg=[0.53557, 0.53557]
INFO:root:Epoch 1609 [181.8s + 29.0s]: train==[115.76197=114.87950 + 0.88242], recall=[0.83113, 0.83113], precision=[0.08311, 0.08311], hit=[0.83113, 0.83113], ndcg=[0.53773, 0.53773]
INFO:root:Epoch 1619 [178.8s + 30.5s]: train==[113.80543=112.91832 + 0.88714], recall=[0.83775, 0.83775], precision=[0.08377, 0.08377], hit=[0.83775, 0.83775], ndcg=[0.53831, 0.53831]
INFO:root:save the weights in path: model/run4_1_no_pri.pkl
INFO:root:Epoch 1629 [184.5s + 31.9s]: train==[112.36125=111.47235 + 0.88888], recall=[0.83609, 0.83609], precision=[0.08361, 0.08361], hit=[0.83609, 0.83609], ndcg=[0.53846, 0.53846]
INFO:root:Epoch 1639 [182.3s + 28.5s]: train==[112.98286=112.09061 + 0.89229], recall=[0.83228, 0.83228], precision=[0.08323, 0.08323], hit=[0.83228, 0.83228], ndcg=[0.53919, 0.53919]
INFO:root:Epoch 1649 [180.5s + 29.7s]: train==[111.84088=110.94591 + 0.89498], recall=[0.83361, 0.83361], precision=[0.08336, 0.08336], hit=[0.83361, 0.83361], ndcg=[0.53785, 0.53785]
INFO:root:Epoch 1659 [177.6s + 30.3s]: train==[113.54790=112.65090 + 0.89699], recall=[0.83328, 0.83328], precision=[0.08333, 0.08333], hit=[0.83328, 0.83328], ndcg=[0.53956, 0.53956]
INFO:root:Epoch 1669 [181.8s + 29.6s]: train==[111.21463=110.31306 + 0.90148], recall=[0.83642, 0.83642], precision=[0.08364, 0.08364], hit=[0.83642, 0.83642], ndcg=[0.53807, 0.53807]
INFO:root:Epoch 1679 [178.9s + 28.9s]: train==[112.39529=111.49090 + 0.90448], recall=[0.83560, 0.83560], precision=[0.08356, 0.08356], hit=[0.83560, 0.83560], ndcg=[0.54031, 0.54031]
INFO:root:Epoch 1689 [179.9s + 28.6s]: train==[110.28772=109.38010 + 0.90766], recall=[0.83411, 0.83411], precision=[0.08341, 0.08341], hit=[0.83411, 0.83411], ndcg=[0.54070, 0.54070]
INFO:root:Epoch 1699 [188.5s + 29.2s]: train==[109.29848=108.38808 + 0.91031], recall=[0.83493, 0.83493], precision=[0.08349, 0.08349], hit=[0.83493, 0.83493], ndcg=[0.53941, 0.53941]
INFO:root:Epoch 1709 [184.3s + 28.9s]: train==[108.65089=107.73705 + 0.91385], recall=[0.83659, 0.83659], precision=[0.08366, 0.08366], hit=[0.83659, 0.83659], ndcg=[0.54085, 0.54085]
INFO:root:Epoch 1719 [184.8s + 31.2s]: train==[108.87319=107.95755 + 0.91566], recall=[0.83825, 0.83825], precision=[0.08382, 0.08382], hit=[0.83825, 0.83825], ndcg=[0.54479, 0.54479]
INFO:root:save the weights in path: model/run4_1_no_pri.pkl
INFO:root:Epoch 1729 [175.6s + 30.3s]: train==[109.52809=108.60758 + 0.92046], recall=[0.83245, 0.83245], precision=[0.08325, 0.08325], hit=[0.83245, 0.83245], ndcg=[0.54265, 0.54265]
INFO:root:Epoch 1739 [181.0s + 29.0s]: train==[109.81107=108.88856 + 0.92257], recall=[0.83411, 0.83411], precision=[0.08341, 0.08341], hit=[0.83411, 0.83411], ndcg=[0.53953, 0.53953]
INFO:root:Epoch 1749 [178.5s + 28.1s]: train==[107.94127=107.01416 + 0.92700], recall=[0.83394, 0.83394], precision=[0.08339, 0.08339], hit=[0.83394, 0.83394], ndcg=[0.53918, 0.53918]
INFO:root:Epoch 1759 [176.5s + 30.4s]: train==[110.58765=109.65990 + 0.92778], recall=[0.83642, 0.83642], precision=[0.08364, 0.08364], hit=[0.83642, 0.83642], ndcg=[0.53939, 0.53939]
INFO:root:Epoch 1769 [183.8s + 29.2s]: train==[107.69795=106.76606 + 0.93190], recall=[0.83907, 0.83907], precision=[0.08391, 0.08391], hit=[0.83907, 0.83907], ndcg=[0.54596, 0.54596]
INFO:root:save the weights in path: model/run4_1_no_pri.pkl
INFO:root:Epoch 1779 [192.8s + 29.2s]: train==[107.34187=106.40739 + 0.93444], recall=[0.83742, 0.83742], precision=[0.08374, 0.08374], hit=[0.83742, 0.83742], ndcg=[0.54477, 0.54477]
INFO:root:Epoch 1789 [181.4s + 28.9s]: train==[107.91209=106.97318 + 0.93885], recall=[0.83444, 0.83444], precision=[0.08344, 0.08344], hit=[0.83444, 0.83444], ndcg=[0.54151, 0.54151]
INFO:root:Epoch 1799 [183.8s + 32.1s]: train==[106.66521=105.72384 + 0.94138], recall=[0.83278, 0.83278], precision=[0.08328, 0.08328], hit=[0.83278, 0.83278], ndcg=[0.53991, 0.53991]
INFO:root:Epoch 1809 [179.8s + 28.8s]: train==[106.36585=105.42292 + 0.94294], recall=[0.83477, 0.83477], precision=[0.08348, 0.08348], hit=[0.83477, 0.83477], ndcg=[0.54061, 0.54061]
INFO:root:Epoch 1819 [186.9s + 30.8s]: train==[106.54805=105.60277 + 0.94530], recall=[0.83295, 0.83295], precision=[0.08329, 0.08329], hit=[0.83295, 0.83295], ndcg=[0.54002, 0.54002]
INFO:root:Epoch 1829 [192.4s + 28.6s]: train==[106.48804=105.53893 + 0.94925], recall=[0.83874, 0.83874], precision=[0.08387, 0.08387], hit=[0.83874, 0.83874], ndcg=[0.54400, 0.54400]
INFO:root:Epoch 1839 [185.8s + 27.9s]: train==[105.78207=104.82954 + 0.95239], recall=[0.84139, 0.84139], precision=[0.08414, 0.08414], hit=[0.84139, 0.84139], ndcg=[0.54228, 0.54228]
INFO:root:save the weights in path: model/run4_1_no_pri.pkl
INFO:root:Epoch 1849 [184.8s + 30.7s]: train==[104.90051=103.94411 + 0.95644], recall=[0.83775, 0.83775], precision=[0.08377, 0.08377], hit=[0.83775, 0.83775], ndcg=[0.54334, 0.54334]
INFO:root:Epoch 1859 [181.9s + 29.7s]: train==[105.75291=104.79333 + 0.95956], recall=[0.84139, 0.84139], precision=[0.08414, 0.08414], hit=[0.84139, 0.84139], ndcg=[0.54621, 0.54621]
INFO:root:save the weights in path: model/run4_1_no_pri.pkl
INFO:root:Epoch 1869 [182.2s + 31.1s]: train==[105.04557=104.08598 + 0.95944], recall=[0.83709, 0.83709], precision=[0.08371, 0.08371], hit=[0.83709, 0.83709], ndcg=[0.53950, 0.53950]
INFO:root:Epoch 1879 [183.1s + 29.9s]: train==[103.11239=102.14651 + 0.96593], recall=[0.83675, 0.83675], precision=[0.08368, 0.08368], hit=[0.83675, 0.83675], ndcg=[0.54577, 0.54577]
INFO:root:Epoch 1889 [182.3s + 28.8s]: train==[103.74014=102.77352 + 0.96667], recall=[0.83692, 0.83692], precision=[0.08369, 0.08369], hit=[0.83692, 0.83692], ndcg=[0.54476, 0.54476]
INFO:root:Epoch 1899 [181.8s + 29.3s]: train==[102.24696=101.27753 + 0.96939], recall=[0.84321, 0.84321], precision=[0.08432, 0.08432], hit=[0.84321, 0.84321], ndcg=[0.54454, 0.54454]
INFO:root:save the weights in path: model/run4_1_no_pri.pkl
INFO:root:Epoch 1909 [180.1s + 30.5s]: train==[104.72142=103.74770 + 0.97378], recall=[0.83891, 0.83891], precision=[0.08389, 0.08389], hit=[0.83891, 0.83891], ndcg=[0.54490, 0.54490]
INFO:root:Epoch 1919 [177.7s + 29.7s]: train==[103.92494=102.95071 + 0.97422], recall=[0.84106, 0.84106], precision=[0.08411, 0.08411], hit=[0.84106, 0.84106], ndcg=[0.54421, 0.54421]
INFO:root:Epoch 1929 [182.8s + 30.5s]: train==[102.45560=101.47633 + 0.97922], recall=[0.83775, 0.83775], precision=[0.08377, 0.08377], hit=[0.83775, 0.83775], ndcg=[0.54277, 0.54277]
INFO:root:Epoch 1939 [181.4s + 29.4s]: train==[101.74341=100.76129 + 0.98212], recall=[0.83758, 0.83758], precision=[0.08376, 0.08376], hit=[0.83758, 0.83758], ndcg=[0.54675, 0.54675]
INFO:root:Epoch 1949 [177.3s + 31.6s]: train==[101.98856=101.00483 + 0.98375], recall=[0.83758, 0.83758], precision=[0.08376, 0.08376], hit=[0.83758, 0.83758], ndcg=[0.54279, 0.54279]
INFO:root:Epoch 1959 [177.5s + 28.1s]: train==[100.24677=99.26048 + 0.98617], recall=[0.84123, 0.84123], precision=[0.08412, 0.08412], hit=[0.84123, 0.84123], ndcg=[0.54400, 0.54400]
INFO:root:Epoch 1969 [178.2s + 31.0s]: train==[99.33895=98.34940 + 0.98950], recall=[0.84056, 0.84056], precision=[0.08406, 0.08406], hit=[0.84056, 0.84056], ndcg=[0.54679, 0.54679]
INFO:root:Epoch 1979 [173.3s + 28.7s]: train==[100.88154=99.88976 + 0.99185], recall=[0.84040, 0.84040], precision=[0.08404, 0.08404], hit=[0.84040, 0.84040], ndcg=[0.54757, 0.54757]
INFO:root:Epoch 1989 [177.8s + 30.5s]: train==[100.67103=99.67506 + 0.99604], recall=[0.83791, 0.83791], precision=[0.08379, 0.08379], hit=[0.83791, 0.83791], ndcg=[0.54564, 0.54564]
INFO:root:Epoch 1999 [189.2s + 29.8s]: train==[98.97307=97.97475 + 0.99835], recall=[0.84007, 0.84007], precision=[0.08401, 0.08401], hit=[0.84007, 0.84007], ndcg=[0.54571, 0.54571]
INFO:root:Best Iter=[189]@[357424.8]	recall=[0.84321], precision=[0.08432], hit=[0.84321], ndcg=[0.54454]