console output.txt

+ bash run_main.sh
Loading acm dataset from local
****************************************Training loop No.1****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=1870, out_features=512, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.9031		nmi: 0.6751		ari: 0.7351		f1: 0.9029		
epoch: 002		acc: 0.4225		nmi: 0.1379		ari: 0.0174		f1: 0.3289		
epoch: 003		acc: 0.8919		nmi: 0.6760		ari: 0.7083		f1: 0.8916		
epoch: 004		acc: 0.8440		nmi: 0.6012		ari: 0.6130		f1: 0.8331		
epoch: 005		acc: 0.8863		nmi: 0.6605		ari: 0.6983		f1: 0.8826		
epoch: 006		acc: 0.9088		nmi: 0.6965		ari: 0.7504		f1: 0.9082		
epoch: 007		acc: 0.9114		nmi: 0.7061		ari: 0.7568		f1: 0.9114		
epoch: 008		acc: 0.9107		nmi: 0.7119		ari: 0.7563		f1: 0.9104		
epoch: 009		acc: 0.9074		nmi: 0.7020		ari: 0.7480		f1: 0.9066		
epoch: 010		acc: 0.9038		nmi: 0.6938		ari: 0.7391		f1: 0.9025		
epoch: 011		acc: 0.9038		nmi: 0.6928		ari: 0.7391		f1: 0.9022		
epoch: 012		acc: 0.9078		nmi: 0.7002		ari: 0.7482		f1: 0.9065		
epoch: 013		acc: 0.9164		nmi: 0.7148		ari: 0.7690		f1: 0.9157		
epoch: 014		acc: 0.9183		nmi: 0.7188		ari: 0.7738		f1: 0.9181		
epoch: 015		acc: 0.9217		nmi: 0.7258		ari: 0.7819		f1: 0.9217		
epoch: 016		acc: 0.9220		nmi: 0.7234		ari: 0.7822		f1: 0.9221		
epoch: 017		acc: 0.9223		nmi: 0.7240		ari: 0.7828		f1: 0.9226		
epoch: 018		acc: 0.9246		nmi: 0.7291		ari: 0.7890		f1: 0.9247		
epoch: 019		acc: 0.9243		nmi: 0.7280		ari: 0.7881		f1: 0.9243		
epoch: 020		acc: 0.9266		nmi: 0.7354		ari: 0.7941		f1: 0.9268		
epoch: 021		acc: 0.9250		nmi: 0.7302		ari: 0.7898		f1: 0.9251		
epoch: 022		acc: 0.9253		nmi: 0.7315		ari: 0.7907		f1: 0.9254		
epoch: 023		acc: 0.9263		nmi: 0.7342		ari: 0.7932		f1: 0.9264		
epoch: 024		acc: 0.9266		nmi: 0.7341		ari: 0.7940		f1: 0.9267		
epoch: 025		acc: 0.9253		nmi: 0.7305		ari: 0.7905		f1: 0.9255		
epoch: 026		acc: 0.9276		nmi: 0.7373		ari: 0.7966		f1: 0.9277		
epoch: 027		acc: 0.9276		nmi: 0.7371		ari: 0.7966		f1: 0.9277		
epoch: 028		acc: 0.9266		nmi: 0.7342		ari: 0.7938		f1: 0.9268		
epoch: 029		acc: 0.9263		nmi: 0.7331		ari: 0.7931		f1: 0.9264		
epoch: 030		acc: 0.9256		nmi: 0.7310		ari: 0.7913		f1: 0.9258		
epoch: 031		acc: 0.9263		nmi: 0.7318		ari: 0.7930		f1: 0.9264		
epoch: 032		acc: 0.9260		nmi: 0.7323		ari: 0.7922		f1: 0.9261		
epoch: 033		acc: 0.9256		nmi: 0.7315		ari: 0.7914		f1: 0.9258		
epoch: 034		acc: 0.9250		nmi: 0.7294		ari: 0.7897		f1: 0.9251		
epoch: 035		acc: 0.9263		nmi: 0.7335		ari: 0.7931		f1: 0.9265		
epoch: 036		acc: 0.9256		nmi: 0.7316		ari: 0.7913		f1: 0.9258		
epoch: 037		acc: 0.9256		nmi: 0.7312		ari: 0.7913		f1: 0.9258		
epoch: 038		acc: 0.9253		nmi: 0.7305		ari: 0.7905		f1: 0.9255		
epoch: 039		acc: 0.9263		nmi: 0.7319		ari: 0.7930		f1: 0.9264		
epoch: 040		acc: 0.9273		nmi: 0.7355		ari: 0.7955		f1: 0.9275		
epoch: 041		acc: 0.9256		nmi: 0.7310		ari: 0.7913		f1: 0.9258		
epoch: 042		acc: 0.9260		nmi: 0.7326		ari: 0.7922		f1: 0.9261		
epoch: 043		acc: 0.9269		nmi: 0.7346		ari: 0.7947		f1: 0.9271		
epoch: 044		acc: 0.9240		nmi: 0.7266		ari: 0.7869		f1: 0.9242		
epoch: 045		acc: 0.9263		nmi: 0.7328		ari: 0.7931		f1: 0.9264		
epoch: 046		acc: 0.9269		nmi: 0.7350		ari: 0.7948		f1: 0.9271		
epoch: 047		acc: 0.9260		nmi: 0.7315		ari: 0.7921		f1: 0.9261		
epoch: 048		acc: 0.9256		nmi: 0.7313		ari: 0.7913		f1: 0.9258		
epoch: 049		acc: 0.9263		nmi: 0.7325		ari: 0.7930		f1: 0.9264		
epoch: 050		acc: 0.9266		nmi: 0.7340		ari: 0.7939		f1: 0.9268		
The total number of parameters is: 1.093168M(1e6).
The max memory allocated to model is: 628.12 MB.
Time consuming: 7.13s or 0.12m
****************************************Training loop No.2****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=1870, out_features=512, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.9055		nmi: 0.6813		ari: 0.7408		f1: 0.9052		
epoch: 002		acc: 0.3921		nmi: 0.0997		ari: 0.0053		f1: 0.2814		
epoch: 003		acc: 0.8922		nmi: 0.6693		ari: 0.7086		f1: 0.8921		
epoch: 004		acc: 0.8258		nmi: 0.5794		ari: 0.5806		f1: 0.8111		
epoch: 005		acc: 0.8777		nmi: 0.6473		ari: 0.6789		f1: 0.8726		
epoch: 006		acc: 0.9084		nmi: 0.6955		ari: 0.7496		f1: 0.9075		
epoch: 007		acc: 0.9104		nmi: 0.7035		ari: 0.7547		f1: 0.9101		
epoch: 008		acc: 0.9117		nmi: 0.7126		ari: 0.7586		f1: 0.9114		
epoch: 009		acc: 0.9074		nmi: 0.7044		ari: 0.7481		f1: 0.9068		
epoch: 010		acc: 0.9025		nmi: 0.6904		ari: 0.7358		f1: 0.9012		
epoch: 011		acc: 0.9008		nmi: 0.6856		ari: 0.7319		f1: 0.8991		
epoch: 012		acc: 0.9064		nmi: 0.6958		ari: 0.7450		f1: 0.9050		
epoch: 013		acc: 0.9098		nmi: 0.7009		ari: 0.7529		f1: 0.9088		
epoch: 014		acc: 0.9203		nmi: 0.7230		ari: 0.7787		f1: 0.9201		
epoch: 015		acc: 0.9217		nmi: 0.7255		ari: 0.7820		f1: 0.9216		
epoch: 016		acc: 0.9230		nmi: 0.7254		ari: 0.7849		f1: 0.9230		
epoch: 017		acc: 0.9243		nmi: 0.7286		ari: 0.7880		f1: 0.9245		
epoch: 018		acc: 0.9236		nmi: 0.7265		ari: 0.7863		f1: 0.9238		
epoch: 019		acc: 0.9236		nmi: 0.7262		ari: 0.7863		f1: 0.9238		
epoch: 020		acc: 0.9243		nmi: 0.7276		ari: 0.7882		f1: 0.9243		
epoch: 021		acc: 0.9246		nmi: 0.7282		ari: 0.7889		f1: 0.9247		
epoch: 022		acc: 0.9250		nmi: 0.7292		ari: 0.7898		f1: 0.9249		
epoch: 023		acc: 0.9256		nmi: 0.7320		ari: 0.7915		f1: 0.9257		
epoch: 024		acc: 0.9256		nmi: 0.7322		ari: 0.7915		f1: 0.9257		
epoch: 025		acc: 0.9263		nmi: 0.7341		ari: 0.7933		f1: 0.9264		
epoch: 026		acc: 0.9256		nmi: 0.7336		ari: 0.7918		f1: 0.9257		
epoch: 027		acc: 0.9260		nmi: 0.7340		ari: 0.7924		f1: 0.9261		
epoch: 028		acc: 0.9263		nmi: 0.7347		ari: 0.7934		f1: 0.9263		
epoch: 029		acc: 0.9250		nmi: 0.7291		ari: 0.7897		f1: 0.9250		
epoch: 030		acc: 0.9273		nmi: 0.7376		ari: 0.7959		f1: 0.9274		
epoch: 031		acc: 0.9269		nmi: 0.7363		ari: 0.7950		f1: 0.9270		
epoch: 032		acc: 0.9266		nmi: 0.7353		ari: 0.7941		f1: 0.9267		
epoch: 033		acc: 0.9236		nmi: 0.7284		ari: 0.7865		f1: 0.9237		
epoch: 034		acc: 0.9260		nmi: 0.7328		ari: 0.7925		f1: 0.9260		
epoch: 035		acc: 0.9250		nmi: 0.7319		ari: 0.7899		f1: 0.9251		
epoch: 036		acc: 0.9253		nmi: 0.7312		ari: 0.7906		f1: 0.9254		
epoch: 037		acc: 0.9256		nmi: 0.7329		ari: 0.7916		f1: 0.9257		
epoch: 038		acc: 0.9273		nmi: 0.7368		ari: 0.7958		f1: 0.9274		
epoch: 039		acc: 0.9260		nmi: 0.7335		ari: 0.7923		f1: 0.9261		
epoch: 040		acc: 0.9256		nmi: 0.7332		ari: 0.7916		f1: 0.9257		
epoch: 041		acc: 0.9256		nmi: 0.7328		ari: 0.7915		f1: 0.9257		
epoch: 042		acc: 0.9273		nmi: 0.7368		ari: 0.7958		f1: 0.9274		
epoch: 043		acc: 0.9260		nmi: 0.7329		ari: 0.7923		f1: 0.9261		
epoch: 044		acc: 0.9266		nmi: 0.7351		ari: 0.7941		f1: 0.9267		
epoch: 045		acc: 0.9269		nmi: 0.7360		ari: 0.7949		f1: 0.9271		
epoch: 046		acc: 0.9260		nmi: 0.7329		ari: 0.7923		f1: 0.9261		
epoch: 047		acc: 0.9266		nmi: 0.7347		ari: 0.7941		f1: 0.9267		
epoch: 048		acc: 0.9253		nmi: 0.7305		ari: 0.7906		f1: 0.9254		
epoch: 049		acc: 0.9260		nmi: 0.7325		ari: 0.7923		f1: 0.9261		
epoch: 050		acc: 0.9266		nmi: 0.7351		ari: 0.7941		f1: 0.9267		
The total number of parameters is: 1.093168M(1e6).
The max memory allocated to model is: 636.85 MB.
Time consuming: 3.73s or 0.06m
****************************************Training loop No.3****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=1870, out_features=512, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.9031		nmi: 0.6760		ari: 0.7352		f1: 0.9029		
epoch: 002		acc: 0.4291		nmi: 0.1471		ari: 0.0190		f1: 0.3407		
epoch: 003		acc: 0.8899		nmi: 0.6696		ari: 0.7032		f1: 0.8896		
epoch: 004		acc: 0.8397		nmi: 0.5967		ari: 0.6049		f1: 0.8277		
epoch: 005		acc: 0.8869		nmi: 0.6611		ari: 0.6997		f1: 0.8834		
epoch: 006		acc: 0.9081		nmi: 0.6980		ari: 0.7488		f1: 0.9075		
epoch: 007		acc: 0.9117		nmi: 0.7092		ari: 0.7581		f1: 0.9116		
epoch: 008		acc: 0.9101		nmi: 0.7069		ari: 0.7541		f1: 0.9097		
epoch: 009		acc: 0.9061		nmi: 0.6990		ari: 0.7447		f1: 0.9050		
epoch: 010		acc: 0.8998		nmi: 0.6843		ari: 0.7297		f1: 0.8981		
epoch: 011		acc: 0.9025		nmi: 0.6887		ari: 0.7357		f1: 0.9008		
epoch: 012		acc: 0.9074		nmi: 0.6992		ari: 0.7477		f1: 0.9061		
epoch: 013		acc: 0.9147		nmi: 0.7133		ari: 0.7651		f1: 0.9140		
epoch: 014		acc: 0.9213		nmi: 0.7278		ari: 0.7815		f1: 0.9211		
epoch: 015		acc: 0.9220		nmi: 0.7261		ari: 0.7826		f1: 0.9220		
epoch: 016		acc: 0.9236		nmi: 0.7297		ari: 0.7867		f1: 0.9238		
epoch: 017		acc: 0.9233		nmi: 0.7258		ari: 0.7855		f1: 0.9235		
epoch: 018		acc: 0.9223		nmi: 0.7233		ari: 0.7830		f1: 0.9224		
epoch: 019		acc: 0.9260		nmi: 0.7346		ari: 0.7926		f1: 0.9260		
epoch: 020		acc: 0.9246		nmi: 0.7303		ari: 0.7891		f1: 0.9247		
epoch: 021		acc: 0.9243		nmi: 0.7291		ari: 0.7882		f1: 0.9244		
epoch: 022		acc: 0.9240		nmi: 0.7297		ari: 0.7876		f1: 0.9240		
epoch: 023		acc: 0.9250		nmi: 0.7318		ari: 0.7900		f1: 0.9250		
epoch: 024		acc: 0.9240		nmi: 0.7284		ari: 0.7873		f1: 0.9241		
epoch: 025		acc: 0.9240		nmi: 0.7293		ari: 0.7875		f1: 0.9240		
epoch: 026		acc: 0.9256		nmi: 0.7327		ari: 0.7916		f1: 0.9257		
epoch: 027		acc: 0.9276		nmi: 0.7394		ari: 0.7969		f1: 0.9276		
epoch: 028		acc: 0.9256		nmi: 0.7337		ari: 0.7918		f1: 0.9257		
epoch: 029		acc: 0.9250		nmi: 0.7314		ari: 0.7899		f1: 0.9251		
epoch: 030		acc: 0.9269		nmi: 0.7369		ari: 0.7951		f1: 0.9271		
epoch: 031		acc: 0.9260		nmi: 0.7331		ari: 0.7925		f1: 0.9260		
epoch: 032		acc: 0.9260		nmi: 0.7346		ari: 0.7926		f1: 0.9260		
epoch: 033		acc: 0.9246		nmi: 0.7311		ari: 0.7891		f1: 0.9248		
epoch: 034		acc: 0.9263		nmi: 0.7349		ari: 0.7933		f1: 0.9264		
epoch: 035		acc: 0.9226		nmi: 0.7247		ari: 0.7840		f1: 0.9226		
epoch: 036		acc: 0.9240		nmi: 0.7284		ari: 0.7874		f1: 0.9240		
epoch: 037		acc: 0.9253		nmi: 0.7324		ari: 0.7908		f1: 0.9254		
epoch: 038		acc: 0.9236		nmi: 0.7269		ari: 0.7865		f1: 0.9237		
epoch: 039		acc: 0.9226		nmi: 0.7245		ari: 0.7840		f1: 0.9227		
epoch: 040		acc: 0.9250		nmi: 0.7313		ari: 0.7899		f1: 0.9251		
epoch: 041		acc: 0.9256		nmi: 0.7331		ari: 0.7917		f1: 0.9257		
epoch: 042		acc: 0.9250		nmi: 0.7305		ari: 0.7898		f1: 0.9251		
epoch: 043		acc: 0.9246		nmi: 0.7300		ari: 0.7890		f1: 0.9247		
epoch: 044		acc: 0.9253		nmi: 0.7319		ari: 0.7908		f1: 0.9254		
epoch: 045		acc: 0.9240		nmi: 0.7274		ari: 0.7873		f1: 0.9241		
epoch: 046		acc: 0.9253		nmi: 0.7316		ari: 0.7908		f1: 0.9254		
epoch: 047		acc: 0.9256		nmi: 0.7327		ari: 0.7916		f1: 0.9258		
epoch: 048		acc: 0.9260		nmi: 0.7334		ari: 0.7925		f1: 0.9260		
epoch: 049		acc: 0.9240		nmi: 0.7277		ari: 0.7872		f1: 0.9241		
epoch: 050		acc: 0.9253		nmi: 0.7317		ari: 0.7907		f1: 0.9254		
The total number of parameters is: 1.093168M(1e6).
The max memory allocated to model is: 636.85 MB.
Time consuming: 3.66s or 0.06m
****************************************Training loop No.4****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=1870, out_features=512, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.9031		nmi: 0.6751		ari: 0.7352		f1: 0.9028		
epoch: 002		acc: 0.4235		nmi: 0.1382		ari: 0.0162		f1: 0.3327		
epoch: 003		acc: 0.8909		nmi: 0.6732		ari: 0.7062		f1: 0.8905		
epoch: 004		acc: 0.8393		nmi: 0.5910		ari: 0.6028		f1: 0.8276		
epoch: 005		acc: 0.8866		nmi: 0.6574		ari: 0.6983		f1: 0.8833		
epoch: 006		acc: 0.9084		nmi: 0.6961		ari: 0.7495		f1: 0.9079		
epoch: 007		acc: 0.9094		nmi: 0.6988		ari: 0.7518		f1: 0.9092		
epoch: 008		acc: 0.9098		nmi: 0.7056		ari: 0.7534		f1: 0.9093		
epoch: 009		acc: 0.9041		nmi: 0.6932		ari: 0.7402		f1: 0.9030		
epoch: 010		acc: 0.9035		nmi: 0.6911		ari: 0.7380		f1: 0.9020		
epoch: 011		acc: 0.9045		nmi: 0.6926		ari: 0.7405		f1: 0.9029		
epoch: 012		acc: 0.9064		nmi: 0.6938		ari: 0.7449		f1: 0.9053		
epoch: 013		acc: 0.9164		nmi: 0.7128		ari: 0.7687		f1: 0.9159		
epoch: 014		acc: 0.9200		nmi: 0.7195		ari: 0.7777		f1: 0.9197		
epoch: 015		acc: 0.9210		nmi: 0.7196		ari: 0.7797		f1: 0.9210		
epoch: 016		acc: 0.9230		nmi: 0.7237		ari: 0.7846		f1: 0.9231		
epoch: 017		acc: 0.9256		nmi: 0.7304		ari: 0.7913		f1: 0.9257		
epoch: 018		acc: 0.9246		nmi: 0.7271		ari: 0.7888		f1: 0.9246		
epoch: 019		acc: 0.9236		nmi: 0.7242		ari: 0.7863		f1: 0.9236		
epoch: 020		acc: 0.9223		nmi: 0.7228		ari: 0.7831		f1: 0.9223		
epoch: 021		acc: 0.9233		nmi: 0.7244		ari: 0.7855		f1: 0.9233		
epoch: 022		acc: 0.9253		nmi: 0.7295		ari: 0.7904		f1: 0.9254		
epoch: 023		acc: 0.9256		nmi: 0.7316		ari: 0.7914		f1: 0.9257		
epoch: 024		acc: 0.9273		nmi: 0.7361		ari: 0.7957		f1: 0.9274		
epoch: 025		acc: 0.9246		nmi: 0.7281		ari: 0.7888		f1: 0.9247		
epoch: 026		acc: 0.9250		nmi: 0.7287		ari: 0.7897		f1: 0.9250		
epoch: 027		acc: 0.9266		nmi: 0.7328		ari: 0.7939		f1: 0.9267		
epoch: 028		acc: 0.9266		nmi: 0.7330		ari: 0.7938		f1: 0.9267		
epoch: 029		acc: 0.9243		nmi: 0.7269		ari: 0.7878		f1: 0.9244		
epoch: 030		acc: 0.9269		nmi: 0.7339		ari: 0.7947		f1: 0.9271		
epoch: 031		acc: 0.9260		nmi: 0.7309		ari: 0.7921		f1: 0.9261		
epoch: 032		acc: 0.9243		nmi: 0.7264		ari: 0.7879		f1: 0.9244		
epoch: 033		acc: 0.9256		nmi: 0.7300		ari: 0.7912		f1: 0.9257		
epoch: 034		acc: 0.9250		nmi: 0.7286		ari: 0.7896		f1: 0.9251		
epoch: 035		acc: 0.9260		nmi: 0.7314		ari: 0.7921		f1: 0.9261		
epoch: 036		acc: 0.9263		nmi: 0.7315		ari: 0.7929		f1: 0.9264		
epoch: 037		acc: 0.9260		nmi: 0.7311		ari: 0.7922		f1: 0.9261		
epoch: 038		acc: 0.9240		nmi: 0.7250		ari: 0.7868		f1: 0.9241		
epoch: 039		acc: 0.9253		nmi: 0.7292		ari: 0.7903		f1: 0.9254		
epoch: 040		acc: 0.9250		nmi: 0.7277		ari: 0.7895		f1: 0.9250		
epoch: 041		acc: 0.9256		nmi: 0.7301		ari: 0.7912		f1: 0.9257		
epoch: 042		acc: 0.9263		nmi: 0.7316		ari: 0.7929		f1: 0.9264		
epoch: 043		acc: 0.9253		nmi: 0.7292		ari: 0.7903		f1: 0.9255		
epoch: 044		acc: 0.9253		nmi: 0.7286		ari: 0.7903		f1: 0.9254		
epoch: 045		acc: 0.9263		nmi: 0.7315		ari: 0.7929		f1: 0.9264		
epoch: 046		acc: 0.9253		nmi: 0.7290		ari: 0.7903		f1: 0.9255		
epoch: 047		acc: 0.9273		nmi: 0.7344		ari: 0.7955		f1: 0.9274		
epoch: 048		acc: 0.9250		nmi: 0.7276		ari: 0.7894		f1: 0.9251		
epoch: 049		acc: 0.9253		nmi: 0.7280		ari: 0.7902		f1: 0.9254		
epoch: 050		acc: 0.9266		nmi: 0.7324		ari: 0.7938		f1: 0.9267		
The total number of parameters is: 1.093168M(1e6).
The max memory allocated to model is: 636.85 MB.
Time consuming: 3.67s or 0.06m
****************************************Training loop No.5****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=1870, out_features=512, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.9048		nmi: 0.6802		ari: 0.7392		f1: 0.9047		
epoch: 002		acc: 0.3993		nmi: 0.1101		ari: 0.0075		f1: 0.2930		
epoch: 003		acc: 0.8893		nmi: 0.6643		ari: 0.7012		f1: 0.8890		
epoch: 004		acc: 0.8298		nmi: 0.5826		ari: 0.5871		f1: 0.8161		
epoch: 005		acc: 0.8770		nmi: 0.6444		ari: 0.6777		f1: 0.8719		
epoch: 006		acc: 0.9094		nmi: 0.6990		ari: 0.7521		f1: 0.9086		
epoch: 007		acc: 0.9101		nmi: 0.7014		ari: 0.7536		f1: 0.9098		
epoch: 008		acc: 0.9094		nmi: 0.7077		ari: 0.7528		f1: 0.9093		
epoch: 009		acc: 0.9098		nmi: 0.7084		ari: 0.7537		f1: 0.9092		
epoch: 010		acc: 0.9055		nmi: 0.6963		ari: 0.7432		f1: 0.9043		
epoch: 011		acc: 0.9025		nmi: 0.6898		ari: 0.7360		f1: 0.9008		
epoch: 012		acc: 0.9058		nmi: 0.6937		ari: 0.7434		f1: 0.9045		
epoch: 013		acc: 0.9144		nmi: 0.7098		ari: 0.7641		f1: 0.9137		
epoch: 014		acc: 0.9190		nmi: 0.7185		ari: 0.7754		f1: 0.9187		
epoch: 015		acc: 0.9217		nmi: 0.7236		ari: 0.7818		f1: 0.9215		
epoch: 016		acc: 0.9230		nmi: 0.7252		ari: 0.7848		f1: 0.9230		
epoch: 017		acc: 0.9230		nmi: 0.7243		ari: 0.7845		f1: 0.9231		
epoch: 018		acc: 0.9243		nmi: 0.7272		ari: 0.7878		f1: 0.9245		
epoch: 019		acc: 0.9250		nmi: 0.7279		ari: 0.7895		f1: 0.9251		
epoch: 020		acc: 0.9246		nmi: 0.7274		ari: 0.7887		f1: 0.9248		
epoch: 021		acc: 0.9269		nmi: 0.7335		ari: 0.7948		f1: 0.9270		
epoch: 022		acc: 0.9250		nmi: 0.7293		ari: 0.7898		f1: 0.9250		
epoch: 023		acc: 0.9246		nmi: 0.7273		ari: 0.7888		f1: 0.9247		
epoch: 024		acc: 0.9279		nmi: 0.7370		ari: 0.7974		f1: 0.9280		
epoch: 025		acc: 0.9253		nmi: 0.7295		ari: 0.7905		f1: 0.9254		
epoch: 026		acc: 0.9243		nmi: 0.7266		ari: 0.7879		f1: 0.9244		
epoch: 027		acc: 0.9246		nmi: 0.7276		ari: 0.7887		f1: 0.9248		
epoch: 028		acc: 0.9260		nmi: 0.7311		ari: 0.7921		f1: 0.9261		
epoch: 029		acc: 0.9263		nmi: 0.7316		ari: 0.7929		f1: 0.9264		
epoch: 030		acc: 0.9273		nmi: 0.7345		ari: 0.7955		f1: 0.9275		
epoch: 031		acc: 0.9253		nmi: 0.7294		ari: 0.7903		f1: 0.9255		
epoch: 032		acc: 0.9266		nmi: 0.7317		ari: 0.7937		f1: 0.9267		
epoch: 033		acc: 0.9253		nmi: 0.7284		ari: 0.7902		f1: 0.9255		
epoch: 034		acc: 0.9256		nmi: 0.7289		ari: 0.7910		f1: 0.9258		
epoch: 035		acc: 0.9253		nmi: 0.7284		ari: 0.7902		f1: 0.9255		
epoch: 036		acc: 0.9260		nmi: 0.7304		ari: 0.7920		f1: 0.9261		
epoch: 037		acc: 0.9266		nmi: 0.7320		ari: 0.7936		f1: 0.9268		
epoch: 038		acc: 0.9256		nmi: 0.7287		ari: 0.7910		f1: 0.9258		
epoch: 039		acc: 0.9250		nmi: 0.7271		ari: 0.7893		f1: 0.9251		
epoch: 040		acc: 0.9260		nmi: 0.7302		ari: 0.7919		f1: 0.9261		
epoch: 041		acc: 0.9263		nmi: 0.7305		ari: 0.7928		f1: 0.9264		
epoch: 042		acc: 0.9260		nmi: 0.7302		ari: 0.7919		f1: 0.9261		
epoch: 043		acc: 0.9243		nmi: 0.7257		ari: 0.7875		f1: 0.9245		
epoch: 044		acc: 0.9266		nmi: 0.7320		ari: 0.7937		f1: 0.9268		
epoch: 045		acc: 0.9246		nmi: 0.7265		ari: 0.7884		f1: 0.9248		
epoch: 046		acc: 0.9269		nmi: 0.7326		ari: 0.7945		f1: 0.9271		
epoch: 047		acc: 0.9253		nmi: 0.7282		ari: 0.7901		f1: 0.9255		
epoch: 048		acc: 0.9263		nmi: 0.7309		ari: 0.7927		f1: 0.9265		
epoch: 049		acc: 0.9253		nmi: 0.7276		ari: 0.7901		f1: 0.9254		
epoch: 050		acc: 0.9250		nmi: 0.7271		ari: 0.7893		f1: 0.9252		
The total number of parameters is: 1.093168M(1e6).
The max memory allocated to model is: 636.85 MB.
Time consuming: 3.75s or 0.06m
****************************************Training loop No.6****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=1870, out_features=512, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.9061		nmi: 0.6845		ari: 0.7425		f1: 0.9059		
epoch: 002		acc: 0.3914		nmi: 0.0986		ari: 0.0049		f1: 0.2809		
epoch: 003		acc: 0.8936		nmi: 0.6725		ari: 0.7117		f1: 0.8933		
epoch: 004		acc: 0.8221		nmi: 0.5728		ari: 0.5737		f1: 0.8067		
epoch: 005		acc: 0.8797		nmi: 0.6480		ari: 0.6827		f1: 0.8751		
epoch: 006		acc: 0.9058		nmi: 0.6862		ari: 0.7426		f1: 0.9050		
epoch: 007		acc: 0.9104		nmi: 0.7000		ari: 0.7540		f1: 0.9103		
epoch: 008		acc: 0.9121		nmi: 0.7102		ari: 0.7589		f1: 0.9118		
epoch: 009		acc: 0.9081		nmi: 0.7033		ari: 0.7497		f1: 0.9072		
epoch: 010		acc: 0.9055		nmi: 0.6969		ari: 0.7431		f1: 0.9043		
epoch: 011		acc: 0.9045		nmi: 0.6944		ari: 0.7407		f1: 0.9029		
epoch: 012		acc: 0.9061		nmi: 0.6973		ari: 0.7447		f1: 0.9046		
epoch: 013		acc: 0.9134		nmi: 0.7073		ari: 0.7617		f1: 0.9124		
epoch: 014		acc: 0.9170		nmi: 0.7142		ari: 0.7705		f1: 0.9165		
epoch: 015		acc: 0.9220		nmi: 0.7238		ari: 0.7826		f1: 0.9218		
epoch: 016		acc: 0.9243		nmi: 0.7289		ari: 0.7882		f1: 0.9244		
epoch: 017		acc: 0.9243		nmi: 0.7280		ari: 0.7881		f1: 0.9244		
epoch: 018		acc: 0.9253		nmi: 0.7294		ari: 0.7902		f1: 0.9255		
epoch: 019		acc: 0.9230		nmi: 0.7217		ari: 0.7843		f1: 0.9231		
epoch: 020		acc: 0.9240		nmi: 0.7233		ari: 0.7867		f1: 0.9240		
epoch: 021		acc: 0.9240		nmi: 0.7247		ari: 0.7868		f1: 0.9241		
epoch: 022		acc: 0.9253		nmi: 0.7270		ari: 0.7902		f1: 0.9253		
epoch: 023		acc: 0.9250		nmi: 0.7265		ari: 0.7895		f1: 0.9250		
epoch: 024		acc: 0.9250		nmi: 0.7275		ari: 0.7895		f1: 0.9250		
epoch: 025		acc: 0.9260		nmi: 0.7300		ari: 0.7919		f1: 0.9261		
epoch: 026		acc: 0.9256		nmi: 0.7300		ari: 0.7911		f1: 0.9258		
epoch: 027		acc: 0.9253		nmi: 0.7289		ari: 0.7902		f1: 0.9255		
epoch: 028		acc: 0.9253		nmi: 0.7278		ari: 0.7902		f1: 0.9254		
epoch: 029		acc: 0.9250		nmi: 0.7269		ari: 0.7892		f1: 0.9251		
epoch: 030		acc: 0.9256		nmi: 0.7284		ari: 0.7909		f1: 0.9258		
epoch: 031		acc: 0.9250		nmi: 0.7267		ari: 0.7893		f1: 0.9251		
epoch: 032		acc: 0.9253		nmi: 0.7271		ari: 0.7900		f1: 0.9255		
epoch: 033		acc: 0.9250		nmi: 0.7262		ari: 0.7892		f1: 0.9251		
epoch: 034		acc: 0.9250		nmi: 0.7267		ari: 0.7893		f1: 0.9251		
epoch: 035		acc: 0.9263		nmi: 0.7301		ari: 0.7927		f1: 0.9264		
epoch: 036		acc: 0.9246		nmi: 0.7252		ari: 0.7883		f1: 0.9248		
epoch: 037		acc: 0.9246		nmi: 0.7254		ari: 0.7884		f1: 0.9248		
epoch: 038		acc: 0.9253		nmi: 0.7271		ari: 0.7901		f1: 0.9254		
epoch: 039		acc: 0.9253		nmi: 0.7280		ari: 0.7902		f1: 0.9254		
epoch: 040		acc: 0.9263		nmi: 0.7304		ari: 0.7927		f1: 0.9264		
epoch: 041		acc: 0.9250		nmi: 0.7265		ari: 0.7893		f1: 0.9251		
epoch: 042		acc: 0.9250		nmi: 0.7263		ari: 0.7893		f1: 0.9251		
epoch: 043		acc: 0.9260		nmi: 0.7298		ari: 0.7920		f1: 0.9261		
epoch: 044		acc: 0.9266		nmi: 0.7313		ari: 0.7937		f1: 0.9267		
epoch: 045		acc: 0.9260		nmi: 0.7293		ari: 0.7919		f1: 0.9261		
epoch: 046		acc: 0.9250		nmi: 0.7271		ari: 0.7893		f1: 0.9251		
epoch: 047		acc: 0.9256		nmi: 0.7280		ari: 0.7909		f1: 0.9258		
epoch: 048		acc: 0.9256		nmi: 0.7288		ari: 0.7911		f1: 0.9257		
epoch: 049		acc: 0.9260		nmi: 0.7296		ari: 0.7919		f1: 0.9261		
epoch: 050		acc: 0.9256		nmi: 0.7288		ari: 0.7911		f1: 0.9257		
The total number of parameters is: 1.093168M(1e6).
The max memory allocated to model is: 636.85 MB.
Time consuming: 3.69s or 0.06m
****************************************Training loop No.7****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=1870, out_features=512, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.9028		nmi: 0.6753		ari: 0.7343		f1: 0.9026		
epoch: 002		acc: 0.4301		nmi: 0.1501		ari: 0.0222		f1: 0.3389		
epoch: 003		acc: 0.8860		nmi: 0.6632		ari: 0.6941		f1: 0.8855		
epoch: 004		acc: 0.8476		nmi: 0.6043		ari: 0.6182		f1: 0.8380		
epoch: 005		acc: 0.8853		nmi: 0.6574		ari: 0.6960		f1: 0.8815		
epoch: 006		acc: 0.9094		nmi: 0.7008		ari: 0.7521		f1: 0.9088		
epoch: 007		acc: 0.9091		nmi: 0.7001		ari: 0.7511		f1: 0.9089		
epoch: 008		acc: 0.9071		nmi: 0.7012		ari: 0.7471		f1: 0.9066		
epoch: 009		acc: 0.9081		nmi: 0.7051		ari: 0.7498		f1: 0.9074		
epoch: 010		acc: 0.9041		nmi: 0.6948		ari: 0.7400		f1: 0.9029		
epoch: 011		acc: 0.9055		nmi: 0.6961		ari: 0.7430		f1: 0.9040		
epoch: 012		acc: 0.9091		nmi: 0.7005		ari: 0.7513		f1: 0.9081		
epoch: 013		acc: 0.9160		nmi: 0.7136		ari: 0.7680		f1: 0.9156		
epoch: 014		acc: 0.9226		nmi: 0.7275		ari: 0.7844		f1: 0.9225		
epoch: 015		acc: 0.9236		nmi: 0.7274		ari: 0.7865		f1: 0.9236		
epoch: 016		acc: 0.9233		nmi: 0.7260		ari: 0.7856		f1: 0.9234		
epoch: 017		acc: 0.9226		nmi: 0.7237		ari: 0.7839		f1: 0.9227		
epoch: 018		acc: 0.9246		nmi: 0.7280		ari: 0.7888		f1: 0.9247		
epoch: 019		acc: 0.9250		nmi: 0.7294		ari: 0.7897		f1: 0.9250		
epoch: 020		acc: 0.9253		nmi: 0.7299		ari: 0.7905		f1: 0.9254		
epoch: 021		acc: 0.9236		nmi: 0.7257		ari: 0.7862		f1: 0.9238		
epoch: 022		acc: 0.9253		nmi: 0.7303		ari: 0.7906		f1: 0.9254		
epoch: 023		acc: 0.9256		nmi: 0.7314		ari: 0.7914		f1: 0.9258		
epoch: 024		acc: 0.9263		nmi: 0.7329		ari: 0.7931		f1: 0.9264		
epoch: 025		acc: 0.9263		nmi: 0.7333		ari: 0.7930		f1: 0.9264		
epoch: 026		acc: 0.9246		nmi: 0.7287		ari: 0.7889		f1: 0.9247		
epoch: 027		acc: 0.9263		nmi: 0.7336		ari: 0.7932		f1: 0.9264		
epoch: 028		acc: 0.9240		nmi: 0.7262		ari: 0.7872		f1: 0.9240		
epoch: 029		acc: 0.9253		nmi: 0.7291		ari: 0.7905		f1: 0.9253		
epoch: 030		acc: 0.9250		nmi: 0.7284		ari: 0.7896		f1: 0.9250		
epoch: 031		acc: 0.9266		nmi: 0.7337		ari: 0.7940		f1: 0.9267		
epoch: 032		acc: 0.9253		nmi: 0.7295		ari: 0.7905		f1: 0.9253		
epoch: 033		acc: 0.9256		nmi: 0.7307		ari: 0.7913		f1: 0.9257		
epoch: 034		acc: 0.9246		nmi: 0.7278		ari: 0.7887		f1: 0.9248		
epoch: 035		acc: 0.9260		nmi: 0.7321		ari: 0.7922		f1: 0.9261		
epoch: 036		acc: 0.9253		nmi: 0.7294		ari: 0.7904		f1: 0.9254		
epoch: 037		acc: 0.9250		nmi: 0.7290		ari: 0.7896		f1: 0.9251		
epoch: 038		acc: 0.9263		nmi: 0.7319		ari: 0.7931		f1: 0.9263		
epoch: 039		acc: 0.9250		nmi: 0.7287		ari: 0.7896		f1: 0.9251		
epoch: 040		acc: 0.9253		nmi: 0.7297		ari: 0.7905		f1: 0.9254		
epoch: 041		acc: 0.9243		nmi: 0.7264		ari: 0.7878		f1: 0.9244		
epoch: 042		acc: 0.9260		nmi: 0.7311		ari: 0.7922		f1: 0.9260		
epoch: 043		acc: 0.9246		nmi: 0.7277		ari: 0.7888		f1: 0.9247		
epoch: 044		acc: 0.9253		nmi: 0.7295		ari: 0.7904		f1: 0.9254		
epoch: 045		acc: 0.9253		nmi: 0.7294		ari: 0.7905		f1: 0.9254		
epoch: 046		acc: 0.9253		nmi: 0.7299		ari: 0.7904		f1: 0.9254		
epoch: 047		acc: 0.9240		nmi: 0.7254		ari: 0.7869		f1: 0.9241		
epoch: 048		acc: 0.9263		nmi: 0.7319		ari: 0.7930		f1: 0.9264		
epoch: 049		acc: 0.9260		nmi: 0.7314		ari: 0.7921		f1: 0.9261		
epoch: 050		acc: 0.9243		nmi: 0.7265		ari: 0.7878		f1: 0.9244		
The total number of parameters is: 1.093168M(1e6).
The max memory allocated to model is: 636.85 MB.
Time consuming: 3.67s or 0.06m
****************************************Training loop No.8****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=1870, out_features=512, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.9061		nmi: 0.6829		ari: 0.7424		f1: 0.9059		
epoch: 002		acc: 0.4000		nmi: 0.1084		ari: 0.0074		f1: 0.2945		
epoch: 003		acc: 0.8945		nmi: 0.6782		ari: 0.7143		f1: 0.8943		
epoch: 004		acc: 0.8357		nmi: 0.5919		ari: 0.5978		f1: 0.8232		
epoch: 005		acc: 0.8807		nmi: 0.6500		ari: 0.6853		f1: 0.8763		
epoch: 006		acc: 0.9084		nmi: 0.6969		ari: 0.7494		f1: 0.9078		
epoch: 007		acc: 0.9107		nmi: 0.7035		ari: 0.7552		f1: 0.9107		
epoch: 008		acc: 0.9104		nmi: 0.7082		ari: 0.7551		f1: 0.9101		
epoch: 009		acc: 0.9081		nmi: 0.7041		ari: 0.7496		f1: 0.9074		
epoch: 010		acc: 0.9028		nmi: 0.6901		ari: 0.7365		f1: 0.9014		
epoch: 011		acc: 0.9045		nmi: 0.6924		ari: 0.7403		f1: 0.9029		
epoch: 012		acc: 0.9074		nmi: 0.6959		ari: 0.7472		f1: 0.9062		
epoch: 013		acc: 0.9131		nmi: 0.7065		ari: 0.7609		f1: 0.9123		
epoch: 014		acc: 0.9200		nmi: 0.7217		ari: 0.7779		f1: 0.9197		
epoch: 015		acc: 0.9203		nmi: 0.7189		ari: 0.7781		f1: 0.9203		
epoch: 016		acc: 0.9230		nmi: 0.7255		ari: 0.7848		f1: 0.9231		
epoch: 017		acc: 0.9223		nmi: 0.7229		ari: 0.7830		f1: 0.9224		
epoch: 018		acc: 0.9250		nmi: 0.7296		ari: 0.7897		f1: 0.9251		
epoch: 019		acc: 0.9233		nmi: 0.7227		ari: 0.7853		f1: 0.9233		
epoch: 020		acc: 0.9260		nmi: 0.7308		ari: 0.7922		f1: 0.9260		
epoch: 021		acc: 0.9240		nmi: 0.7258		ari: 0.7871		f1: 0.9240		
epoch: 022		acc: 0.9256		nmi: 0.7289		ari: 0.7911		f1: 0.9258		
epoch: 023		acc: 0.9246		nmi: 0.7280		ari: 0.7888		f1: 0.9248		
epoch: 024		acc: 0.9243		nmi: 0.7279		ari: 0.7880		f1: 0.9244		
epoch: 025		acc: 0.9263		nmi: 0.7333		ari: 0.7930		f1: 0.9265		
epoch: 026		acc: 0.9256		nmi: 0.7307		ari: 0.7914		f1: 0.9257		
epoch: 027		acc: 0.9250		nmi: 0.7294		ari: 0.7896		f1: 0.9251		
epoch: 028		acc: 0.9256		nmi: 0.7312		ari: 0.7913		f1: 0.9258		
epoch: 029		acc: 0.9263		nmi: 0.7324		ari: 0.7930		f1: 0.9264		
epoch: 030		acc: 0.9263		nmi: 0.7328		ari: 0.7930		f1: 0.9265		
epoch: 031		acc: 0.9256		nmi: 0.7308		ari: 0.7913		f1: 0.9258		
epoch: 032		acc: 0.9250		nmi: 0.7277		ari: 0.7895		f1: 0.9251		
epoch: 033		acc: 0.9246		nmi: 0.7273		ari: 0.7887		f1: 0.9247		
epoch: 034		acc: 0.9256		nmi: 0.7297		ari: 0.7912		f1: 0.9257		
epoch: 035		acc: 0.9263		nmi: 0.7333		ari: 0.7930		f1: 0.9265		
epoch: 036		acc: 0.9260		nmi: 0.7311		ari: 0.7921		f1: 0.9261		
epoch: 037		acc: 0.9269		nmi: 0.7346		ari: 0.7947		f1: 0.9271		
epoch: 038		acc: 0.9250		nmi: 0.7280		ari: 0.7895		f1: 0.9251		
epoch: 039		acc: 0.9250		nmi: 0.7287		ari: 0.7895		f1: 0.9251		
epoch: 040		acc: 0.9250		nmi: 0.7281		ari: 0.7894		f1: 0.9251		
epoch: 041		acc: 0.9240		nmi: 0.7252		ari: 0.7869		f1: 0.9241		
epoch: 042		acc: 0.9256		nmi: 0.7302		ari: 0.7912		f1: 0.9258		
epoch: 043		acc: 0.9260		nmi: 0.7312		ari: 0.7921		f1: 0.9261		
epoch: 044		acc: 0.9256		nmi: 0.7302		ari: 0.7912		f1: 0.9258		
epoch: 045		acc: 0.9256		nmi: 0.7303		ari: 0.7912		f1: 0.9258		
epoch: 046		acc: 0.9253		nmi: 0.7288		ari: 0.7903		f1: 0.9254		
epoch: 047		acc: 0.9236		nmi: 0.7247		ari: 0.7860		f1: 0.9238		
epoch: 048		acc: 0.9253		nmi: 0.7290		ari: 0.7903		f1: 0.9254		
epoch: 049		acc: 0.9246		nmi: 0.7276		ari: 0.7886		f1: 0.9248		
epoch: 050		acc: 0.9246		nmi: 0.7271		ari: 0.7885		f1: 0.9248		
The total number of parameters is: 1.093168M(1e6).
The max memory allocated to model is: 636.85 MB.
Time consuming: 3.72s or 0.06m
****************************************Training loop No.9****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=1870, out_features=512, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.9031		nmi: 0.6746		ari: 0.7350		f1: 0.9028		
epoch: 002		acc: 0.3871		nmi: 0.0923		ari: 0.0037		f1: 0.2748		
epoch: 003		acc: 0.8949		nmi: 0.6772		ari: 0.7152		f1: 0.8948		
epoch: 004		acc: 0.8208		nmi: 0.5724		ari: 0.5722		f1: 0.8052		
epoch: 005		acc: 0.8770		nmi: 0.6440		ari: 0.6774		f1: 0.8721		
epoch: 006		acc: 0.9078		nmi: 0.6931		ari: 0.7479		f1: 0.9069		
epoch: 007		acc: 0.9117		nmi: 0.7035		ari: 0.7574		f1: 0.9117		
epoch: 008		acc: 0.9107		nmi: 0.7060		ari: 0.7557		f1: 0.9104		
epoch: 009		acc: 0.9074		nmi: 0.7009		ari: 0.7478		f1: 0.9065		
epoch: 010		acc: 0.9008		nmi: 0.6883		ari: 0.7325		f1: 0.8991		
epoch: 011		acc: 0.9015		nmi: 0.6891		ari: 0.7338		f1: 0.8996		
epoch: 012		acc: 0.9055		nmi: 0.6965		ari: 0.7433		f1: 0.9038		
epoch: 013		acc: 0.9114		nmi: 0.7075		ari: 0.7573		f1: 0.9104		
epoch: 014		acc: 0.9160		nmi: 0.7138		ari: 0.7681		f1: 0.9155		
epoch: 015		acc: 0.9203		nmi: 0.7217		ari: 0.7786		f1: 0.9201		
epoch: 016		acc: 0.9200		nmi: 0.7187		ari: 0.7774		f1: 0.9199		
epoch: 017		acc: 0.9236		nmi: 0.7265		ari: 0.7863		f1: 0.9238		
epoch: 018		acc: 0.9230		nmi: 0.7237		ari: 0.7846		f1: 0.9231		
epoch: 019		acc: 0.9223		nmi: 0.7218		ari: 0.7829		f1: 0.9224		
epoch: 020		acc: 0.9250		nmi: 0.7290		ari: 0.7898		f1: 0.9250		
epoch: 021		acc: 0.9260		nmi: 0.7308		ari: 0.7924		f1: 0.9259		
epoch: 022		acc: 0.9223		nmi: 0.7231		ari: 0.7830		f1: 0.9224		
epoch: 023		acc: 0.9240		nmi: 0.7273		ari: 0.7874		f1: 0.9240		
epoch: 024		acc: 0.9273		nmi: 0.7347		ari: 0.7958		f1: 0.9272		
epoch: 025		acc: 0.9250		nmi: 0.7295		ari: 0.7898		f1: 0.9250		
epoch: 026		acc: 0.9269		nmi: 0.7340		ari: 0.7949		f1: 0.9269		
epoch: 027		acc: 0.9253		nmi: 0.7297		ari: 0.7906		f1: 0.9253		
epoch: 028		acc: 0.9256		nmi: 0.7315		ari: 0.7915		f1: 0.9257		
epoch: 029		acc: 0.9256		nmi: 0.7304		ari: 0.7915		f1: 0.9256		
epoch: 030		acc: 0.9269		nmi: 0.7336		ari: 0.7949		f1: 0.9270		
epoch: 031		acc: 0.9253		nmi: 0.7294		ari: 0.7905		f1: 0.9254		
epoch: 032		acc: 0.9253		nmi: 0.7290		ari: 0.7905		f1: 0.9253		
epoch: 033		acc: 0.9260		nmi: 0.7308		ari: 0.7922		f1: 0.9260		
epoch: 034		acc: 0.9263		nmi: 0.7325		ari: 0.7931		f1: 0.9264		
epoch: 035		acc: 0.9266		nmi: 0.7318		ari: 0.7938		f1: 0.9267		
epoch: 036		acc: 0.9263		nmi: 0.7311		ari: 0.7929		f1: 0.9264		
epoch: 037		acc: 0.9256		nmi: 0.7301		ari: 0.7913		f1: 0.9257		
epoch: 038		acc: 0.9276		nmi: 0.7349		ari: 0.7964		f1: 0.9277		
epoch: 039		acc: 0.9263		nmi: 0.7314		ari: 0.7929		f1: 0.9264		
epoch: 040		acc: 0.9263		nmi: 0.7314		ari: 0.7929		f1: 0.9264		
epoch: 041		acc: 0.9260		nmi: 0.7310		ari: 0.7922		f1: 0.9260		
epoch: 042		acc: 0.9260		nmi: 0.7303		ari: 0.7922		f1: 0.9260		
epoch: 043		acc: 0.9250		nmi: 0.7279		ari: 0.7895		f1: 0.9251		
epoch: 044		acc: 0.9269		nmi: 0.7341		ari: 0.7948		f1: 0.9270		
epoch: 045		acc: 0.9256		nmi: 0.7295		ari: 0.7912		f1: 0.9258		
epoch: 046		acc: 0.9253		nmi: 0.7284		ari: 0.7904		f1: 0.9254		
epoch: 047		acc: 0.9266		nmi: 0.7323		ari: 0.7938		f1: 0.9267		
epoch: 048		acc: 0.9250		nmi: 0.7279		ari: 0.7895		f1: 0.9251		
epoch: 049		acc: 0.9256		nmi: 0.7300		ari: 0.7912		f1: 0.9258		
epoch: 050		acc: 0.9266		nmi: 0.7319		ari: 0.7938		f1: 0.9267		
The total number of parameters is: 1.093168M(1e6).
The max memory allocated to model is: 636.85 MB.
Time consuming: 3.7s or 0.06m
****************************************Training loop No.10****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=1870, out_features=512, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.9041		nmi: 0.6776		ari: 0.7376		f1: 0.9038		
epoch: 002		acc: 0.4099		nmi: 0.1221		ari: 0.0123		f1: 0.3087		
epoch: 003		acc: 0.8866		nmi: 0.6579		ari: 0.6944		f1: 0.8864		
epoch: 004		acc: 0.8324		nmi: 0.5841		ari: 0.5909		f1: 0.8191		
epoch: 005		acc: 0.8774		nmi: 0.6431		ari: 0.6777		f1: 0.8727		
epoch: 006		acc: 0.9081		nmi: 0.6972		ari: 0.7490		f1: 0.9072		
epoch: 007		acc: 0.9048		nmi: 0.6929		ari: 0.7412		f1: 0.9045		
epoch: 008		acc: 0.9088		nmi: 0.7051		ari: 0.7509		f1: 0.9085		
epoch: 009		acc: 0.9058		nmi: 0.7013		ari: 0.7442		f1: 0.9052		
epoch: 010		acc: 0.9051		nmi: 0.6957		ari: 0.7421		f1: 0.9039		
epoch: 011		acc: 0.9061		nmi: 0.6964		ari: 0.7446		f1: 0.9050		
epoch: 012		acc: 0.9071		nmi: 0.6967		ari: 0.7466		f1: 0.9060		
epoch: 013		acc: 0.9154		nmi: 0.7138		ari: 0.7667		f1: 0.9148		
epoch: 014		acc: 0.9190		nmi: 0.7192		ari: 0.7754		f1: 0.9188		
epoch: 015		acc: 0.9203		nmi: 0.7201		ari: 0.7782		f1: 0.9204		
epoch: 016		acc: 0.9217		nmi: 0.7220		ari: 0.7812		f1: 0.9218		
epoch: 017		acc: 0.9250		nmi: 0.7308		ari: 0.7896		f1: 0.9252		
epoch: 018		acc: 0.9250		nmi: 0.7297		ari: 0.7896		f1: 0.9252		
epoch: 019		acc: 0.9243		nmi: 0.7282		ari: 0.7879		f1: 0.9245		
epoch: 020		acc: 0.9269		nmi: 0.7351		ari: 0.7948		f1: 0.9271		
epoch: 021		acc: 0.9243		nmi: 0.7279		ari: 0.7880		f1: 0.9244		
epoch: 022		acc: 0.9250		nmi: 0.7298		ari: 0.7896		f1: 0.9251		
epoch: 023		acc: 0.9250		nmi: 0.7283		ari: 0.7895		f1: 0.9251		
epoch: 024		acc: 0.9250		nmi: 0.7296		ari: 0.7896		f1: 0.9251		
epoch: 025		acc: 0.9243		nmi: 0.7278		ari: 0.7879		f1: 0.9245		
epoch: 026		acc: 0.9243		nmi: 0.7273		ari: 0.7878		f1: 0.9245		
epoch: 027		acc: 0.9263		nmi: 0.7324		ari: 0.7930		f1: 0.9264		
epoch: 028		acc: 0.9243		nmi: 0.7270		ari: 0.7876		f1: 0.9246		
epoch: 029		acc: 0.9253		nmi: 0.7302		ari: 0.7903		f1: 0.9255		
epoch: 030		acc: 0.9253		nmi: 0.7295		ari: 0.7904		f1: 0.9254		
epoch: 031		acc: 0.9263		nmi: 0.7317		ari: 0.7928		f1: 0.9265		
epoch: 032		acc: 0.9246		nmi: 0.7275		ari: 0.7885		f1: 0.9248		
epoch: 033		acc: 0.9266		nmi: 0.7324		ari: 0.7937		f1: 0.9268		
epoch: 034		acc: 0.9243		nmi: 0.7256		ari: 0.7876		f1: 0.9245		
epoch: 035		acc: 0.9260		nmi: 0.7316		ari: 0.7921		f1: 0.9261		
epoch: 036		acc: 0.9243		nmi: 0.7257		ari: 0.7876		f1: 0.9245		
epoch: 037		acc: 0.9263		nmi: 0.7313		ari: 0.7929		f1: 0.9264		
epoch: 038		acc: 0.9260		nmi: 0.7314		ari: 0.7920		f1: 0.9262		
epoch: 039		acc: 0.9260		nmi: 0.7310		ari: 0.7920		f1: 0.9261		
epoch: 040		acc: 0.9253		nmi: 0.7293		ari: 0.7902		f1: 0.9255		
epoch: 041		acc: 0.9260		nmi: 0.7314		ari: 0.7920		f1: 0.9262		
epoch: 042		acc: 0.9243		nmi: 0.7261		ari: 0.7877		f1: 0.9244		
epoch: 043		acc: 0.9263		nmi: 0.7313		ari: 0.7927		f1: 0.9265		
epoch: 044		acc: 0.9273		nmi: 0.7347		ari: 0.7954		f1: 0.9275		
epoch: 045		acc: 0.9276		nmi: 0.7359		ari: 0.7963		f1: 0.9278		
epoch: 046		acc: 0.9263		nmi: 0.7315		ari: 0.7928		f1: 0.9265		
epoch: 047		acc: 0.9246		nmi: 0.7269		ari: 0.7884		f1: 0.9248		
epoch: 048		acc: 0.9269		nmi: 0.7340		ari: 0.7946		f1: 0.9271		
epoch: 049		acc: 0.9263		nmi: 0.7321		ari: 0.7929		f1: 0.9265		
epoch: 050		acc: 0.9263		nmi: 0.7323		ari: 0.7928		f1: 0.9265		
The total number of parameters is: 1.093168M(1e6).
The max memory allocated to model is: 636.85 MB.
Time consuming: 3.73s or 0.06m
Namespace(is_pretrain=False, plot_clustering_tsne=False, plot_embedding_heatmap=False, adj_norm=False, adj_loop=True, adj_symmetric=True, desc='default', model_name='SYNC', dataset_name='acm', root=None, k=None, t=None, loops=10, feature_type='tensor', label_type='npy', adj_type='tensor', seed=325, epsilon=0.0, device='cuda', clusters=3, nodes=3025, lr=0.002, max_epoch=50, pretrain_lr=0.001, pretrain_epoch=30, input_dim=1870, log_save_path='./logs/SYNC/acm/', dataset_path='../data/', clustering_tsne_save_path='./img/clustering/SYNC/acm/', embedding_heatmap_save_path='./img/heatmap/SYNC/acm/', pretrain_save_path='./pretrain/pretrain_tigae/SYNC/acm/', hidden_dim=256, embedding_dim=16, linear_dim=512, beta=1)
Total loops: 10
****************************************Mean value:****************************************
acc: 0.9273±0.0004		nmi: 0.7358±0.0022		ari: 0.7958±0.0012		f1: 0.9274±0.0004
Training over! Punch out!
Loading dblp dataset from local
****************************************Training loop No.1****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=334, out_features=512, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.7754		nmi: 0.4461		ari: 0.4991		f1: 0.7709		
epoch: 002		acc: 0.3071		nmi: 0.0493		ari: 0.0018		f1: 0.1581		
epoch: 003		acc: 0.8001		nmi: 0.4856		ari: 0.5461		f1: 0.7917		
epoch: 004		acc: 0.6160		nmi: 0.3590		ari: 0.2745		f1: 0.5774		
epoch: 005		acc: 0.8117		nmi: 0.5090		ari: 0.5723		f1: 0.8035		
epoch: 006		acc: 0.8035		nmi: 0.5031		ari: 0.5586		f1: 0.7964		
epoch: 007		acc: 0.8193		nmi: 0.5215		ari: 0.5871		f1: 0.8117		
epoch: 008		acc: 0.8208		nmi: 0.5293		ari: 0.5915		f1: 0.8101		
epoch: 009		acc: 0.8129		nmi: 0.5227		ari: 0.5806		f1: 0.7967		
epoch: 010		acc: 0.8122		nmi: 0.5177		ari: 0.5784		f1: 0.7968		
epoch: 011		acc: 0.8230		nmi: 0.5340		ari: 0.5977		f1: 0.8109		
epoch: 012		acc: 0.8312		nmi: 0.5458		ari: 0.6121		f1: 0.8220		
epoch: 013		acc: 0.8314		nmi: 0.5438		ari: 0.6104		f1: 0.8246		
epoch: 014		acc: 0.8361		nmi: 0.5523		ari: 0.6193		f1: 0.8304		
epoch: 015		acc: 0.8312		nmi: 0.5438		ari: 0.6094		f1: 0.8257		
epoch: 016		acc: 0.8326		nmi: 0.5485		ari: 0.6128		f1: 0.8274		
epoch: 017		acc: 0.8312		nmi: 0.5467		ari: 0.6098		f1: 0.8260		
epoch: 018		acc: 0.8326		nmi: 0.5474		ari: 0.6128		f1: 0.8272		
epoch: 019		acc: 0.8292		nmi: 0.5406		ari: 0.6054		f1: 0.8236		
epoch: 020		acc: 0.8287		nmi: 0.5402		ari: 0.6053		f1: 0.8225		
epoch: 021		acc: 0.8294		nmi: 0.5407		ari: 0.6067		f1: 0.8232		
epoch: 022		acc: 0.8299		nmi: 0.5421		ari: 0.6075		f1: 0.8239		
epoch: 023		acc: 0.8309		nmi: 0.5439		ari: 0.6091		f1: 0.8251		
epoch: 024		acc: 0.8280		nmi: 0.5376		ari: 0.6035		f1: 0.8219		
epoch: 025		acc: 0.8284		nmi: 0.5384		ari: 0.6035		f1: 0.8230		
epoch: 026		acc: 0.8297		nmi: 0.5418		ari: 0.6064		f1: 0.8244		
epoch: 027		acc: 0.8284		nmi: 0.5398		ari: 0.6039		f1: 0.8230		
epoch: 028		acc: 0.8309		nmi: 0.5445		ari: 0.6086		f1: 0.8258		
epoch: 029		acc: 0.8284		nmi: 0.5407		ari: 0.6046		f1: 0.8229		
epoch: 030		acc: 0.8294		nmi: 0.5411		ari: 0.6055		f1: 0.8243		
epoch: 031		acc: 0.8280		nmi: 0.5377		ari: 0.6026		f1: 0.8227		
epoch: 032		acc: 0.8282		nmi: 0.5396		ari: 0.6041		f1: 0.8227		
epoch: 033		acc: 0.8302		nmi: 0.5423		ari: 0.6066		f1: 0.8252		
epoch: 034		acc: 0.8284		nmi: 0.5401		ari: 0.6047		f1: 0.8228		
epoch: 035		acc: 0.8275		nmi: 0.5382		ari: 0.6012		f1: 0.8224		
epoch: 036		acc: 0.8272		nmi: 0.5379		ari: 0.6009		f1: 0.8222		
epoch: 037		acc: 0.8265		nmi: 0.5367		ari: 0.5996		f1: 0.8213		
epoch: 038		acc: 0.8275		nmi: 0.5382		ari: 0.6009		f1: 0.8227		
epoch: 039		acc: 0.8275		nmi: 0.5378		ari: 0.6008		f1: 0.8226		
epoch: 040		acc: 0.8270		nmi: 0.5387		ari: 0.6003		f1: 0.8220		
epoch: 041		acc: 0.8255		nmi: 0.5356		ari: 0.5968		f1: 0.8208		
epoch: 042		acc: 0.8245		nmi: 0.5338		ari: 0.5953		f1: 0.8196		
epoch: 043		acc: 0.8225		nmi: 0.5316		ari: 0.5907		f1: 0.8180		
epoch: 044		acc: 0.8208		nmi: 0.5286		ari: 0.5877		f1: 0.8161		
epoch: 045		acc: 0.8233		nmi: 0.5328		ari: 0.5927		f1: 0.8185		
epoch: 046		acc: 0.8245		nmi: 0.5359		ari: 0.5951		f1: 0.8199		
epoch: 047		acc: 0.8215		nmi: 0.5303		ari: 0.5893		f1: 0.8168		
epoch: 048		acc: 0.8198		nmi: 0.5271		ari: 0.5855		f1: 0.8152		
epoch: 049		acc: 0.8186		nmi: 0.5263		ari: 0.5830		f1: 0.8141		
epoch: 050		acc: 0.8196		nmi: 0.5275		ari: 0.5847		f1: 0.8151		
The total number of parameters is: 0.306752M(1e6).
The max memory allocated to model is: 1048.10 MB.
Time consuming: 10.34s or 0.17m
****************************************Training loop No.2****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=334, out_features=512, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.7695		nmi: 0.4365		ari: 0.4869		f1: 0.7655		
epoch: 002		acc: 0.3071		nmi: 0.0535		ari: 0.0018		f1: 0.1601		
epoch: 003		acc: 0.7927		nmi: 0.4743		ari: 0.5315		f1: 0.7844		
epoch: 004		acc: 0.6172		nmi: 0.3611		ari: 0.2715		f1: 0.5868		
epoch: 005		acc: 0.8149		nmi: 0.5145		ari: 0.5779		f1: 0.8091		
epoch: 006		acc: 0.8031		nmi: 0.5042		ari: 0.5568		f1: 0.7965		
epoch: 007		acc: 0.8156		nmi: 0.5159		ari: 0.5811		f1: 0.8077		
epoch: 008		acc: 0.8220		nmi: 0.5292		ari: 0.5927		f1: 0.8125		
epoch: 009		acc: 0.8186		nmi: 0.5265		ari: 0.5885		f1: 0.8059		
epoch: 010		acc: 0.8233		nmi: 0.5338		ari: 0.5983		f1: 0.8115		
epoch: 011		acc: 0.8247		nmi: 0.5343		ari: 0.5983		f1: 0.8155		
epoch: 012		acc: 0.8319		nmi: 0.5447		ari: 0.6116		f1: 0.8249		
epoch: 013		acc: 0.8341		nmi: 0.5488		ari: 0.6160		f1: 0.8282		
epoch: 014		acc: 0.8349		nmi: 0.5517		ari: 0.6171		f1: 0.8297		
epoch: 015		acc: 0.8297		nmi: 0.5418		ari: 0.6069		f1: 0.8244		
epoch: 016		acc: 0.8324		nmi: 0.5492		ari: 0.6129		f1: 0.8272		
epoch: 017		acc: 0.8321		nmi: 0.5478		ari: 0.6118		f1: 0.8271		
epoch: 018		acc: 0.8299		nmi: 0.5448		ari: 0.6082		f1: 0.8246		
epoch: 019		acc: 0.8297		nmi: 0.5435		ari: 0.6079		f1: 0.8239		
epoch: 020		acc: 0.8289		nmi: 0.5419		ari: 0.6062		f1: 0.8233		
epoch: 021		acc: 0.8289		nmi: 0.5395		ari: 0.6048		f1: 0.8234		
epoch: 022		acc: 0.8284		nmi: 0.5397		ari: 0.6049		f1: 0.8225		
epoch: 023		acc: 0.8297		nmi: 0.5420		ari: 0.6066		f1: 0.8242		
epoch: 024		acc: 0.8299		nmi: 0.5425		ari: 0.6076		f1: 0.8241		
epoch: 025		acc: 0.8275		nmi: 0.5385		ari: 0.6018		f1: 0.8222		
epoch: 026		acc: 0.8277		nmi: 0.5391		ari: 0.6034		f1: 0.8222		
epoch: 027		acc: 0.8275		nmi: 0.5387		ari: 0.6020		f1: 0.8224		
epoch: 028		acc: 0.8289		nmi: 0.5430		ari: 0.6056		f1: 0.8237		
epoch: 029		acc: 0.8287		nmi: 0.5407		ari: 0.6052		f1: 0.8232		
epoch: 030		acc: 0.8262		nmi: 0.5366		ari: 0.5992		f1: 0.8213		
epoch: 031		acc: 0.8280		nmi: 0.5405		ari: 0.6031		f1: 0.8229		
epoch: 032		acc: 0.8280		nmi: 0.5407		ari: 0.6035		f1: 0.8228		
epoch: 033		acc: 0.8245		nmi: 0.5339		ari: 0.5962		f1: 0.8194		
epoch: 034		acc: 0.8247		nmi: 0.5346		ari: 0.5963		f1: 0.8198		
epoch: 035		acc: 0.8247		nmi: 0.5346		ari: 0.5963		f1: 0.8198		
epoch: 036		acc: 0.8247		nmi: 0.5351		ari: 0.5966		f1: 0.8198		
epoch: 037		acc: 0.8243		nmi: 0.5356		ari: 0.5959		f1: 0.8193		
epoch: 038		acc: 0.8243		nmi: 0.5332		ari: 0.5955		f1: 0.8192		
epoch: 039		acc: 0.8245		nmi: 0.5349		ari: 0.5970		f1: 0.8191		
epoch: 040		acc: 0.8235		nmi: 0.5334		ari: 0.5939		f1: 0.8187		
epoch: 041		acc: 0.8225		nmi: 0.5305		ari: 0.5918		f1: 0.8176		
epoch: 042		acc: 0.8206		nmi: 0.5266		ari: 0.5881		f1: 0.8156		
epoch: 043		acc: 0.8233		nmi: 0.5333		ari: 0.5945		f1: 0.8181		
epoch: 044		acc: 0.8235		nmi: 0.5333		ari: 0.5951		f1: 0.8182		
epoch: 045		acc: 0.8228		nmi: 0.5318		ari: 0.5930		f1: 0.8177		
epoch: 046		acc: 0.8215		nmi: 0.5294		ari: 0.5898		f1: 0.8168		
epoch: 047		acc: 0.8206		nmi: 0.5270		ari: 0.5875		f1: 0.8158		
epoch: 048		acc: 0.8186		nmi: 0.5230		ari: 0.5847		f1: 0.8133		
epoch: 049		acc: 0.8208		nmi: 0.5281		ari: 0.5889		f1: 0.8157		
epoch: 050		acc: 0.8215		nmi: 0.5293		ari: 0.5899		f1: 0.8167		
The total number of parameters is: 0.306752M(1e6).
The max memory allocated to model is: 1051.31 MB.
Time consuming: 7.46s or 0.12m
****************************************Training loop No.3****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=334, out_features=512, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.7740		nmi: 0.4440		ari: 0.4963		f1: 0.7696		
epoch: 002		acc: 0.3091		nmi: 0.0481		ari: 0.0021		f1: 0.1592		
epoch: 003		acc: 0.7966		nmi: 0.4810		ari: 0.5398		f1: 0.7878		
epoch: 004		acc: 0.6256		nmi: 0.3623		ari: 0.2842		f1: 0.5915		
epoch: 005		acc: 0.8154		nmi: 0.5146		ari: 0.5800		f1: 0.8081		
epoch: 006		acc: 0.8080		nmi: 0.5110		ari: 0.5675		f1: 0.8011		
epoch: 007		acc: 0.8215		nmi: 0.5256		ari: 0.5915		f1: 0.8139		
epoch: 008		acc: 0.8250		nmi: 0.5368		ari: 0.5992		f1: 0.8143		
epoch: 009		acc: 0.8107		nmi: 0.5175		ari: 0.5752		f1: 0.7947		
epoch: 010		acc: 0.8181		nmi: 0.5285		ari: 0.5882		f1: 0.8043		
epoch: 011		acc: 0.8235		nmi: 0.5338		ari: 0.5975		f1: 0.8124		
epoch: 012		acc: 0.8277		nmi: 0.5398		ari: 0.6051		f1: 0.8188		
epoch: 013		acc: 0.8307		nmi: 0.5433		ari: 0.6083		f1: 0.8243		
epoch: 014		acc: 0.8309		nmi: 0.5440		ari: 0.6089		f1: 0.8254		
epoch: 015		acc: 0.8331		nmi: 0.5487		ari: 0.6140		f1: 0.8277		
epoch: 016		acc: 0.8275		nmi: 0.5393		ari: 0.6018		f1: 0.8224		
epoch: 017		acc: 0.8275		nmi: 0.5389		ari: 0.6014		f1: 0.8225		
epoch: 018		acc: 0.8262		nmi: 0.5365		ari: 0.6009		f1: 0.8202		
epoch: 019		acc: 0.8272		nmi: 0.5389		ari: 0.6027		f1: 0.8211		
epoch: 020		acc: 0.8297		nmi: 0.5427		ari: 0.6078		f1: 0.8235		
epoch: 021		acc: 0.8289		nmi: 0.5416		ari: 0.6055		f1: 0.8229		
epoch: 022		acc: 0.8257		nmi: 0.5344		ari: 0.5989		f1: 0.8196		
epoch: 023		acc: 0.8282		nmi: 0.5388		ari: 0.6038		f1: 0.8223		
epoch: 024		acc: 0.8297		nmi: 0.5431		ari: 0.6078		f1: 0.8234		
epoch: 025		acc: 0.8289		nmi: 0.5398		ari: 0.6049		f1: 0.8233		
epoch: 026		acc: 0.8270		nmi: 0.5364		ari: 0.6014		f1: 0.8210		
epoch: 027		acc: 0.8287		nmi: 0.5391		ari: 0.6036		f1: 0.8235		
epoch: 028		acc: 0.8287		nmi: 0.5393		ari: 0.6045		f1: 0.8231		
epoch: 029		acc: 0.8329		nmi: 0.5479		ari: 0.6130		f1: 0.8275		
epoch: 030		acc: 0.8302		nmi: 0.5425		ari: 0.6072		f1: 0.8249		
epoch: 031		acc: 0.8307		nmi: 0.5441		ari: 0.6089		f1: 0.8250		
epoch: 032		acc: 0.8297		nmi: 0.5414		ari: 0.6068		f1: 0.8239		
epoch: 033		acc: 0.8309		nmi: 0.5429		ari: 0.6083		f1: 0.8257		
epoch: 034		acc: 0.8299		nmi: 0.5429		ari: 0.6074		f1: 0.8245		
epoch: 035		acc: 0.8282		nmi: 0.5383		ari: 0.6027		f1: 0.8231		
epoch: 036		acc: 0.8275		nmi: 0.5375		ari: 0.6016		f1: 0.8223		
epoch: 037		acc: 0.8292		nmi: 0.5412		ari: 0.6059		f1: 0.8236		
epoch: 038		acc: 0.8272		nmi: 0.5371		ari: 0.6019		f1: 0.8216		
epoch: 039		acc: 0.8250		nmi: 0.5328		ari: 0.5968		f1: 0.8197		
epoch: 040		acc: 0.8260		nmi: 0.5352		ari: 0.5993		f1: 0.8205		
epoch: 041		acc: 0.8257		nmi: 0.5345		ari: 0.5984		f1: 0.8204		
epoch: 042		acc: 0.8247		nmi: 0.5331		ari: 0.5967		f1: 0.8193		
epoch: 043		acc: 0.8280		nmi: 0.5387		ari: 0.6033		f1: 0.8224		
epoch: 044		acc: 0.8260		nmi: 0.5349		ari: 0.5995		f1: 0.8204		
epoch: 045		acc: 0.8255		nmi: 0.5335		ari: 0.5984		f1: 0.8199		
epoch: 046		acc: 0.8260		nmi: 0.5357		ari: 0.5991		f1: 0.8207		
epoch: 047		acc: 0.8260		nmi: 0.5348		ari: 0.5993		f1: 0.8204		
epoch: 048		acc: 0.8238		nmi: 0.5297		ari: 0.5940		f1: 0.8184		
epoch: 049		acc: 0.8255		nmi: 0.5339		ari: 0.5975		f1: 0.8203		
epoch: 050		acc: 0.8250		nmi: 0.5331		ari: 0.5970		f1: 0.8196		
The total number of parameters is: 0.306752M(1e6).
The max memory allocated to model is: 1051.31 MB.
Time consuming: 7.57s or 0.13m
****************************************Training loop No.4****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=334, out_features=512, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.7725		nmi: 0.4405		ari: 0.4934		f1: 0.7679		
epoch: 002		acc: 0.3071		nmi: 0.0450		ari: 0.0015		f1: 0.1544		
epoch: 003		acc: 0.7957		nmi: 0.4811		ari: 0.5386		f1: 0.7853		
epoch: 004		acc: 0.6133		nmi: 0.3595		ari: 0.2734		f1: 0.5795		
epoch: 005		acc: 0.8139		nmi: 0.5152		ari: 0.5775		f1: 0.8074		
epoch: 006		acc: 0.8026		nmi: 0.5024		ari: 0.5569		f1: 0.7956		
epoch: 007		acc: 0.8220		nmi: 0.5284		ari: 0.5944		f1: 0.8134		
epoch: 008		acc: 0.8223		nmi: 0.5325		ari: 0.5946		f1: 0.8110		
epoch: 009		acc: 0.8174		nmi: 0.5286		ari: 0.5889		f1: 0.8021		
epoch: 010		acc: 0.8211		nmi: 0.5315		ari: 0.5945		f1: 0.8078		
epoch: 011		acc: 0.8247		nmi: 0.5353		ari: 0.6016		f1: 0.8132		
epoch: 012		acc: 0.8326		nmi: 0.5472		ari: 0.6139		f1: 0.8249		
epoch: 013		acc: 0.8319		nmi: 0.5448		ari: 0.6120		f1: 0.8254		
epoch: 014		acc: 0.8353		nmi: 0.5528		ari: 0.6189		f1: 0.8298		
epoch: 015		acc: 0.8314		nmi: 0.5461		ari: 0.6110		f1: 0.8258		
epoch: 016		acc: 0.8312		nmi: 0.5461		ari: 0.6104		f1: 0.8258		
epoch: 017		acc: 0.8292		nmi: 0.5423		ari: 0.6064		f1: 0.8238		
epoch: 018		acc: 0.8267		nmi: 0.5380		ari: 0.6022		f1: 0.8208		
epoch: 019		acc: 0.8304		nmi: 0.5438		ari: 0.6090		f1: 0.8246		
epoch: 020		acc: 0.8297		nmi: 0.5424		ari: 0.6076		f1: 0.8235		
epoch: 021		acc: 0.8282		nmi: 0.5399		ari: 0.6051		f1: 0.8219		
epoch: 022		acc: 0.8243		nmi: 0.5335		ari: 0.5981		f1: 0.8174		
epoch: 023		acc: 0.8272		nmi: 0.5385		ari: 0.6037		f1: 0.8207		
epoch: 024		acc: 0.8270		nmi: 0.5375		ari: 0.6023		f1: 0.8209		
epoch: 025		acc: 0.8275		nmi: 0.5386		ari: 0.6033		f1: 0.8216		
epoch: 026		acc: 0.8260		nmi: 0.5355		ari: 0.5997		f1: 0.8203		
epoch: 027		acc: 0.8260		nmi: 0.5358		ari: 0.5994		f1: 0.8206		
epoch: 028		acc: 0.8267		nmi: 0.5372		ari: 0.6016		f1: 0.8211		
epoch: 029		acc: 0.8265		nmi: 0.5374		ari: 0.6010		f1: 0.8209		
epoch: 030		acc: 0.8262		nmi: 0.5369		ari: 0.6004		f1: 0.8208		
epoch: 031		acc: 0.8257		nmi: 0.5355		ari: 0.5994		f1: 0.8202		
epoch: 032		acc: 0.8265		nmi: 0.5380		ari: 0.6006		f1: 0.8213		
epoch: 033		acc: 0.8257		nmi: 0.5372		ari: 0.5989		f1: 0.8207		
epoch: 034		acc: 0.8250		nmi: 0.5352		ari: 0.5973		f1: 0.8199		
epoch: 035		acc: 0.8267		nmi: 0.5390		ari: 0.6018		f1: 0.8213		
epoch: 036		acc: 0.8238		nmi: 0.5343		ari: 0.5949		f1: 0.8188		
epoch: 037		acc: 0.8223		nmi: 0.5310		ari: 0.5919		f1: 0.8172		
epoch: 038		acc: 0.8250		nmi: 0.5371		ari: 0.5973		f1: 0.8201		
epoch: 039		acc: 0.8260		nmi: 0.5389		ari: 0.5997		f1: 0.8210		
epoch: 040		acc: 0.8228		nmi: 0.5330		ari: 0.5930		f1: 0.8178		
epoch: 041		acc: 0.8223		nmi: 0.5327		ari: 0.5924		f1: 0.8172		
epoch: 042		acc: 0.8198		nmi: 0.5288		ari: 0.5870		f1: 0.8150		
epoch: 043		acc: 0.8176		nmi: 0.5249		ari: 0.5827		f1: 0.8127		
epoch: 044		acc: 0.8198		nmi: 0.5296		ari: 0.5870		f1: 0.8150		
epoch: 045		acc: 0.8198		nmi: 0.5287		ari: 0.5867		f1: 0.8150		
epoch: 046		acc: 0.8159		nmi: 0.5242		ari: 0.5789		f1: 0.8113		
epoch: 047		acc: 0.8188		nmi: 0.5288		ari: 0.5850		f1: 0.8141		
epoch: 048		acc: 0.8178		nmi: 0.5268		ari: 0.5826		f1: 0.8132		
epoch: 049		acc: 0.8164		nmi: 0.5257		ari: 0.5807		f1: 0.8114		
epoch: 050		acc: 0.8181		nmi: 0.5293		ari: 0.5836		f1: 0.8134		
The total number of parameters is: 0.306752M(1e6).
The max memory allocated to model is: 1051.31 MB.
Time consuming: 7.53s or 0.13m
****************************************Training loop No.5****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=334, out_features=512, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.7747		nmi: 0.4447		ari: 0.4974		f1: 0.7703		
epoch: 002		acc: 0.3113		nmi: 0.0540		ari: 0.0024		f1: 0.1633		
epoch: 003		acc: 0.7897		nmi: 0.4723		ari: 0.5253		f1: 0.7808		
epoch: 004		acc: 0.6345		nmi: 0.3677		ari: 0.2904		f1: 0.6041		
epoch: 005		acc: 0.8149		nmi: 0.5140		ari: 0.5790		f1: 0.8085		
epoch: 006		acc: 0.8035		nmi: 0.5043		ari: 0.5599		f1: 0.7965		
epoch: 007		acc: 0.8146		nmi: 0.5137		ari: 0.5803		f1: 0.8058		
epoch: 008		acc: 0.8211		nmi: 0.5294		ari: 0.5926		f1: 0.8098		
epoch: 009		acc: 0.8178		nmi: 0.5263		ari: 0.5866		f1: 0.8046		
epoch: 010		acc: 0.8213		nmi: 0.5309		ari: 0.5931		f1: 0.8091		
epoch: 011		acc: 0.8228		nmi: 0.5319		ari: 0.5961		f1: 0.8121		
epoch: 012		acc: 0.8324		nmi: 0.5461		ari: 0.6118		f1: 0.8255		
epoch: 013		acc: 0.8314		nmi: 0.5446		ari: 0.6105		f1: 0.8251		
epoch: 014		acc: 0.8336		nmi: 0.5487		ari: 0.6136		f1: 0.8287		
epoch: 015		acc: 0.8304		nmi: 0.5434		ari: 0.6079		f1: 0.8252		
epoch: 016		acc: 0.8275		nmi: 0.5399		ari: 0.6020		f1: 0.8225		
epoch: 017		acc: 0.8302		nmi: 0.5444		ari: 0.6072		f1: 0.8254		
epoch: 018		acc: 0.8282		nmi: 0.5410		ari: 0.6042		f1: 0.8227		
epoch: 019		acc: 0.8302		nmi: 0.5447		ari: 0.6079		f1: 0.8247		
epoch: 020		acc: 0.8267		nmi: 0.5370		ari: 0.6020		f1: 0.8204		
epoch: 021		acc: 0.8277		nmi: 0.5396		ari: 0.6036		f1: 0.8217		
epoch: 022		acc: 0.8257		nmi: 0.5357		ari: 0.5998		f1: 0.8197		
epoch: 023		acc: 0.8275		nmi: 0.5399		ari: 0.6039		f1: 0.8212		
epoch: 024		acc: 0.8275		nmi: 0.5397		ari: 0.6036		f1: 0.8215		
epoch: 025		acc: 0.8326		nmi: 0.5487		ari: 0.6132		f1: 0.8271		
epoch: 026		acc: 0.8260		nmi: 0.5365		ari: 0.5998		f1: 0.8204		
epoch: 027		acc: 0.8304		nmi: 0.5442		ari: 0.6087		f1: 0.8249		
epoch: 028		acc: 0.8287		nmi: 0.5416		ari: 0.6048		f1: 0.8234		
epoch: 029		acc: 0.8280		nmi: 0.5395		ari: 0.6024		f1: 0.8232		
epoch: 030		acc: 0.8289		nmi: 0.5424		ari: 0.6050		f1: 0.8240		
epoch: 031		acc: 0.8280		nmi: 0.5402		ari: 0.6029		f1: 0.8230		
epoch: 032		acc: 0.8304		nmi: 0.5442		ari: 0.6077		f1: 0.8255		
epoch: 033		acc: 0.8280		nmi: 0.5414		ari: 0.6030		f1: 0.8230		
epoch: 034		acc: 0.8245		nmi: 0.5339		ari: 0.5958		f1: 0.8194		
epoch: 035		acc: 0.8265		nmi: 0.5375		ari: 0.6001		f1: 0.8213		
epoch: 036		acc: 0.8252		nmi: 0.5344		ari: 0.5974		f1: 0.8201		
epoch: 037		acc: 0.8247		nmi: 0.5345		ari: 0.5963		f1: 0.8198		
epoch: 038		acc: 0.8243		nmi: 0.5352		ari: 0.5955		f1: 0.8194		
epoch: 039		acc: 0.8260		nmi: 0.5374		ari: 0.5985		f1: 0.8211		
epoch: 040		acc: 0.8235		nmi: 0.5330		ari: 0.5942		f1: 0.8185		
epoch: 041		acc: 0.8233		nmi: 0.5342		ari: 0.5930		f1: 0.8186		
epoch: 042		acc: 0.8230		nmi: 0.5334		ari: 0.5923		f1: 0.8184		
epoch: 043		acc: 0.8213		nmi: 0.5314		ari: 0.5891		f1: 0.8166		
epoch: 044		acc: 0.8203		nmi: 0.5306		ari: 0.5872		f1: 0.8157		
epoch: 045		acc: 0.8203		nmi: 0.5299		ari: 0.5875		f1: 0.8155		
epoch: 046		acc: 0.8206		nmi: 0.5315		ari: 0.5874		f1: 0.8161		
epoch: 047		acc: 0.8174		nmi: 0.5261		ari: 0.5813		f1: 0.8128		
epoch: 048		acc: 0.8220		nmi: 0.5344		ari: 0.5909		f1: 0.8174		
epoch: 049		acc: 0.8166		nmi: 0.5249		ari: 0.5793		f1: 0.8122		
epoch: 050		acc: 0.8176		nmi: 0.5260		ari: 0.5811		f1: 0.8133		
The total number of parameters is: 0.306752M(1e6).
The max memory allocated to model is: 1051.31 MB.
Time consuming: 7.5s or 0.12m
****************************************Training loop No.6****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=334, out_features=512, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.7777		nmi: 0.4494		ari: 0.5028		f1: 0.7733		
epoch: 002		acc: 0.3052		nmi: 0.0434		ari: 0.0013		f1: 0.1529		
epoch: 003		acc: 0.8082		nmi: 0.5002		ari: 0.5623		f1: 0.8011		
epoch: 004		acc: 0.6300		nmi: 0.3671		ari: 0.2919		f1: 0.5952		
epoch: 005		acc: 0.8132		nmi: 0.5117		ari: 0.5749		f1: 0.8056		
epoch: 006		acc: 0.8053		nmi: 0.5069		ari: 0.5614		f1: 0.7984		
epoch: 007		acc: 0.8188		nmi: 0.5197		ari: 0.5859		f1: 0.8117		
epoch: 008		acc: 0.8208		nmi: 0.5277		ari: 0.5914		f1: 0.8100		
epoch: 009		acc: 0.8114		nmi: 0.5175		ari: 0.5759		f1: 0.7967		
epoch: 010		acc: 0.8109		nmi: 0.5172		ari: 0.5754		f1: 0.7955		
epoch: 011		acc: 0.8198		nmi: 0.5273		ari: 0.5884		f1: 0.8093		
epoch: 012		acc: 0.8275		nmi: 0.5398		ari: 0.6040		f1: 0.8182		
epoch: 013		acc: 0.8351		nmi: 0.5526		ari: 0.6174		f1: 0.8286		
epoch: 014		acc: 0.8312		nmi: 0.5447		ari: 0.6097		f1: 0.8251		
epoch: 015		acc: 0.8326		nmi: 0.5493		ari: 0.6126		f1: 0.8273		
epoch: 016		acc: 0.8329		nmi: 0.5502		ari: 0.6126		f1: 0.8280		
epoch: 017		acc: 0.8277		nmi: 0.5403		ari: 0.6028		f1: 0.8223		
epoch: 018		acc: 0.8287		nmi: 0.5432		ari: 0.6044		f1: 0.8235		
epoch: 019		acc: 0.8292		nmi: 0.5433		ari: 0.6061		f1: 0.8236		
epoch: 020		acc: 0.8284		nmi: 0.5405		ari: 0.6038		f1: 0.8229		
epoch: 021		acc: 0.8280		nmi: 0.5403		ari: 0.6032		f1: 0.8221		
epoch: 022		acc: 0.8243		nmi: 0.5329		ari: 0.5953		f1: 0.8188		
epoch: 023		acc: 0.8265		nmi: 0.5372		ari: 0.6004		f1: 0.8208		
epoch: 024		acc: 0.8282		nmi: 0.5399		ari: 0.6034		f1: 0.8226		
epoch: 025		acc: 0.8255		nmi: 0.5348		ari: 0.5982		f1: 0.8198		
epoch: 026		acc: 0.8280		nmi: 0.5395		ari: 0.6029		f1: 0.8225		
epoch: 027		acc: 0.8275		nmi: 0.5394		ari: 0.6020		f1: 0.8221		
epoch: 028		acc: 0.8287		nmi: 0.5420		ari: 0.6048		f1: 0.8233		
epoch: 029		acc: 0.8247		nmi: 0.5344		ari: 0.5978		f1: 0.8188		
epoch: 030		acc: 0.8270		nmi: 0.5384		ari: 0.6014		f1: 0.8214		
epoch: 031		acc: 0.8292		nmi: 0.5433		ari: 0.6058		f1: 0.8238		
epoch: 032		acc: 0.8257		nmi: 0.5377		ari: 0.5992		f1: 0.8203		
epoch: 033		acc: 0.8250		nmi: 0.5364		ari: 0.5972		f1: 0.8197		
epoch: 034		acc: 0.8252		nmi: 0.5368		ari: 0.5975		f1: 0.8200		
epoch: 035		acc: 0.8255		nmi: 0.5372		ari: 0.5984		f1: 0.8200		
epoch: 036		acc: 0.8220		nmi: 0.5307		ari: 0.5913		f1: 0.8166		
epoch: 037		acc: 0.8225		nmi: 0.5338		ari: 0.5926		f1: 0.8172		
epoch: 038		acc: 0.8181		nmi: 0.5242		ari: 0.5838		f1: 0.8126		
epoch: 039		acc: 0.8191		nmi: 0.5271		ari: 0.5852		f1: 0.8139		
epoch: 040		acc: 0.8201		nmi: 0.5299		ari: 0.5875		f1: 0.8148		
epoch: 041		acc: 0.8206		nmi: 0.5292		ari: 0.5878		f1: 0.8155		
epoch: 042		acc: 0.8201		nmi: 0.5286		ari: 0.5871		f1: 0.8150		
epoch: 043		acc: 0.8201		nmi: 0.5295		ari: 0.5870		f1: 0.8151		
epoch: 044		acc: 0.8218		nmi: 0.5335		ari: 0.5908		f1: 0.8168		
epoch: 045		acc: 0.8196		nmi: 0.5274		ari: 0.5856		f1: 0.8147		
epoch: 046		acc: 0.8178		nmi: 0.5259		ari: 0.5823		f1: 0.8130		
epoch: 047		acc: 0.8169		nmi: 0.5250		ari: 0.5811		f1: 0.8118		
epoch: 048		acc: 0.8196		nmi: 0.5303		ari: 0.5863		f1: 0.8147		
epoch: 049		acc: 0.8161		nmi: 0.5241		ari: 0.5796		f1: 0.8111		
epoch: 050		acc: 0.8159		nmi: 0.5239		ari: 0.5788		f1: 0.8110		
The total number of parameters is: 0.306752M(1e6).
The max memory allocated to model is: 1051.31 MB.
Time consuming: 7.53s or 0.13m
****************************************Training loop No.7****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=334, out_features=512, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.7735		nmi: 0.4432		ari: 0.4943		f1: 0.7695		
epoch: 002		acc: 0.3076		nmi: 0.0523		ari: 0.0019		f1: 0.1603		
epoch: 003		acc: 0.7984		nmi: 0.4832		ari: 0.5433		f1: 0.7903		
epoch: 004		acc: 0.6039		nmi: 0.3503		ari: 0.2563		f1: 0.5697		
epoch: 005		acc: 0.8151		nmi: 0.5137		ari: 0.5787		f1: 0.8080		
epoch: 006		acc: 0.8048		nmi: 0.5074		ari: 0.5593		f1: 0.7984		
epoch: 007		acc: 0.8112		nmi: 0.5093		ari: 0.5725		f1: 0.8034		
epoch: 008		acc: 0.8201		nmi: 0.5270		ari: 0.5899		f1: 0.8093		
epoch: 009		acc: 0.8141		nmi: 0.5199		ari: 0.5817		f1: 0.7999		
epoch: 010		acc: 0.8141		nmi: 0.5200		ari: 0.5823		f1: 0.7993		
epoch: 011		acc: 0.8201		nmi: 0.5267		ari: 0.5908		f1: 0.8092		
epoch: 012		acc: 0.8319		nmi: 0.5465		ari: 0.6125		f1: 0.8240		
epoch: 013		acc: 0.8336		nmi: 0.5479		ari: 0.6147		f1: 0.8274		
epoch: 014		acc: 0.8324		nmi: 0.5445		ari: 0.6115		f1: 0.8270		
epoch: 015		acc: 0.8339		nmi: 0.5492		ari: 0.6150		f1: 0.8287		
epoch: 016		acc: 0.8294		nmi: 0.5427		ari: 0.6062		f1: 0.8245		
epoch: 017		acc: 0.8326		nmi: 0.5491		ari: 0.6132		f1: 0.8274		
epoch: 018		acc: 0.8309		nmi: 0.5438		ari: 0.6085		f1: 0.8258		
epoch: 019		acc: 0.8297		nmi: 0.5412		ari: 0.6066		f1: 0.8242		
epoch: 020		acc: 0.8277		nmi: 0.5384		ari: 0.6029		f1: 0.8219		
epoch: 021		acc: 0.8270		nmi: 0.5362		ari: 0.6023		f1: 0.8204		
epoch: 022		acc: 0.8287		nmi: 0.5402		ari: 0.6056		f1: 0.8225		
epoch: 023		acc: 0.8302		nmi: 0.5420		ari: 0.6074		f1: 0.8245		
epoch: 024		acc: 0.8299		nmi: 0.5414		ari: 0.6068		f1: 0.8243		
epoch: 025		acc: 0.8309		nmi: 0.5436		ari: 0.6092		f1: 0.8252		
epoch: 026		acc: 0.8321		nmi: 0.5453		ari: 0.6108		f1: 0.8269		
epoch: 027		acc: 0.8289		nmi: 0.5388		ari: 0.6048		f1: 0.8234		
epoch: 028		acc: 0.8319		nmi: 0.5452		ari: 0.6104		f1: 0.8266		
epoch: 029		acc: 0.8282		nmi: 0.5377		ari: 0.6032		f1: 0.8227		
epoch: 030		acc: 0.8309		nmi: 0.5420		ari: 0.6077		f1: 0.8259		
epoch: 031		acc: 0.8289		nmi: 0.5391		ari: 0.6048		f1: 0.8236		
epoch: 032		acc: 0.8275		nmi: 0.5358		ari: 0.6012		f1: 0.8221		
epoch: 033		acc: 0.8272		nmi: 0.5356		ari: 0.6015		f1: 0.8216		
epoch: 034		acc: 0.8270		nmi: 0.5361		ari: 0.6007		f1: 0.8217		
epoch: 035		acc: 0.8272		nmi: 0.5371		ari: 0.6015		f1: 0.8219		
epoch: 036		acc: 0.8257		nmi: 0.5335		ari: 0.5978		f1: 0.8206		
epoch: 037		acc: 0.8252		nmi: 0.5333		ari: 0.5968		f1: 0.8203		
epoch: 038		acc: 0.8208		nmi: 0.5260		ari: 0.5879		f1: 0.8158		
epoch: 039		acc: 0.8228		nmi: 0.5307		ari: 0.5915		f1: 0.8182		
epoch: 040		acc: 0.8243		nmi: 0.5337		ari: 0.5950		f1: 0.8194		
epoch: 041		acc: 0.8223		nmi: 0.5310		ari: 0.5907		f1: 0.8177		
epoch: 042		acc: 0.8230		nmi: 0.5325		ari: 0.5919		f1: 0.8185		
epoch: 043		acc: 0.8233		nmi: 0.5342		ari: 0.5927		f1: 0.8187		
epoch: 044		acc: 0.8240		nmi: 0.5344		ari: 0.5942		f1: 0.8194		
epoch: 045		acc: 0.8233		nmi: 0.5324		ari: 0.5926		f1: 0.8186		
epoch: 046		acc: 0.8218		nmi: 0.5302		ari: 0.5902		f1: 0.8170		
epoch: 047		acc: 0.8228		nmi: 0.5327		ari: 0.5921		f1: 0.8180		
epoch: 048		acc: 0.8208		nmi: 0.5276		ari: 0.5882		f1: 0.8159		
epoch: 049		acc: 0.8233		nmi: 0.5323		ari: 0.5927		f1: 0.8186		
epoch: 050		acc: 0.8215		nmi: 0.5301		ari: 0.5894		f1: 0.8168		
The total number of parameters is: 0.306752M(1e6).
The max memory allocated to model is: 1051.31 MB.
Time consuming: 7.58s or 0.13m
****************************************Training loop No.8****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=334, out_features=512, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.7740		nmi: 0.4433		ari: 0.4954		f1: 0.7698		
epoch: 002		acc: 0.3101		nmi: 0.0514		ari: 0.0022		f1: 0.1615		
epoch: 003		acc: 0.8043		nmi: 0.4950		ari: 0.5538		f1: 0.7965		
epoch: 004		acc: 0.6007		nmi: 0.3502		ari: 0.2595		f1: 0.5642		
epoch: 005		acc: 0.8129		nmi: 0.5114		ari: 0.5743		f1: 0.8060		
epoch: 006		acc: 0.8018		nmi: 0.5017		ari: 0.5525		f1: 0.7956		
epoch: 007		acc: 0.8211		nmi: 0.5241		ari: 0.5898		f1: 0.8141		
epoch: 008		acc: 0.8230		nmi: 0.5314		ari: 0.5948		f1: 0.8133		
epoch: 009		acc: 0.8176		nmi: 0.5273		ari: 0.5876		f1: 0.8044		
epoch: 010		acc: 0.8208		nmi: 0.5319		ari: 0.5942		f1: 0.8077		
epoch: 011		acc: 0.8262		nmi: 0.5378		ari: 0.6043		f1: 0.8154		
epoch: 012		acc: 0.8299		nmi: 0.5422		ari: 0.6093		f1: 0.8218		
epoch: 013		acc: 0.8336		nmi: 0.5490		ari: 0.6155		f1: 0.8274		
epoch: 014		acc: 0.8361		nmi: 0.5543		ari: 0.6200		f1: 0.8307		
epoch: 015		acc: 0.8299		nmi: 0.5439		ari: 0.6070		f1: 0.8248		
epoch: 016		acc: 0.8299		nmi: 0.5444		ari: 0.6082		f1: 0.8244		
epoch: 017		acc: 0.8307		nmi: 0.5452		ari: 0.6083		f1: 0.8257		
epoch: 018		acc: 0.8265		nmi: 0.5362		ari: 0.6004		f1: 0.8209		
epoch: 019		acc: 0.8287		nmi: 0.5409		ari: 0.6057		f1: 0.8227		
epoch: 020		acc: 0.8294		nmi: 0.5424		ari: 0.6069		f1: 0.8236		
epoch: 021		acc: 0.8265		nmi: 0.5369		ari: 0.6021		f1: 0.8199		
epoch: 022		acc: 0.8265		nmi: 0.5356		ari: 0.6012		f1: 0.8201		
epoch: 023		acc: 0.8260		nmi: 0.5341		ari: 0.6009		f1: 0.8192		
epoch: 024		acc: 0.8255		nmi: 0.5352		ari: 0.5997		f1: 0.8191		
epoch: 025		acc: 0.8270		nmi: 0.5371		ari: 0.6019		f1: 0.8210		
epoch: 026		acc: 0.8225		nmi: 0.5296		ari: 0.5932		f1: 0.8165		
epoch: 027		acc: 0.8284		nmi: 0.5410		ari: 0.6051		f1: 0.8226		
epoch: 028		acc: 0.8284		nmi: 0.5398		ari: 0.6044		f1: 0.8229		
epoch: 029		acc: 0.8297		nmi: 0.5423		ari: 0.6070		f1: 0.8241		
epoch: 030		acc: 0.8289		nmi: 0.5418		ari: 0.6058		f1: 0.8233		
epoch: 031		acc: 0.8282		nmi: 0.5401		ari: 0.6040		f1: 0.8227		
epoch: 032		acc: 0.8277		nmi: 0.5392		ari: 0.6030		f1: 0.8223		
epoch: 033		acc: 0.8272		nmi: 0.5389		ari: 0.6030		f1: 0.8214		
epoch: 034		acc: 0.8255		nmi: 0.5363		ari: 0.6001		f1: 0.8194		
epoch: 035		acc: 0.8247		nmi: 0.5348		ari: 0.5981		f1: 0.8189		
epoch: 036		acc: 0.8252		nmi: 0.5347		ari: 0.5983		f1: 0.8197		
epoch: 037		acc: 0.8245		nmi: 0.5338		ari: 0.5968		f1: 0.8189		
epoch: 038		acc: 0.8262		nmi: 0.5375		ari: 0.6005		f1: 0.8206		
epoch: 039		acc: 0.8270		nmi: 0.5394		ari: 0.6022		f1: 0.8214		
epoch: 040		acc: 0.8235		nmi: 0.5324		ari: 0.5954		f1: 0.8178		
epoch: 041		acc: 0.8211		nmi: 0.5284		ari: 0.5898		f1: 0.8156		
epoch: 042		acc: 0.8198		nmi: 0.5255		ari: 0.5871		f1: 0.8143		
epoch: 043		acc: 0.8230		nmi: 0.5334		ari: 0.5938		f1: 0.8177		
epoch: 044		acc: 0.8201		nmi: 0.5279		ari: 0.5881		f1: 0.8146		
epoch: 045		acc: 0.8223		nmi: 0.5328		ari: 0.5921		f1: 0.8171		
epoch: 046		acc: 0.8196		nmi: 0.5291		ari: 0.5873		f1: 0.8143		
epoch: 047		acc: 0.8206		nmi: 0.5295		ari: 0.5894		f1: 0.8151		
epoch: 048		acc: 0.8201		nmi: 0.5290		ari: 0.5883		f1: 0.8147		
epoch: 049		acc: 0.8193		nmi: 0.5279		ari: 0.5876		f1: 0.8137		
epoch: 050		acc: 0.8211		nmi: 0.5302		ari: 0.5911		f1: 0.8152		
The total number of parameters is: 0.306752M(1e6).
The max memory allocated to model is: 1051.31 MB.
Time consuming: 7.55s or 0.13m
****************************************Training loop No.9****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=334, out_features=512, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.7720		nmi: 0.4414		ari: 0.4925		f1: 0.7676		
epoch: 002		acc: 0.3108		nmi: 0.0532		ari: 0.0023		f1: 0.1622		
epoch: 003		acc: 0.7996		nmi: 0.4838		ari: 0.5456		f1: 0.7918		
epoch: 004		acc: 0.6041		nmi: 0.3523		ari: 0.2587		f1: 0.5690		
epoch: 005		acc: 0.8132		nmi: 0.5100		ari: 0.5748		f1: 0.8063		
epoch: 006		acc: 0.8011		nmi: 0.5026		ari: 0.5527		f1: 0.7948		
epoch: 007		acc: 0.8198		nmi: 0.5222		ari: 0.5878		f1: 0.8129		
epoch: 008		acc: 0.8245		nmi: 0.5324		ari: 0.5971		f1: 0.8155		
epoch: 009		acc: 0.8206		nmi: 0.5311		ari: 0.5910		f1: 0.8086		
epoch: 010		acc: 0.8211		nmi: 0.5303		ari: 0.5934		f1: 0.8087		
epoch: 011		acc: 0.8220		nmi: 0.5292		ari: 0.5932		f1: 0.8123		
epoch: 012		acc: 0.8292		nmi: 0.5406		ari: 0.6066		f1: 0.8218		
epoch: 013		acc: 0.8299		nmi: 0.5408		ari: 0.6073		f1: 0.8237		
epoch: 014		acc: 0.8329		nmi: 0.5467		ari: 0.6133		f1: 0.8273		
epoch: 015		acc: 0.8329		nmi: 0.5483		ari: 0.6125		f1: 0.8280		
epoch: 016		acc: 0.8316		nmi: 0.5475		ari: 0.6108		f1: 0.8267		
epoch: 017		acc: 0.8304		nmi: 0.5451		ari: 0.6085		f1: 0.8254		
epoch: 018		acc: 0.8294		nmi: 0.5417		ari: 0.6059		f1: 0.8243		
epoch: 019		acc: 0.8326		nmi: 0.5480		ari: 0.6132		f1: 0.8270		
epoch: 020		acc: 0.8282		nmi: 0.5398		ari: 0.6043		f1: 0.8225		
epoch: 021		acc: 0.8319		nmi: 0.5466		ari: 0.6127		f1: 0.8257		
epoch: 022		acc: 0.8280		nmi: 0.5392		ari: 0.6037		f1: 0.8221		
epoch: 023		acc: 0.8314		nmi: 0.5449		ari: 0.6097		f1: 0.8261		
epoch: 024		acc: 0.8277		nmi: 0.5381		ari: 0.6025		f1: 0.8222		
epoch: 025		acc: 0.8289		nmi: 0.5404		ari: 0.6047		f1: 0.8237		
epoch: 026		acc: 0.8282		nmi: 0.5389		ari: 0.6030		f1: 0.8231		
epoch: 027		acc: 0.8262		nmi: 0.5349		ari: 0.5994		f1: 0.8209		
epoch: 028		acc: 0.8252		nmi: 0.5340		ari: 0.5978		f1: 0.8199		
epoch: 029		acc: 0.8272		nmi: 0.5380		ari: 0.6012		f1: 0.8223		
epoch: 030		acc: 0.8262		nmi: 0.5362		ari: 0.5993		f1: 0.8212		
epoch: 031		acc: 0.8282		nmi: 0.5395		ari: 0.6028		f1: 0.8233		
epoch: 032		acc: 0.8287		nmi: 0.5412		ari: 0.6044		f1: 0.8237		
epoch: 033		acc: 0.8250		nmi: 0.5347		ari: 0.5970		f1: 0.8199		
epoch: 034		acc: 0.8245		nmi: 0.5336		ari: 0.5960		f1: 0.8194		
epoch: 035		acc: 0.8247		nmi: 0.5351		ari: 0.5967		f1: 0.8196		
epoch: 036		acc: 0.8235		nmi: 0.5315		ari: 0.5931		f1: 0.8188		
epoch: 037		acc: 0.8250		nmi: 0.5356		ari: 0.5967		f1: 0.8202		
epoch: 038		acc: 0.8255		nmi: 0.5371		ari: 0.5980		f1: 0.8206		
epoch: 039		acc: 0.8228		nmi: 0.5320		ari: 0.5918		f1: 0.8182		
epoch: 040		acc: 0.8211		nmi: 0.5294		ari: 0.5896		f1: 0.8160		
epoch: 041		acc: 0.8211		nmi: 0.5286		ari: 0.5885		f1: 0.8164		
epoch: 042		acc: 0.8218		nmi: 0.5300		ari: 0.5901		f1: 0.8171		
epoch: 043		acc: 0.8196		nmi: 0.5272		ari: 0.5856		f1: 0.8150		
epoch: 044		acc: 0.8225		nmi: 0.5319		ari: 0.5922		f1: 0.8176		
epoch: 045		acc: 0.8203		nmi: 0.5266		ari: 0.5873		f1: 0.8154		
epoch: 046		acc: 0.8188		nmi: 0.5266		ari: 0.5854		f1: 0.8138		
epoch: 047		acc: 0.8201		nmi: 0.5281		ari: 0.5871		f1: 0.8152		
epoch: 048		acc: 0.8181		nmi: 0.5236		ari: 0.5832		f1: 0.8131		
epoch: 049		acc: 0.8220		nmi: 0.5306		ari: 0.5909		f1: 0.8171		
epoch: 050		acc: 0.8225		nmi: 0.5318		ari: 0.5920		f1: 0.8177		
The total number of parameters is: 0.306752M(1e6).
The max memory allocated to model is: 1051.31 MB.
Time consuming: 7.56s or 0.13m
****************************************Training loop No.10****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=334, out_features=512, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.7708		nmi: 0.4389		ari: 0.4898		f1: 0.7665		
epoch: 002		acc: 0.3101		nmi: 0.0489		ari: 0.0022		f1: 0.1610		
epoch: 003		acc: 0.7962		nmi: 0.4778		ari: 0.5390		f1: 0.7879		
epoch: 004		acc: 0.6083		nmi: 0.3546		ari: 0.2620		f1: 0.5731		
epoch: 005		acc: 0.8144		nmi: 0.5121		ari: 0.5772		f1: 0.8077		
epoch: 006		acc: 0.7994		nmi: 0.4957		ari: 0.5488		f1: 0.7927		
epoch: 007		acc: 0.8203		nmi: 0.5228		ari: 0.5893		f1: 0.8127		
epoch: 008		acc: 0.8255		nmi: 0.5363		ari: 0.5996		f1: 0.8155		
epoch: 009		acc: 0.8201		nmi: 0.5328		ari: 0.5928		f1: 0.8060		
epoch: 010		acc: 0.8164		nmi: 0.5241		ari: 0.5853		f1: 0.8025		
epoch: 011		acc: 0.8235		nmi: 0.5342		ari: 0.5985		f1: 0.8120		
epoch: 012		acc: 0.8267		nmi: 0.5378		ari: 0.6035		f1: 0.8177		
epoch: 013		acc: 0.8334		nmi: 0.5481		ari: 0.6144		f1: 0.8268		
epoch: 014		acc: 0.8376		nmi: 0.5560		ari: 0.6217		f1: 0.8324		
epoch: 015		acc: 0.8302		nmi: 0.5444		ari: 0.6078		f1: 0.8249		
epoch: 016		acc: 0.8312		nmi: 0.5451		ari: 0.6088		f1: 0.8261		
epoch: 017		acc: 0.8294		nmi: 0.5434		ari: 0.6065		f1: 0.8241		
epoch: 018		acc: 0.8302		nmi: 0.5443		ari: 0.6073		f1: 0.8248		
epoch: 019		acc: 0.8265		nmi: 0.5370		ari: 0.6006		f1: 0.8207		
epoch: 020		acc: 0.8287		nmi: 0.5410		ari: 0.6049		f1: 0.8227		
epoch: 021		acc: 0.8270		nmi: 0.5374		ari: 0.6024		f1: 0.8203		
epoch: 022		acc: 0.8247		nmi: 0.5323		ari: 0.5967		f1: 0.8187		
epoch: 023		acc: 0.8243		nmi: 0.5319		ari: 0.5966		f1: 0.8175		
epoch: 024		acc: 0.8294		nmi: 0.5416		ari: 0.6069		f1: 0.8232		
epoch: 025		acc: 0.8255		nmi: 0.5349		ari: 0.5993		f1: 0.8192		
epoch: 026		acc: 0.8262		nmi: 0.5363		ari: 0.5999		f1: 0.8205		
epoch: 027		acc: 0.8282		nmi: 0.5393		ari: 0.6039		f1: 0.8226		
epoch: 028		acc: 0.8255		nmi: 0.5344		ari: 0.5988		f1: 0.8197		
epoch: 029		acc: 0.8257		nmi: 0.5347		ari: 0.5982		f1: 0.8206		
epoch: 030		acc: 0.8270		nmi: 0.5370		ari: 0.6014		f1: 0.8214		
epoch: 031		acc: 0.8247		nmi: 0.5331		ari: 0.5968		f1: 0.8192		
epoch: 032		acc: 0.8257		nmi: 0.5347		ari: 0.5983		f1: 0.8204		
epoch: 033		acc: 0.8257		nmi: 0.5354		ari: 0.5993		f1: 0.8201		
epoch: 034		acc: 0.8240		nmi: 0.5320		ari: 0.5954		f1: 0.8185		
epoch: 035		acc: 0.8255		nmi: 0.5349		ari: 0.5988		f1: 0.8198		
epoch: 036		acc: 0.8247		nmi: 0.5331		ari: 0.5962		f1: 0.8196		
epoch: 037		acc: 0.8238		nmi: 0.5324		ari: 0.5943		f1: 0.8187		
epoch: 038		acc: 0.8238		nmi: 0.5330		ari: 0.5945		f1: 0.8186		
epoch: 039		acc: 0.8247		nmi: 0.5356		ari: 0.5963		f1: 0.8199		
epoch: 040		acc: 0.8247		nmi: 0.5363		ari: 0.5959		f1: 0.8200		
epoch: 041		acc: 0.8213		nmi: 0.5293		ari: 0.5891		f1: 0.8164		
epoch: 042		acc: 0.8245		nmi: 0.5355		ari: 0.5954		f1: 0.8197		
epoch: 043		acc: 0.8193		nmi: 0.5257		ari: 0.5855		f1: 0.8143		
epoch: 044		acc: 0.8218		nmi: 0.5313		ari: 0.5902		f1: 0.8169		
epoch: 045		acc: 0.8208		nmi: 0.5287		ari: 0.5884		f1: 0.8158		
epoch: 046		acc: 0.8203		nmi: 0.5266		ari: 0.5873		f1: 0.8153		
epoch: 047		acc: 0.8174		nmi: 0.5207		ari: 0.5813		f1: 0.8124		
epoch: 048		acc: 0.8183		nmi: 0.5240		ari: 0.5835		f1: 0.8133		
epoch: 049		acc: 0.8201		nmi: 0.5279		ari: 0.5876		f1: 0.8149		
epoch: 050		acc: 0.8191		nmi: 0.5254		ari: 0.5850		f1: 0.8140		
The total number of parameters is: 0.306752M(1e6).
The max memory allocated to model is: 1051.31 MB.
Time consuming: 7.61s or 0.13m
Namespace(is_pretrain=False, plot_clustering_tsne=False, plot_embedding_heatmap=False, adj_norm=False, adj_loop=True, adj_symmetric=True, desc='default', model_name='SYNC', dataset_name='dblp', root=None, k=None, t=None, loops=10, feature_type='tensor', label_type='npy', adj_type='tensor', seed=325, epsilon=0.0, device='cuda', clusters=4, nodes=4057, lr=0.02, max_epoch=50, pretrain_lr=0.001, pretrain_epoch=30, input_dim=334, log_save_path='./logs/SYNC/dblp/', dataset_path='../data/', clustering_tsne_save_path='./img/clustering/SYNC/dblp/', embedding_heatmap_save_path='./img/heatmap/SYNC/dblp/', pretrain_save_path='./pretrain/pretrain_tigae/SYNC/dblp/', hidden_dim=256, embedding_dim=16, linear_dim=512, beta=1)
Total loops: 10
****************************************Mean value:****************************************
acc: 0.8349±0.0014		nmi: 0.5513±0.0027		ari: 0.6170±0.0028		f1: 0.8294±0.0014
Training over! Punch out!
Loading cite dataset from local
****************************************Training loop No.1****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=3703, out_features=512, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.6730		nmi: 0.4054		ari: 0.4181		f1: 0.6283		
epoch: 002		acc: 0.6330		nmi: 0.3911		ari: 0.3314		f1: 0.5663		
epoch: 003		acc: 0.6907		nmi: 0.4369		ari: 0.4290		f1: 0.6341		
epoch: 004		acc: 0.7048		nmi: 0.4469		ari: 0.4598		f1: 0.6436		
epoch: 005		acc: 0.7066		nmi: 0.4524		ari: 0.4623		f1: 0.6463		
epoch: 006		acc: 0.7106		nmi: 0.4529		ari: 0.4684		f1: 0.6514		
epoch: 007		acc: 0.7142		nmi: 0.4600		ari: 0.4755		f1: 0.6546		
epoch: 008		acc: 0.7142		nmi: 0.4581		ari: 0.4739		f1: 0.6536		
epoch: 009		acc: 0.7154		nmi: 0.4599		ari: 0.4769		f1: 0.6538		
epoch: 010		acc: 0.7148		nmi: 0.4581		ari: 0.4771		f1: 0.6526		
epoch: 011		acc: 0.7166		nmi: 0.4612		ari: 0.4785		f1: 0.6563		
epoch: 012		acc: 0.7151		nmi: 0.4587		ari: 0.4765		f1: 0.6558		
epoch: 013		acc: 0.7166		nmi: 0.4612		ari: 0.4788		f1: 0.6584		
epoch: 014		acc: 0.7172		nmi: 0.4612		ari: 0.4795		f1: 0.6570		
epoch: 015		acc: 0.7151		nmi: 0.4583		ari: 0.4764		f1: 0.6564		
epoch: 016		acc: 0.7136		nmi: 0.4556		ari: 0.4738		f1: 0.6550		
epoch: 017		acc: 0.7169		nmi: 0.4603		ari: 0.4790		f1: 0.6579		
epoch: 018		acc: 0.7160		nmi: 0.4604		ari: 0.4778		f1: 0.6567		
epoch: 019		acc: 0.7145		nmi: 0.4572		ari: 0.4757		f1: 0.6561		
epoch: 020		acc: 0.7151		nmi: 0.4584		ari: 0.4763		f1: 0.6560		
epoch: 021		acc: 0.7139		nmi: 0.4562		ari: 0.4746		f1: 0.6554		
epoch: 022		acc: 0.7160		nmi: 0.4605		ari: 0.4783		f1: 0.6574		
epoch: 023		acc: 0.7154		nmi: 0.4577		ari: 0.4770		f1: 0.6575		
epoch: 024		acc: 0.7142		nmi: 0.4568		ari: 0.4760		f1: 0.6560		
epoch: 025		acc: 0.7142		nmi: 0.4580		ari: 0.4757		f1: 0.6564		
epoch: 026		acc: 0.7148		nmi: 0.4571		ari: 0.4762		f1: 0.6575		
epoch: 027		acc: 0.7151		nmi: 0.4575		ari: 0.4775		f1: 0.6580		
epoch: 028		acc: 0.7154		nmi: 0.4588		ari: 0.4778		f1: 0.6577		
epoch: 029		acc: 0.7154		nmi: 0.4571		ari: 0.4778		f1: 0.6581		
epoch: 030		acc: 0.7148		nmi: 0.4560		ari: 0.4770		f1: 0.6577		
epoch: 031		acc: 0.7151		nmi: 0.4575		ari: 0.4780		f1: 0.6575		
epoch: 032		acc: 0.7142		nmi: 0.4561		ari: 0.4762		f1: 0.6567		
epoch: 033		acc: 0.7136		nmi: 0.4554		ari: 0.4755		f1: 0.6567		
epoch: 034		acc: 0.7154		nmi: 0.4574		ari: 0.4782		f1: 0.6584		
epoch: 035		acc: 0.7154		nmi: 0.4577		ari: 0.4784		f1: 0.6590		
epoch: 036		acc: 0.7157		nmi: 0.4576		ari: 0.4787		f1: 0.6590		
epoch: 037		acc: 0.7151		nmi: 0.4568		ari: 0.4777		f1: 0.6587		
epoch: 038		acc: 0.7133		nmi: 0.4544		ari: 0.4749		f1: 0.6571		
epoch: 039		acc: 0.7151		nmi: 0.4566		ari: 0.4780		f1: 0.6587		
epoch: 040		acc: 0.7139		nmi: 0.4553		ari: 0.4761		f1: 0.6578		
epoch: 041		acc: 0.7139		nmi: 0.4552		ari: 0.4762		f1: 0.6577		
epoch: 042		acc: 0.7139		nmi: 0.4551		ari: 0.4764		f1: 0.6577		
epoch: 043		acc: 0.7142		nmi: 0.4553		ari: 0.4764		f1: 0.6579		
epoch: 044		acc: 0.7142		nmi: 0.4552		ari: 0.4764		f1: 0.6585		
epoch: 045		acc: 0.7142		nmi: 0.4557		ari: 0.4769		f1: 0.6580		
epoch: 046		acc: 0.7151		nmi: 0.4566		ari: 0.4779		f1: 0.6592		
epoch: 047		acc: 0.7139		nmi: 0.4547		ari: 0.4760		f1: 0.6582		
epoch: 048		acc: 0.7142		nmi: 0.4544		ari: 0.4764		f1: 0.6584		
epoch: 049		acc: 0.7139		nmi: 0.4546		ari: 0.4762		f1: 0.6582		
epoch: 050		acc: 0.7142		nmi: 0.4549		ari: 0.4764		f1: 0.6585		
The total number of parameters is: 2.031712M(1e6).
The max memory allocated to model is: 783.83 MB.
Time consuming: 7.97s or 0.13m
****************************************Training loop No.2****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=3703, out_features=512, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.6757		nmi: 0.4072		ari: 0.4211		f1: 0.6309		
epoch: 002		acc: 0.6273		nmi: 0.3877		ari: 0.3226		f1: 0.5607		
epoch: 003		acc: 0.6898		nmi: 0.4335		ari: 0.4272		f1: 0.6299		
epoch: 004		acc: 0.7054		nmi: 0.4466		ari: 0.4608		f1: 0.6423		
epoch: 005		acc: 0.7069		nmi: 0.4506		ari: 0.4634		f1: 0.6465		
epoch: 006		acc: 0.7081		nmi: 0.4509		ari: 0.4641		f1: 0.6500		
epoch: 007		acc: 0.7130		nmi: 0.4580		ari: 0.4715		f1: 0.6543		
epoch: 008		acc: 0.7133		nmi: 0.4581		ari: 0.4732		f1: 0.6526		
epoch: 009		acc: 0.7163		nmi: 0.4611		ari: 0.4778		f1: 0.6536		
epoch: 010		acc: 0.7121		nmi: 0.4544		ari: 0.4711		f1: 0.6512		
epoch: 011		acc: 0.7151		nmi: 0.4592		ari: 0.4766		f1: 0.6537		
epoch: 012		acc: 0.7130		nmi: 0.4560		ari: 0.4733		f1: 0.6522		
epoch: 013		acc: 0.7139		nmi: 0.4591		ari: 0.4750		f1: 0.6539		
epoch: 014		acc: 0.7121		nmi: 0.4562		ari: 0.4723		f1: 0.6520		
epoch: 015		acc: 0.7112		nmi: 0.4549		ari: 0.4707		f1: 0.6516		
epoch: 016		acc: 0.7142		nmi: 0.4584		ari: 0.4758		f1: 0.6548		
epoch: 017		acc: 0.7115		nmi: 0.4547		ari: 0.4708		f1: 0.6512		
epoch: 018		acc: 0.7130		nmi: 0.4573		ari: 0.4735		f1: 0.6535		
epoch: 019		acc: 0.7130		nmi: 0.4559		ari: 0.4727		f1: 0.6532		
epoch: 020		acc: 0.7096		nmi: 0.4540		ari: 0.4692		f1: 0.6501		
epoch: 021		acc: 0.7130		nmi: 0.4573		ari: 0.4746		f1: 0.6535		
epoch: 022		acc: 0.7112		nmi: 0.4556		ari: 0.4720		f1: 0.6514		
epoch: 023		acc: 0.7121		nmi: 0.4569		ari: 0.4736		f1: 0.6522		
epoch: 024		acc: 0.7115		nmi: 0.4562		ari: 0.4729		f1: 0.6517		
epoch: 025		acc: 0.7115		nmi: 0.4559		ari: 0.4723		f1: 0.6523		
epoch: 026		acc: 0.7121		nmi: 0.4559		ari: 0.4738		f1: 0.6529		
epoch: 027		acc: 0.7124		nmi: 0.4566		ari: 0.4746		f1: 0.6531		
epoch: 028		acc: 0.7115		nmi: 0.4548		ari: 0.4728		f1: 0.6523		
epoch: 029		acc: 0.7099		nmi: 0.4537		ari: 0.4706		f1: 0.6511		
epoch: 030		acc: 0.7115		nmi: 0.4561		ari: 0.4733		f1: 0.6524		
epoch: 031		acc: 0.7109		nmi: 0.4534		ari: 0.4723		f1: 0.6519		
epoch: 032		acc: 0.7106		nmi: 0.4524		ari: 0.4711		f1: 0.6524		
epoch: 033		acc: 0.7106		nmi: 0.4532		ari: 0.4713		f1: 0.6523		
epoch: 034		acc: 0.7102		nmi: 0.4534		ari: 0.4714		f1: 0.6516		
epoch: 035		acc: 0.7102		nmi: 0.4527		ari: 0.4712		f1: 0.6521		
epoch: 036		acc: 0.7102		nmi: 0.4527		ari: 0.4715		f1: 0.6516		
epoch: 037		acc: 0.7106		nmi: 0.4531		ari: 0.4714		f1: 0.6524		
epoch: 038		acc: 0.7112		nmi: 0.4543		ari: 0.4725		f1: 0.6529		
epoch: 039		acc: 0.7115		nmi: 0.4543		ari: 0.4730		f1: 0.6533		
epoch: 040		acc: 0.7102		nmi: 0.4529		ari: 0.4714		f1: 0.6522		
epoch: 041		acc: 0.7102		nmi: 0.4525		ari: 0.4709		f1: 0.6522		
epoch: 042		acc: 0.7106		nmi: 0.4534		ari: 0.4717		f1: 0.6524		
epoch: 043		acc: 0.7106		nmi: 0.4538		ari: 0.4721		f1: 0.6525		
epoch: 044		acc: 0.7106		nmi: 0.4536		ari: 0.4717		f1: 0.6525		
epoch: 045		acc: 0.7102		nmi: 0.4527		ari: 0.4711		f1: 0.6522		
epoch: 046		acc: 0.7096		nmi: 0.4515		ari: 0.4698		f1: 0.6523		
epoch: 047		acc: 0.7109		nmi: 0.4533		ari: 0.4722		f1: 0.6528		
epoch: 048		acc: 0.7096		nmi: 0.4518		ari: 0.4702		f1: 0.6518		
epoch: 049		acc: 0.7099		nmi: 0.4519		ari: 0.4707		f1: 0.6520		
epoch: 050		acc: 0.7102		nmi: 0.4520		ari: 0.4706		f1: 0.6528		
The total number of parameters is: 2.031712M(1e6).
The max memory allocated to model is: 799.76 MB.
Time consuming: 5.04s or 0.08m
****************************************Training loop No.3****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=3703, out_features=512, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.6706		nmi: 0.4039		ari: 0.4151		f1: 0.6265		
epoch: 002		acc: 0.6288		nmi: 0.3877		ari: 0.3233		f1: 0.5614		
epoch: 003		acc: 0.6862		nmi: 0.4291		ari: 0.4234		f1: 0.6264		
epoch: 004		acc: 0.7066		nmi: 0.4508		ari: 0.4642		f1: 0.6444		
epoch: 005		acc: 0.7081		nmi: 0.4515		ari: 0.4643		f1: 0.6488		
epoch: 006		acc: 0.7066		nmi: 0.4502		ari: 0.4623		f1: 0.6483		
epoch: 007		acc: 0.7078		nmi: 0.4508		ari: 0.4655		f1: 0.6484		
epoch: 008		acc: 0.7136		nmi: 0.4571		ari: 0.4734		f1: 0.6544		
epoch: 009		acc: 0.7145		nmi: 0.4579		ari: 0.4757		f1: 0.6535		
epoch: 010		acc: 0.7133		nmi: 0.4552		ari: 0.4739		f1: 0.6519		
epoch: 011		acc: 0.7145		nmi: 0.4569		ari: 0.4774		f1: 0.6540		
epoch: 012		acc: 0.7136		nmi: 0.4580		ari: 0.4763		f1: 0.6536		
epoch: 013		acc: 0.7130		nmi: 0.4579		ari: 0.4765		f1: 0.6524		
epoch: 014		acc: 0.7121		nmi: 0.4566		ari: 0.4743		f1: 0.6519		
epoch: 015		acc: 0.7133		nmi: 0.4580		ari: 0.4759		f1: 0.6526		
epoch: 016		acc: 0.7145		nmi: 0.4601		ari: 0.4790		f1: 0.6538		
epoch: 017		acc: 0.7127		nmi: 0.4564		ari: 0.4754		f1: 0.6523		
epoch: 018		acc: 0.7124		nmi: 0.4574		ari: 0.4752		f1: 0.6522		
epoch: 019		acc: 0.7121		nmi: 0.4568		ari: 0.4749		f1: 0.6511		
epoch: 020		acc: 0.7127		nmi: 0.4575		ari: 0.4760		f1: 0.6525		
epoch: 021		acc: 0.7127		nmi: 0.4571		ari: 0.4756		f1: 0.6529		
epoch: 022		acc: 0.7133		nmi: 0.4585		ari: 0.4765		f1: 0.6534		
epoch: 023		acc: 0.7115		nmi: 0.4555		ari: 0.4744		f1: 0.6518		
epoch: 024		acc: 0.7139		nmi: 0.4584		ari: 0.4781		f1: 0.6546		
epoch: 025		acc: 0.7096		nmi: 0.4532		ari: 0.4716		f1: 0.6507		
epoch: 026		acc: 0.7118		nmi: 0.4559		ari: 0.4753		f1: 0.6523		
epoch: 027		acc: 0.7106		nmi: 0.4546		ari: 0.4735		f1: 0.6517		
epoch: 028		acc: 0.7124		nmi: 0.4563		ari: 0.4761		f1: 0.6532		
epoch: 029		acc: 0.7099		nmi: 0.4525		ari: 0.4718		f1: 0.6513		
epoch: 030		acc: 0.7121		nmi: 0.4561		ari: 0.4758		f1: 0.6530		
epoch: 031		acc: 0.7115		nmi: 0.4552		ari: 0.4752		f1: 0.6528		
epoch: 032		acc: 0.7096		nmi: 0.4522		ari: 0.4721		f1: 0.6511		
epoch: 033		acc: 0.7115		nmi: 0.4550		ari: 0.4749		f1: 0.6527		
epoch: 034		acc: 0.7106		nmi: 0.4539		ari: 0.4743		f1: 0.6513		
epoch: 035		acc: 0.7118		nmi: 0.4554		ari: 0.4754		f1: 0.6529		
epoch: 036		acc: 0.7109		nmi: 0.4543		ari: 0.4746		f1: 0.6522		
epoch: 037		acc: 0.7099		nmi: 0.4527		ari: 0.4732		f1: 0.6514		
epoch: 038		acc: 0.7106		nmi: 0.4533		ari: 0.4737		f1: 0.6519		
epoch: 039		acc: 0.7115		nmi: 0.4554		ari: 0.4759		f1: 0.6527		
epoch: 040		acc: 0.7109		nmi: 0.4538		ari: 0.4741		f1: 0.6528		
epoch: 041		acc: 0.7106		nmi: 0.4537		ari: 0.4737		f1: 0.6520		
epoch: 042		acc: 0.7109		nmi: 0.4541		ari: 0.4747		f1: 0.6523		
epoch: 043		acc: 0.7109		nmi: 0.4541		ari: 0.4746		f1: 0.6522		
epoch: 044		acc: 0.7115		nmi: 0.4541		ari: 0.4749		f1: 0.6534		
epoch: 045		acc: 0.7112		nmi: 0.4533		ari: 0.4740		f1: 0.6536		
epoch: 046		acc: 0.7106		nmi: 0.4536		ari: 0.4739		f1: 0.6520		
epoch: 047		acc: 0.7106		nmi: 0.4534		ari: 0.4740		f1: 0.6520		
epoch: 048		acc: 0.7099		nmi: 0.4524		ari: 0.4729		f1: 0.6514		
epoch: 049		acc: 0.7099		nmi: 0.4526		ari: 0.4729		f1: 0.6515		
epoch: 050		acc: 0.7112		nmi: 0.4536		ari: 0.4741		f1: 0.6536		
The total number of parameters is: 2.031712M(1e6).
The max memory allocated to model is: 799.76 MB.
Time consuming: 5.02s or 0.08m
****************************************Training loop No.4****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=3703, out_features=512, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.6748		nmi: 0.4058		ari: 0.4204		f1: 0.6311		
epoch: 002		acc: 0.6390		nmi: 0.3897		ari: 0.3389		f1: 0.5709		
epoch: 003		acc: 0.6868		nmi: 0.4310		ari: 0.4198		f1: 0.6287		
epoch: 004		acc: 0.7051		nmi: 0.4474		ari: 0.4606		f1: 0.6441		
epoch: 005		acc: 0.7048		nmi: 0.4477		ari: 0.4594		f1: 0.6453		
epoch: 006		acc: 0.7093		nmi: 0.4523		ari: 0.4664		f1: 0.6512		
epoch: 007		acc: 0.7118		nmi: 0.4554		ari: 0.4687		f1: 0.6533		
epoch: 008		acc: 0.7163		nmi: 0.4618		ari: 0.4773		f1: 0.6572		
epoch: 009		acc: 0.7160		nmi: 0.4593		ari: 0.4769		f1: 0.6551		
epoch: 010		acc: 0.7124		nmi: 0.4545		ari: 0.4712		f1: 0.6518		
epoch: 011		acc: 0.7142		nmi: 0.4553		ari: 0.4740		f1: 0.6549		
epoch: 012		acc: 0.7166		nmi: 0.4619		ari: 0.4783		f1: 0.6582		
epoch: 013		acc: 0.7172		nmi: 0.4613		ari: 0.4790		f1: 0.6603		
epoch: 014		acc: 0.7163		nmi: 0.4602		ari: 0.4777		f1: 0.6590		
epoch: 015		acc: 0.7145		nmi: 0.4574		ari: 0.4747		f1: 0.6579		
epoch: 016		acc: 0.7148		nmi: 0.4587		ari: 0.4756		f1: 0.6576		
epoch: 017		acc: 0.7160		nmi: 0.4606		ari: 0.4780		f1: 0.6583		
epoch: 018		acc: 0.7148		nmi: 0.4580		ari: 0.4760		f1: 0.6575		
epoch: 019		acc: 0.7139		nmi: 0.4588		ari: 0.4750		f1: 0.6576		
epoch: 020		acc: 0.7142		nmi: 0.4587		ari: 0.4756		f1: 0.6579		
epoch: 021		acc: 0.7130		nmi: 0.4565		ari: 0.4734		f1: 0.6563		
epoch: 022		acc: 0.7121		nmi: 0.4554		ari: 0.4727		f1: 0.6538		
epoch: 023		acc: 0.7127		nmi: 0.4553		ari: 0.4725		f1: 0.6566		
epoch: 024		acc: 0.7133		nmi: 0.4573		ari: 0.4739		f1: 0.6566		
epoch: 025		acc: 0.7139		nmi: 0.4569		ari: 0.4747		f1: 0.6583		
epoch: 026		acc: 0.7142		nmi: 0.4572		ari: 0.4755		f1: 0.6590		
epoch: 027		acc: 0.7142		nmi: 0.4582		ari: 0.4762		f1: 0.6581		
epoch: 028		acc: 0.7124		nmi: 0.4547		ari: 0.4724		f1: 0.6572		
epoch: 029		acc: 0.7145		nmi: 0.4575		ari: 0.4759		f1: 0.6591		
epoch: 030		acc: 0.7118		nmi: 0.4543		ari: 0.4716		f1: 0.6566		
epoch: 031		acc: 0.7136		nmi: 0.4564		ari: 0.4750		f1: 0.6577		
epoch: 032		acc: 0.7136		nmi: 0.4557		ari: 0.4742		f1: 0.6587		
epoch: 033		acc: 0.7127		nmi: 0.4551		ari: 0.4731		f1: 0.6574		
epoch: 034		acc: 0.7130		nmi: 0.4555		ari: 0.4740		f1: 0.6577		
epoch: 035		acc: 0.7136		nmi: 0.4566		ari: 0.4754		f1: 0.6577		
epoch: 036		acc: 0.7130		nmi: 0.4554		ari: 0.4742		f1: 0.6576		
epoch: 037		acc: 0.7121		nmi: 0.4550		ari: 0.4730		f1: 0.6571		
epoch: 038		acc: 0.7118		nmi: 0.4538		ari: 0.4721		f1: 0.6573		
epoch: 039		acc: 0.7130		nmi: 0.4550		ari: 0.4737		f1: 0.6589		
epoch: 040		acc: 0.7121		nmi: 0.4544		ari: 0.4729		f1: 0.6570		
epoch: 041		acc: 0.7124		nmi: 0.4539		ari: 0.4730		f1: 0.6577		
epoch: 042		acc: 0.7121		nmi: 0.4542		ari: 0.4732		f1: 0.6569		
epoch: 043		acc: 0.7112		nmi: 0.4532		ari: 0.4714		f1: 0.6561		
epoch: 044		acc: 0.7127		nmi: 0.4547		ari: 0.4737		f1: 0.6580		
epoch: 045		acc: 0.7115		nmi: 0.4527		ari: 0.4717		f1: 0.6570		
epoch: 046		acc: 0.7121		nmi: 0.4542		ari: 0.4729		f1: 0.6569		
epoch: 047		acc: 0.7124		nmi: 0.4542		ari: 0.4732		f1: 0.6578		
epoch: 048		acc: 0.7121		nmi: 0.4534		ari: 0.4729		f1: 0.6574		
epoch: 049		acc: 0.7124		nmi: 0.4542		ari: 0.4729		f1: 0.6577		
epoch: 050		acc: 0.7118		nmi: 0.4539		ari: 0.4727		f1: 0.6562		
The total number of parameters is: 2.031712M(1e6).
The max memory allocated to model is: 799.76 MB.
Time consuming: 5.12s or 0.09m
****************************************Training loop No.5****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=3703, out_features=512, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.6790		nmi: 0.4141		ari: 0.4274		f1: 0.6354		
epoch: 002		acc: 0.6456		nmi: 0.3981		ari: 0.3506		f1: 0.5767		
epoch: 003		acc: 0.6877		nmi: 0.4294		ari: 0.4243		f1: 0.6299		
epoch: 004		acc: 0.7030		nmi: 0.4450		ari: 0.4590		f1: 0.6407		
epoch: 005		acc: 0.7081		nmi: 0.4530		ari: 0.4659		f1: 0.6465		
epoch: 006		acc: 0.7093		nmi: 0.4542		ari: 0.4689		f1: 0.6479		
epoch: 007		acc: 0.7151		nmi: 0.4614		ari: 0.4763		f1: 0.6549		
epoch: 008		acc: 0.7157		nmi: 0.4613		ari: 0.4770		f1: 0.6539		
epoch: 009		acc: 0.7148		nmi: 0.4592		ari: 0.4770		f1: 0.6517		
epoch: 010		acc: 0.7142		nmi: 0.4587		ari: 0.4759		f1: 0.6514		
epoch: 011		acc: 0.7151		nmi: 0.4586		ari: 0.4773		f1: 0.6530		
epoch: 012		acc: 0.7166		nmi: 0.4641		ari: 0.4805		f1: 0.6540		
epoch: 013		acc: 0.7145		nmi: 0.4580		ari: 0.4766		f1: 0.6532		
epoch: 014		acc: 0.7148		nmi: 0.4598		ari: 0.4771		f1: 0.6527		
epoch: 015		acc: 0.7175		nmi: 0.4633		ari: 0.4808		f1: 0.6563		
epoch: 016		acc: 0.7160		nmi: 0.4603		ari: 0.4792		f1: 0.6545		
epoch: 017		acc: 0.7160		nmi: 0.4599		ari: 0.4789		f1: 0.6539		
epoch: 018		acc: 0.7157		nmi: 0.4599		ari: 0.4785		f1: 0.6536		
epoch: 019		acc: 0.7145		nmi: 0.4589		ari: 0.4762		f1: 0.6532		
epoch: 020		acc: 0.7139		nmi: 0.4591		ari: 0.4755		f1: 0.6521		
epoch: 021		acc: 0.7154		nmi: 0.4609		ari: 0.4783		f1: 0.6535		
epoch: 022		acc: 0.7154		nmi: 0.4608		ari: 0.4783		f1: 0.6539		
epoch: 023		acc: 0.7166		nmi: 0.4623		ari: 0.4809		f1: 0.6538		
epoch: 024		acc: 0.7154		nmi: 0.4602		ari: 0.4784		f1: 0.6541		
epoch: 025		acc: 0.7169		nmi: 0.4630		ari: 0.4817		f1: 0.6553		
epoch: 026		acc: 0.7157		nmi: 0.4612		ari: 0.4793		f1: 0.6555		
epoch: 027		acc: 0.7154		nmi: 0.4604		ari: 0.4794		f1: 0.6540		
epoch: 028		acc: 0.7136		nmi: 0.4592		ari: 0.4771		f1: 0.6528		
epoch: 029		acc: 0.7160		nmi: 0.4620		ari: 0.4805		f1: 0.6549		
epoch: 030		acc: 0.7145		nmi: 0.4601		ari: 0.4783		f1: 0.6535		
epoch: 031		acc: 0.7157		nmi: 0.4599		ari: 0.4801		f1: 0.6551		
epoch: 032		acc: 0.7157		nmi: 0.4594		ari: 0.4800		f1: 0.6556		
epoch: 033		acc: 0.7145		nmi: 0.4574		ari: 0.4780		f1: 0.6541		
epoch: 034		acc: 0.7136		nmi: 0.4572		ari: 0.4771		f1: 0.6528		
epoch: 035		acc: 0.7136		nmi: 0.4564		ari: 0.4771		f1: 0.6528		
epoch: 036		acc: 0.7148		nmi: 0.4582		ari: 0.4789		f1: 0.6544		
epoch: 037		acc: 0.7142		nmi: 0.4580		ari: 0.4779		f1: 0.6545		
epoch: 038		acc: 0.7142		nmi: 0.4573		ari: 0.4780		f1: 0.6539		
epoch: 039		acc: 0.7151		nmi: 0.4595		ari: 0.4797		f1: 0.6548		
epoch: 040		acc: 0.7145		nmi: 0.4583		ari: 0.4785		f1: 0.6542		
epoch: 041		acc: 0.7148		nmi: 0.4582		ari: 0.4785		f1: 0.6556		
epoch: 042		acc: 0.7142		nmi: 0.4575		ari: 0.4780		f1: 0.6546		
epoch: 043		acc: 0.7136		nmi: 0.4570		ari: 0.4772		f1: 0.6534		
epoch: 044		acc: 0.7142		nmi: 0.4579		ari: 0.4781		f1: 0.6540		
epoch: 045		acc: 0.7139		nmi: 0.4572		ari: 0.4777		f1: 0.6543		
epoch: 046		acc: 0.7133		nmi: 0.4564		ari: 0.4769		f1: 0.6533		
epoch: 047		acc: 0.7136		nmi: 0.4566		ari: 0.4771		f1: 0.6541		
epoch: 048		acc: 0.7151		nmi: 0.4586		ari: 0.4794		f1: 0.6553		
epoch: 049		acc: 0.7136		nmi: 0.4570		ari: 0.4771		f1: 0.6535		
epoch: 050		acc: 0.7145		nmi: 0.4580		ari: 0.4786		f1: 0.6549		
The total number of parameters is: 2.031712M(1e6).
The max memory allocated to model is: 799.76 MB.
Time consuming: 5.05s or 0.08m
****************************************Training loop No.6****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=3703, out_features=512, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.6811		nmi: 0.4135		ari: 0.4275		f1: 0.6362		
epoch: 002		acc: 0.6435		nmi: 0.3997		ari: 0.3466		f1: 0.5736		
epoch: 003		acc: 0.6868		nmi: 0.4311		ari: 0.4230		f1: 0.6276		
epoch: 004		acc: 0.7072		nmi: 0.4504		ari: 0.4642		f1: 0.6445		
epoch: 005		acc: 0.7072		nmi: 0.4485		ari: 0.4612		f1: 0.6484		
epoch: 006		acc: 0.7112		nmi: 0.4553		ari: 0.4686		f1: 0.6517		
epoch: 007		acc: 0.7115		nmi: 0.4559		ari: 0.4702		f1: 0.6520		
epoch: 008		acc: 0.7139		nmi: 0.4581		ari: 0.4747		f1: 0.6511		
epoch: 009		acc: 0.7148		nmi: 0.4583		ari: 0.4751		f1: 0.6524		
epoch: 010		acc: 0.7169		nmi: 0.4625		ari: 0.4804		f1: 0.6543		
epoch: 011		acc: 0.7172		nmi: 0.4638		ari: 0.4806		f1: 0.6546		
epoch: 012		acc: 0.7163		nmi: 0.4601		ari: 0.4790		f1: 0.6550		
epoch: 013		acc: 0.7142		nmi: 0.4581		ari: 0.4765		f1: 0.6539		
epoch: 014		acc: 0.7142		nmi: 0.4571		ari: 0.4759		f1: 0.6532		
epoch: 015		acc: 0.7166		nmi: 0.4613		ari: 0.4799		f1: 0.6553		
epoch: 016		acc: 0.7175		nmi: 0.4626		ari: 0.4815		f1: 0.6557		
epoch: 017		acc: 0.7157		nmi: 0.4595		ari: 0.4784		f1: 0.6551		
epoch: 018		acc: 0.7154		nmi: 0.4608		ari: 0.4779		f1: 0.6544		
epoch: 019		acc: 0.7154		nmi: 0.4603		ari: 0.4783		f1: 0.6537		
epoch: 020		acc: 0.7163		nmi: 0.4614		ari: 0.4804		f1: 0.6539		
epoch: 021		acc: 0.7142		nmi: 0.4583		ari: 0.4762		f1: 0.6531		
epoch: 022		acc: 0.7148		nmi: 0.4592		ari: 0.4777		f1: 0.6538		
epoch: 023		acc: 0.7142		nmi: 0.4581		ari: 0.4770		f1: 0.6533		
epoch: 024		acc: 0.7163		nmi: 0.4617		ari: 0.4802		f1: 0.6552		
epoch: 025		acc: 0.7154		nmi: 0.4604		ari: 0.4795		f1: 0.6544		
epoch: 026		acc: 0.7163		nmi: 0.4621		ari: 0.4813		f1: 0.6547		
epoch: 027		acc: 0.7139		nmi: 0.4580		ari: 0.4776		f1: 0.6533		
epoch: 028		acc: 0.7145		nmi: 0.4586		ari: 0.4787		f1: 0.6544		
epoch: 029		acc: 0.7130		nmi: 0.4554		ari: 0.4764		f1: 0.6525		
epoch: 030		acc: 0.7145		nmi: 0.4588		ari: 0.4787		f1: 0.6540		
epoch: 031		acc: 0.7151		nmi: 0.4599		ari: 0.4796		f1: 0.6551		
epoch: 032		acc: 0.7148		nmi: 0.4586		ari: 0.4790		f1: 0.6548		
epoch: 033		acc: 0.7151		nmi: 0.4590		ari: 0.4794		f1: 0.6550		
epoch: 034		acc: 0.7151		nmi: 0.4588		ari: 0.4792		f1: 0.6555		
epoch: 035		acc: 0.7154		nmi: 0.4592		ari: 0.4799		f1: 0.6559		
epoch: 036		acc: 0.7139		nmi: 0.4570		ari: 0.4775		f1: 0.6542		
epoch: 037		acc: 0.7148		nmi: 0.4589		ari: 0.4795		f1: 0.6548		
epoch: 038		acc: 0.7151		nmi: 0.4581		ari: 0.4792		f1: 0.6563		
epoch: 039		acc: 0.7142		nmi: 0.4575		ari: 0.4783		f1: 0.6551		
epoch: 040		acc: 0.7142		nmi: 0.4574		ari: 0.4780		f1: 0.6555		
epoch: 041		acc: 0.7142		nmi: 0.4570		ari: 0.4779		f1: 0.6556		
epoch: 042		acc: 0.7139		nmi: 0.4561		ari: 0.4772		f1: 0.6559		
epoch: 043		acc: 0.7136		nmi: 0.4559		ari: 0.4770		f1: 0.6551		
epoch: 044		acc: 0.7142		nmi: 0.4571		ari: 0.4780		f1: 0.6556		
epoch: 045		acc: 0.7136		nmi: 0.4556		ari: 0.4764		f1: 0.6556		
epoch: 046		acc: 0.7127		nmi: 0.4543		ari: 0.4753		f1: 0.6550		
epoch: 047		acc: 0.7145		nmi: 0.4567		ari: 0.4782		f1: 0.6565		
epoch: 048		acc: 0.7142		nmi: 0.4568		ari: 0.4778		f1: 0.6562		
epoch: 049		acc: 0.7136		nmi: 0.4555		ari: 0.4766		f1: 0.6557		
epoch: 050		acc: 0.7130		nmi: 0.4545		ari: 0.4759		f1: 0.6551		
The total number of parameters is: 2.031712M(1e6).
The max memory allocated to model is: 799.76 MB.
Time consuming: 5.26s or 0.09m
****************************************Training loop No.7****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=3703, out_features=512, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.6778		nmi: 0.4116		ari: 0.4232		f1: 0.6330		
epoch: 002		acc: 0.6318		nmi: 0.3945		ari: 0.3334		f1: 0.5628		
epoch: 003		acc: 0.6937		nmi: 0.4383		ari: 0.4350		f1: 0.6361		
epoch: 004		acc: 0.7054		nmi: 0.4469		ari: 0.4609		f1: 0.6427		
epoch: 005		acc: 0.7133		nmi: 0.4617		ari: 0.4736		f1: 0.6529		
epoch: 006		acc: 0.7096		nmi: 0.4543		ari: 0.4680		f1: 0.6507		
epoch: 007		acc: 0.7118		nmi: 0.4563		ari: 0.4701		f1: 0.6540		
epoch: 008		acc: 0.7157		nmi: 0.4619		ari: 0.4770		f1: 0.6558		
epoch: 009		acc: 0.7178		nmi: 0.4630		ari: 0.4793		f1: 0.6572		
epoch: 010		acc: 0.7148		nmi: 0.4587		ari: 0.4752		f1: 0.6547		
epoch: 011		acc: 0.7151		nmi: 0.4600		ari: 0.4766		f1: 0.6563		
epoch: 012		acc: 0.7157		nmi: 0.4623		ari: 0.4775		f1: 0.6577		
epoch: 013		acc: 0.7166		nmi: 0.4637		ari: 0.4799		f1: 0.6581		
epoch: 014		acc: 0.7172		nmi: 0.4639		ari: 0.4794		f1: 0.6594		
epoch: 015		acc: 0.7184		nmi: 0.4652		ari: 0.4818		f1: 0.6603		
epoch: 016		acc: 0.7157		nmi: 0.4605		ari: 0.4771		f1: 0.6574		
epoch: 017		acc: 0.7175		nmi: 0.4640		ari: 0.4810		f1: 0.6583		
epoch: 018		acc: 0.7148		nmi: 0.4606		ari: 0.4765		f1: 0.6562		
epoch: 019		acc: 0.7172		nmi: 0.4650		ari: 0.4808		f1: 0.6577		
epoch: 020		acc: 0.7184		nmi: 0.4653		ari: 0.4829		f1: 0.6587		
epoch: 021		acc: 0.7163		nmi: 0.4630		ari: 0.4793		f1: 0.6568		
epoch: 022		acc: 0.7154		nmi: 0.4614		ari: 0.4783		f1: 0.6565		
epoch: 023		acc: 0.7169		nmi: 0.4641		ari: 0.4807		f1: 0.6579		
epoch: 024		acc: 0.7157		nmi: 0.4617		ari: 0.4793		f1: 0.6570		
epoch: 025		acc: 0.7157		nmi: 0.4626		ari: 0.4795		f1: 0.6570		
epoch: 026		acc: 0.7169		nmi: 0.4644		ari: 0.4811		f1: 0.6591		
epoch: 027		acc: 0.7175		nmi: 0.4655		ari: 0.4821		f1: 0.6585		
epoch: 028		acc: 0.7163		nmi: 0.4646		ari: 0.4810		f1: 0.6576		
epoch: 029		acc: 0.7169		nmi: 0.4640		ari: 0.4815		f1: 0.6592		
epoch: 030		acc: 0.7172		nmi: 0.4640		ari: 0.4817		f1: 0.6600		
epoch: 031		acc: 0.7166		nmi: 0.4635		ari: 0.4810		f1: 0.6590		
epoch: 032		acc: 0.7172		nmi: 0.4641		ari: 0.4817		f1: 0.6600		
epoch: 033		acc: 0.7166		nmi: 0.4632		ari: 0.4810		f1: 0.6595		
epoch: 034		acc: 0.7172		nmi: 0.4642		ari: 0.4819		f1: 0.6601		
epoch: 035		acc: 0.7163		nmi: 0.4616		ari: 0.4796		f1: 0.6598		
epoch: 036		acc: 0.7160		nmi: 0.4617		ari: 0.4800		f1: 0.6591		
epoch: 037		acc: 0.7160		nmi: 0.4626		ari: 0.4804		f1: 0.6585		
epoch: 038		acc: 0.7148		nmi: 0.4611		ari: 0.4786		f1: 0.6574		
epoch: 039		acc: 0.7154		nmi: 0.4604		ari: 0.4788		f1: 0.6584		
epoch: 040		acc: 0.7166		nmi: 0.4627		ari: 0.4810		f1: 0.6595		
epoch: 041		acc: 0.7169		nmi: 0.4631		ari: 0.4809		f1: 0.6598		
epoch: 042		acc: 0.7154		nmi: 0.4614		ari: 0.4792		f1: 0.6579		
epoch: 043		acc: 0.7139		nmi: 0.4583		ari: 0.4768		f1: 0.6572		
epoch: 044		acc: 0.7163		nmi: 0.4622		ari: 0.4804		f1: 0.6593		
epoch: 045		acc: 0.7154		nmi: 0.4614		ari: 0.4794		f1: 0.6586		
epoch: 046		acc: 0.7163		nmi: 0.4624		ari: 0.4806		f1: 0.6588		
epoch: 047		acc: 0.7145		nmi: 0.4600		ari: 0.4778		f1: 0.6577		
epoch: 048		acc: 0.7151		nmi: 0.4604		ari: 0.4785		f1: 0.6583		
epoch: 049		acc: 0.7157		nmi: 0.4614		ari: 0.4794		f1: 0.6588		
epoch: 050		acc: 0.7151		nmi: 0.4604		ari: 0.4787		f1: 0.6583		
The total number of parameters is: 2.031712M(1e6).
The max memory allocated to model is: 799.76 MB.
Time consuming: 5.08s or 0.08m
****************************************Training loop No.8****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=3703, out_features=512, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.6817		nmi: 0.4156		ari: 0.4311		f1: 0.6377		
epoch: 002		acc: 0.6435		nmi: 0.3954		ari: 0.3490		f1: 0.5738		
epoch: 003		acc: 0.6880		nmi: 0.4331		ari: 0.4256		f1: 0.6285		
epoch: 004		acc: 0.7090		nmi: 0.4493		ari: 0.4679		f1: 0.6468		
epoch: 005		acc: 0.7115		nmi: 0.4554		ari: 0.4708		f1: 0.6522		
epoch: 006		acc: 0.7127		nmi: 0.4576		ari: 0.4732		f1: 0.6538		
epoch: 007		acc: 0.7142		nmi: 0.4595		ari: 0.4742		f1: 0.6545		
epoch: 008		acc: 0.7178		nmi: 0.4618		ari: 0.4804		f1: 0.6558		
epoch: 009		acc: 0.7172		nmi: 0.4614		ari: 0.4799		f1: 0.6536		
epoch: 010		acc: 0.7175		nmi: 0.4621		ari: 0.4811		f1: 0.6540		
epoch: 011		acc: 0.7169		nmi: 0.4611		ari: 0.4798		f1: 0.6548		
epoch: 012		acc: 0.7139		nmi: 0.4583		ari: 0.4750		f1: 0.6523		
epoch: 013		acc: 0.7181		nmi: 0.4632		ari: 0.4817		f1: 0.6571		
epoch: 014		acc: 0.7160		nmi: 0.4602		ari: 0.4794		f1: 0.6540		
epoch: 015		acc: 0.7172		nmi: 0.4624		ari: 0.4809		f1: 0.6551		
epoch: 016		acc: 0.7151		nmi: 0.4600		ari: 0.4776		f1: 0.6533		
epoch: 017		acc: 0.7163		nmi: 0.4621		ari: 0.4795		f1: 0.6538		
epoch: 018		acc: 0.7172		nmi: 0.4641		ari: 0.4809		f1: 0.6552		
epoch: 019		acc: 0.7187		nmi: 0.4661		ari: 0.4834		f1: 0.6567		
epoch: 020		acc: 0.7166		nmi: 0.4624		ari: 0.4800		f1: 0.6542		
epoch: 021		acc: 0.7175		nmi: 0.4634		ari: 0.4821		f1: 0.6550		
epoch: 022		acc: 0.7181		nmi: 0.4645		ari: 0.4828		f1: 0.6560		
epoch: 023		acc: 0.7178		nmi: 0.4646		ari: 0.4828		f1: 0.6560		
epoch: 024		acc: 0.7163		nmi: 0.4621		ari: 0.4800		f1: 0.6538		
epoch: 025		acc: 0.7172		nmi: 0.4630		ari: 0.4818		f1: 0.6553		
epoch: 026		acc: 0.7172		nmi: 0.4641		ari: 0.4823		f1: 0.6554		
epoch: 027		acc: 0.7184		nmi: 0.4650		ari: 0.4839		f1: 0.6564		
epoch: 028		acc: 0.7157		nmi: 0.4608		ari: 0.4794		f1: 0.6543		
epoch: 029		acc: 0.7166		nmi: 0.4633		ari: 0.4809		f1: 0.6549		
epoch: 030		acc: 0.7175		nmi: 0.4628		ari: 0.4825		f1: 0.6565		
epoch: 031		acc: 0.7169		nmi: 0.4624		ari: 0.4816		f1: 0.6553		
epoch: 032		acc: 0.7169		nmi: 0.4631		ari: 0.4818		f1: 0.6553		
epoch: 033		acc: 0.7175		nmi: 0.4639		ari: 0.4823		f1: 0.6564		
epoch: 034		acc: 0.7163		nmi: 0.4623		ari: 0.4816		f1: 0.6548		
epoch: 035		acc: 0.7163		nmi: 0.4617		ari: 0.4814		f1: 0.6542		
epoch: 036		acc: 0.7157		nmi: 0.4604		ari: 0.4799		f1: 0.6544		
epoch: 037		acc: 0.7175		nmi: 0.4636		ari: 0.4828		f1: 0.6570		
epoch: 038		acc: 0.7151		nmi: 0.4597		ari: 0.4796		f1: 0.6539		
epoch: 039		acc: 0.7157		nmi: 0.4609		ari: 0.4806		f1: 0.6544		
epoch: 040		acc: 0.7157		nmi: 0.4604		ari: 0.4802		f1: 0.6550		
epoch: 041		acc: 0.7154		nmi: 0.4609		ari: 0.4799		f1: 0.6548		
epoch: 042		acc: 0.7154		nmi: 0.4596		ari: 0.4796		f1: 0.6547		
epoch: 043		acc: 0.7163		nmi: 0.4619		ari: 0.4812		f1: 0.6555		
epoch: 044		acc: 0.7154		nmi: 0.4606		ari: 0.4797		f1: 0.6548		
epoch: 045		acc: 0.7154		nmi: 0.4595		ari: 0.4795		f1: 0.6548		
epoch: 046		acc: 0.7163		nmi: 0.4609		ari: 0.4811		f1: 0.6563		
epoch: 047		acc: 0.7151		nmi: 0.4591		ari: 0.4794		f1: 0.6546		
epoch: 048		acc: 0.7154		nmi: 0.4601		ari: 0.4795		f1: 0.6549		
epoch: 049		acc: 0.7148		nmi: 0.4581		ari: 0.4786		f1: 0.6550		
epoch: 050		acc: 0.7157		nmi: 0.4593		ari: 0.4799		f1: 0.6562		
The total number of parameters is: 2.031712M(1e6).
The max memory allocated to model is: 799.76 MB.
Time consuming: 5.09s or 0.08m
****************************************Training loop No.9****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=3703, out_features=512, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.6766		nmi: 0.4097		ari: 0.4214		f1: 0.6338		
epoch: 002		acc: 0.6372		nmi: 0.3900		ari: 0.3397		f1: 0.5682		
epoch: 003		acc: 0.6895		nmi: 0.4362		ari: 0.4302		f1: 0.6294		
epoch: 004		acc: 0.7072		nmi: 0.4493		ari: 0.4629		f1: 0.6480		
epoch: 005		acc: 0.7072		nmi: 0.4550		ari: 0.4645		f1: 0.6466		
epoch: 006		acc: 0.7106		nmi: 0.4579		ari: 0.4707		f1: 0.6515		
epoch: 007		acc: 0.7121		nmi: 0.4580		ari: 0.4708		f1: 0.6537		
epoch: 008		acc: 0.7151		nmi: 0.4616		ari: 0.4756		f1: 0.6549		
epoch: 009		acc: 0.7151		nmi: 0.4617		ari: 0.4753		f1: 0.6533		
epoch: 010		acc: 0.7142		nmi: 0.4597		ari: 0.4755		f1: 0.6513		
epoch: 011		acc: 0.7151		nmi: 0.4587		ari: 0.4759		f1: 0.6538		
epoch: 012		acc: 0.7136		nmi: 0.4589		ari: 0.4740		f1: 0.6527		
epoch: 013		acc: 0.7160		nmi: 0.4649		ari: 0.4793		f1: 0.6551		
epoch: 014		acc: 0.7133		nmi: 0.4595		ari: 0.4747		f1: 0.6531		
epoch: 015		acc: 0.7151		nmi: 0.4627		ari: 0.4778		f1: 0.6540		
epoch: 016		acc: 0.7145		nmi: 0.4611		ari: 0.4760		f1: 0.6541		
epoch: 017		acc: 0.7145		nmi: 0.4632		ari: 0.4770		f1: 0.6535		
epoch: 018		acc: 0.7148		nmi: 0.4629		ari: 0.4778		f1: 0.6527		
epoch: 019		acc: 0.7145		nmi: 0.4625		ari: 0.4775		f1: 0.6530		
epoch: 020		acc: 0.7145		nmi: 0.4633		ari: 0.4770		f1: 0.6533		
epoch: 021		acc: 0.7127		nmi: 0.4582		ari: 0.4729		f1: 0.6519		
epoch: 022		acc: 0.7142		nmi: 0.4625		ari: 0.4767		f1: 0.6529		
epoch: 023		acc: 0.7136		nmi: 0.4599		ari: 0.4759		f1: 0.6536		
epoch: 024		acc: 0.7145		nmi: 0.4630		ari: 0.4777		f1: 0.6545		
epoch: 025		acc: 0.7145		nmi: 0.4631		ari: 0.4780		f1: 0.6537		
epoch: 026		acc: 0.7136		nmi: 0.4612		ari: 0.4763		f1: 0.6538		
epoch: 027		acc: 0.7145		nmi: 0.4629		ari: 0.4778		f1: 0.6545		
epoch: 028		acc: 0.7133		nmi: 0.4601		ari: 0.4761		f1: 0.6542		
epoch: 029		acc: 0.7136		nmi: 0.4621		ari: 0.4769		f1: 0.6538		
epoch: 030		acc: 0.7130		nmi: 0.4607		ari: 0.4760		f1: 0.6527		
epoch: 031		acc: 0.7142		nmi: 0.4613		ari: 0.4774		f1: 0.6545		
epoch: 032		acc: 0.7127		nmi: 0.4598		ari: 0.4759		f1: 0.6526		
epoch: 033		acc: 0.7142		nmi: 0.4618		ari: 0.4780		f1: 0.6545		
epoch: 034		acc: 0.7148		nmi: 0.4621		ari: 0.4789		f1: 0.6551		
epoch: 035		acc: 0.7139		nmi: 0.4610		ari: 0.4777		f1: 0.6543		
epoch: 036		acc: 0.7133		nmi: 0.4599		ari: 0.4765		f1: 0.6538		
epoch: 037		acc: 0.7139		nmi: 0.4604		ari: 0.4771		f1: 0.6549		
epoch: 038		acc: 0.7151		nmi: 0.4628		ari: 0.4791		f1: 0.6561		
epoch: 039		acc: 0.7148		nmi: 0.4616		ari: 0.4785		f1: 0.6557		
epoch: 040		acc: 0.7139		nmi: 0.4598		ari: 0.4770		f1: 0.6551		
epoch: 041		acc: 0.7133		nmi: 0.4592		ari: 0.4767		f1: 0.6546		
epoch: 042		acc: 0.7136		nmi: 0.4599		ari: 0.4772		f1: 0.6548		
epoch: 043		acc: 0.7142		nmi: 0.4602		ari: 0.4776		f1: 0.6554		
epoch: 044		acc: 0.7145		nmi: 0.4603		ari: 0.4782		f1: 0.6556		
epoch: 045		acc: 0.7136		nmi: 0.4598		ari: 0.4770		f1: 0.6550		
epoch: 046		acc: 0.7124		nmi: 0.4584		ari: 0.4755		f1: 0.6540		
epoch: 047		acc: 0.7127		nmi: 0.4583		ari: 0.4759		f1: 0.6542		
epoch: 048		acc: 0.7124		nmi: 0.4581		ari: 0.4753		f1: 0.6540		
epoch: 049		acc: 0.7136		nmi: 0.4591		ari: 0.4767		f1: 0.6550		
epoch: 050		acc: 0.7124		nmi: 0.4572		ari: 0.4748		f1: 0.6544		
The total number of parameters is: 2.031712M(1e6).
The max memory allocated to model is: 799.76 MB.
Time consuming: 5.05s or 0.08m
****************************************Training loop No.10****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=3703, out_features=512, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.6736		nmi: 0.4055		ari: 0.4192		f1: 0.6282		
epoch: 002		acc: 0.6306		nmi: 0.3918		ari: 0.3292		f1: 0.5625		
epoch: 003		acc: 0.6946		nmi: 0.4398		ari: 0.4353		f1: 0.6364		
epoch: 004		acc: 0.7066		nmi: 0.4493		ari: 0.4639		f1: 0.6453		
epoch: 005		acc: 0.7124		nmi: 0.4596		ari: 0.4740		f1: 0.6514		
epoch: 006		acc: 0.7130		nmi: 0.4581		ari: 0.4734		f1: 0.6535		
epoch: 007		acc: 0.7148		nmi: 0.4590		ari: 0.4754		f1: 0.6550		
epoch: 008		acc: 0.7187		nmi: 0.4657		ari: 0.4828		f1: 0.6576		
epoch: 009		acc: 0.7175		nmi: 0.4632		ari: 0.4809		f1: 0.6561		
epoch: 010		acc: 0.7208		nmi: 0.4694		ari: 0.4863		f1: 0.6590		
epoch: 011		acc: 0.7232		nmi: 0.4722		ari: 0.4902		f1: 0.6623		
epoch: 012		acc: 0.7187		nmi: 0.4657		ari: 0.4824		f1: 0.6598		
epoch: 013		acc: 0.7172		nmi: 0.4644		ari: 0.4804		f1: 0.6575		
epoch: 014		acc: 0.7199		nmi: 0.4666		ari: 0.4846		f1: 0.6616		
epoch: 015		acc: 0.7175		nmi: 0.4649		ari: 0.4816		f1: 0.6584		
epoch: 016		acc: 0.7187		nmi: 0.4661		ari: 0.4826		f1: 0.6601		
epoch: 017		acc: 0.7178		nmi: 0.4643		ari: 0.4820		f1: 0.6595		
epoch: 018		acc: 0.7196		nmi: 0.4673		ari: 0.4850		f1: 0.6610		
epoch: 019		acc: 0.7157		nmi: 0.4620		ari: 0.4788		f1: 0.6585		
epoch: 020		acc: 0.7184		nmi: 0.4654		ari: 0.4823		f1: 0.6611		
epoch: 021		acc: 0.7178		nmi: 0.4637		ari: 0.4825		f1: 0.6595		
epoch: 022		acc: 0.7175		nmi: 0.4640		ari: 0.4818		f1: 0.6597		
epoch: 023		acc: 0.7181		nmi: 0.4630		ari: 0.4821		f1: 0.6610		
epoch: 024		acc: 0.7163		nmi: 0.4623		ari: 0.4797		f1: 0.6582		
epoch: 025		acc: 0.7169		nmi: 0.4637		ari: 0.4812		f1: 0.6594		
epoch: 026		acc: 0.7148		nmi: 0.4602		ari: 0.4782		f1: 0.6576		
epoch: 027		acc: 0.7157		nmi: 0.4608		ari: 0.4795		f1: 0.6588		
epoch: 028		acc: 0.7151		nmi: 0.4604		ari: 0.4785		f1: 0.6579		
epoch: 029		acc: 0.7166		nmi: 0.4623		ari: 0.4810		f1: 0.6598		
epoch: 030		acc: 0.7175		nmi: 0.4637		ari: 0.4826		f1: 0.6599		
epoch: 031		acc: 0.7166		nmi: 0.4615		ari: 0.4805		f1: 0.6598		
epoch: 032		acc: 0.7169		nmi: 0.4623		ari: 0.4812		f1: 0.6606		
epoch: 033		acc: 0.7157		nmi: 0.4607		ari: 0.4796		f1: 0.6590		
epoch: 034		acc: 0.7154		nmi: 0.4595		ari: 0.4794		f1: 0.6582		
epoch: 035		acc: 0.7163		nmi: 0.4610		ari: 0.4806		f1: 0.6601		
epoch: 036		acc: 0.7160		nmi: 0.4604		ari: 0.4801		f1: 0.6599		
epoch: 037		acc: 0.7145		nmi: 0.4592		ari: 0.4779		f1: 0.6581		
epoch: 038		acc: 0.7148		nmi: 0.4581		ari: 0.4785		f1: 0.6588		
epoch: 039		acc: 0.7151		nmi: 0.4602		ari: 0.4790		f1: 0.6586		
epoch: 040		acc: 0.7151		nmi: 0.4597		ari: 0.4792		f1: 0.6592		
epoch: 041		acc: 0.7148		nmi: 0.4592		ari: 0.4787		f1: 0.6590		
epoch: 042		acc: 0.7151		nmi: 0.4599		ari: 0.4794		f1: 0.6587		
epoch: 043		acc: 0.7148		nmi: 0.4597		ari: 0.4788		f1: 0.6584		
epoch: 044		acc: 0.7145		nmi: 0.4589		ari: 0.4785		f1: 0.6588		
epoch: 045		acc: 0.7148		nmi: 0.4583		ari: 0.4789		f1: 0.6591		
epoch: 046		acc: 0.7145		nmi: 0.4583		ari: 0.4782		f1: 0.6588		
epoch: 047		acc: 0.7142		nmi: 0.4581		ari: 0.4778		f1: 0.6585		
epoch: 048		acc: 0.7142		nmi: 0.4577		ari: 0.4776		f1: 0.6585		
epoch: 049		acc: 0.7136		nmi: 0.4569		ari: 0.4770		f1: 0.6580		
epoch: 050		acc: 0.7145		nmi: 0.4583		ari: 0.4783		f1: 0.6589		
The total number of parameters is: 2.031712M(1e6).
The max memory allocated to model is: 799.76 MB.
Time consuming: 5.1s or 0.08m
Namespace(is_pretrain=False, plot_clustering_tsne=False, plot_embedding_heatmap=False, adj_norm=False, adj_loop=True, adj_symmetric=True, desc='default', model_name='SYNC', dataset_name='cite', root=None, k=None, t=None, loops=10, feature_type='tensor', label_type='npy', adj_type='tensor', seed=325, epsilon=0.0, device='cuda', clusters=6, nodes=3327, lr=0.006, max_epoch=50, pretrain_lr=0.001, pretrain_epoch=30, input_dim=3703, log_save_path='./logs/SYNC/cite/', dataset_path='../data/', clustering_tsne_save_path='./img/clustering/SYNC/cite/', embedding_heatmap_save_path='./img/heatmap/SYNC/cite/', pretrain_save_path='./pretrain/pretrain_tigae/SYNC/cite/', hidden_dim=256, embedding_dim=16, linear_dim=512, beta=1)
Total loops: 10
****************************************Mean value:****************************************
acc: 0.7176±0.0022		nmi: 0.4636±0.0037		ari: 0.4809±0.0037		f1: 0.6571±0.0028
Training over! Punch out!
Loading cora dataset from local
****************************************Training loop No.1****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=1433, out_features=128, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.7319		nmi: 0.5277		ari: 0.4940		f1: 0.7199		
epoch: 002		acc: 0.3667		nmi: 0.1416		ari: 0.0208		f1: 0.2312		
epoch: 003		acc: 0.6968		nmi: 0.4880		ari: 0.4236		f1: 0.6935		
epoch: 004		acc: 0.7699		nmi: 0.5433		ari: 0.5574		f1: 0.7489		
epoch: 005		acc: 0.7688		nmi: 0.5516		ari: 0.5534		f1: 0.7557		
epoch: 006		acc: 0.7552		nmi: 0.5427		ari: 0.5205		f1: 0.7490		
epoch: 007		acc: 0.7507		nmi: 0.5357		ari: 0.5133		f1: 0.7426		
epoch: 008		acc: 0.7607		nmi: 0.5469		ari: 0.5328		f1: 0.7508		
epoch: 009		acc: 0.7736		nmi: 0.5653		ari: 0.5580		f1: 0.7621		
epoch: 010		acc: 0.7773		nmi: 0.5729		ari: 0.5625		f1: 0.7691		
epoch: 011		acc: 0.7770		nmi: 0.5744		ari: 0.5581		f1: 0.7693		
epoch: 012		acc: 0.7736		nmi: 0.5679		ari: 0.5529		f1: 0.7662		
epoch: 013		acc: 0.7670		nmi: 0.5584		ari: 0.5404		f1: 0.7586		
epoch: 014		acc: 0.7714		nmi: 0.5627		ari: 0.5473		f1: 0.7643		
epoch: 015		acc: 0.7736		nmi: 0.5661		ari: 0.5543		f1: 0.7651		
epoch: 016		acc: 0.7762		nmi: 0.5743		ari: 0.5585		f1: 0.7674		
epoch: 017		acc: 0.7810		nmi: 0.5812		ari: 0.5680		f1: 0.7719		
epoch: 018		acc: 0.7777		nmi: 0.5757		ari: 0.5621		f1: 0.7680		
epoch: 019		acc: 0.7729		nmi: 0.5687		ari: 0.5534		f1: 0.7641		
epoch: 020		acc: 0.7825		nmi: 0.5826		ari: 0.5702		f1: 0.7738		
epoch: 021		acc: 0.7762		nmi: 0.5735		ari: 0.5583		f1: 0.7670		
epoch: 022		acc: 0.7736		nmi: 0.5736		ari: 0.5521		f1: 0.7658		
epoch: 023		acc: 0.7722		nmi: 0.5678		ari: 0.5490		f1: 0.7644		
epoch: 024		acc: 0.7758		nmi: 0.5758		ari: 0.5577		f1: 0.7675		
epoch: 025		acc: 0.7751		nmi: 0.5751		ari: 0.5528		f1: 0.7695		
epoch: 026		acc: 0.7777		nmi: 0.5778		ari: 0.5581		f1: 0.7709		
epoch: 027		acc: 0.7755		nmi: 0.5732		ari: 0.5551		f1: 0.7677		
epoch: 028		acc: 0.7799		nmi: 0.5782		ari: 0.5658		f1: 0.7714		
epoch: 029		acc: 0.7851		nmi: 0.5855		ari: 0.5722		f1: 0.7782		
epoch: 030		acc: 0.7740		nmi: 0.5706		ari: 0.5536		f1: 0.7662		
epoch: 031		acc: 0.7770		nmi: 0.5790		ari: 0.5597		f1: 0.7683		
epoch: 032		acc: 0.7736		nmi: 0.5758		ari: 0.5533		f1: 0.7656		
epoch: 033		acc: 0.7740		nmi: 0.5729		ari: 0.5560		f1: 0.7654		
epoch: 034		acc: 0.7699		nmi: 0.5699		ari: 0.5490		f1: 0.7616		
epoch: 035		acc: 0.7696		nmi: 0.5671		ari: 0.5494		f1: 0.7604		
epoch: 036		acc: 0.7666		nmi: 0.5669		ari: 0.5436		f1: 0.7587		
epoch: 037		acc: 0.7699		nmi: 0.5736		ari: 0.5496		f1: 0.7613		
epoch: 038		acc: 0.7718		nmi: 0.5737		ari: 0.5532		f1: 0.7629		
epoch: 039		acc: 0.7681		nmi: 0.5680		ari: 0.5462		f1: 0.7593		
epoch: 040		acc: 0.7722		nmi: 0.5713		ari: 0.5555		f1: 0.7625		
epoch: 041		acc: 0.7696		nmi: 0.5707		ari: 0.5492		f1: 0.7607		
epoch: 042		acc: 0.7655		nmi: 0.5644		ari: 0.5443		f1: 0.7559		
epoch: 043		acc: 0.7699		nmi: 0.5679		ari: 0.5510		f1: 0.7609		
epoch: 044		acc: 0.7688		nmi: 0.5704		ari: 0.5480		f1: 0.7601		
epoch: 045		acc: 0.7710		nmi: 0.5745		ari: 0.5539		f1: 0.7622		
epoch: 046		acc: 0.7681		nmi: 0.5725		ari: 0.5498		f1: 0.7589		
epoch: 047		acc: 0.7659		nmi: 0.5671		ari: 0.5451		f1: 0.7562		
epoch: 048		acc: 0.7651		nmi: 0.5666		ari: 0.5455		f1: 0.7552		
epoch: 049		acc: 0.7685		nmi: 0.5760		ari: 0.5531		f1: 0.7581		
epoch: 050		acc: 0.7670		nmi: 0.5722		ari: 0.5485		f1: 0.7573		
The total number of parameters is: 0.220528M(1e6).
The max memory allocated to model is: 485.88 MB.
Time consuming: 6.06s or 0.1m
****************************************Training loop No.2****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=1433, out_features=128, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.7389		nmi: 0.5341		ari: 0.5075		f1: 0.7262		
epoch: 002		acc: 0.3748		nmi: 0.1613		ari: 0.0389		f1: 0.2387		
epoch: 003		acc: 0.6691		nmi: 0.4611		ari: 0.3826		f1: 0.6648		
epoch: 004		acc: 0.7891		nmi: 0.5739		ari: 0.5915		f1: 0.7761		
epoch: 005		acc: 0.7799		nmi: 0.5657		ari: 0.5710		f1: 0.7693		
epoch: 006		acc: 0.7578		nmi: 0.5449		ari: 0.5261		f1: 0.7490		
epoch: 007		acc: 0.7459		nmi: 0.5354		ari: 0.5052		f1: 0.7372		
epoch: 008		acc: 0.7703		nmi: 0.5629		ari: 0.5481		f1: 0.7619		
epoch: 009		acc: 0.7788		nmi: 0.5735		ari: 0.5686		f1: 0.7687		
epoch: 010		acc: 0.7784		nmi: 0.5769		ari: 0.5629		f1: 0.7718		
epoch: 011		acc: 0.7795		nmi: 0.5761		ari: 0.5624		f1: 0.7721		
epoch: 012		acc: 0.7733		nmi: 0.5686		ari: 0.5530		f1: 0.7647		
epoch: 013		acc: 0.7762		nmi: 0.5736		ari: 0.5583		f1: 0.7683		
epoch: 014		acc: 0.7729		nmi: 0.5685		ari: 0.5530		f1: 0.7648		
epoch: 015		acc: 0.7773		nmi: 0.5769		ari: 0.5637		f1: 0.7692		
epoch: 016		acc: 0.7758		nmi: 0.5746		ari: 0.5577		f1: 0.7681		
epoch: 017		acc: 0.7699		nmi: 0.5659		ari: 0.5477		f1: 0.7612		
epoch: 018		acc: 0.7707		nmi: 0.5678		ari: 0.5465		f1: 0.7630		
epoch: 019		acc: 0.7722		nmi: 0.5693		ari: 0.5489		f1: 0.7651		
epoch: 020		acc: 0.7729		nmi: 0.5726		ari: 0.5510		f1: 0.7646		
epoch: 021		acc: 0.7722		nmi: 0.5713		ari: 0.5485		f1: 0.7655		
epoch: 022		acc: 0.7762		nmi: 0.5732		ari: 0.5568		f1: 0.7674		
epoch: 023		acc: 0.7751		nmi: 0.5734		ari: 0.5570		f1: 0.7663		
epoch: 024		acc: 0.7788		nmi: 0.5799		ari: 0.5600		f1: 0.7730		
epoch: 025		acc: 0.7770		nmi: 0.5756		ari: 0.5579		f1: 0.7689		
epoch: 026		acc: 0.7832		nmi: 0.5845		ari: 0.5682		f1: 0.7760		
epoch: 027		acc: 0.7803		nmi: 0.5801		ari: 0.5703		f1: 0.7690		
epoch: 028		acc: 0.7829		nmi: 0.5835		ari: 0.5707		f1: 0.7739		
epoch: 029		acc: 0.7836		nmi: 0.5818		ari: 0.5726		f1: 0.7739		
epoch: 030		acc: 0.7818		nmi: 0.5793		ari: 0.5691		f1: 0.7731		
epoch: 031		acc: 0.7795		nmi: 0.5794		ari: 0.5631		f1: 0.7714		
epoch: 032		acc: 0.7799		nmi: 0.5834		ari: 0.5646		f1: 0.7715		
epoch: 033		acc: 0.7736		nmi: 0.5714		ari: 0.5519		f1: 0.7661		
epoch: 034		acc: 0.7777		nmi: 0.5797		ari: 0.5604		f1: 0.7699		
epoch: 035		acc: 0.7733		nmi: 0.5720		ari: 0.5527		f1: 0.7655		
epoch: 036		acc: 0.7722		nmi: 0.5715		ari: 0.5542		f1: 0.7621		
epoch: 037		acc: 0.7784		nmi: 0.5761		ari: 0.5615		f1: 0.7699		
epoch: 038		acc: 0.7806		nmi: 0.5828		ari: 0.5653		f1: 0.7727		
epoch: 039		acc: 0.7784		nmi: 0.5778		ari: 0.5629		f1: 0.7698		
epoch: 040		acc: 0.7832		nmi: 0.5816		ari: 0.5720		f1: 0.7743		
epoch: 041		acc: 0.7825		nmi: 0.5823		ari: 0.5680		f1: 0.7746		
epoch: 042		acc: 0.7810		nmi: 0.5823		ari: 0.5677		f1: 0.7726		
epoch: 043		acc: 0.7821		nmi: 0.5836		ari: 0.5716		f1: 0.7721		
epoch: 044		acc: 0.7755		nmi: 0.5736		ari: 0.5590		f1: 0.7664		
epoch: 045		acc: 0.7806		nmi: 0.5825		ari: 0.5686		f1: 0.7710		
epoch: 046		acc: 0.7770		nmi: 0.5771		ari: 0.5624		f1: 0.7679		
epoch: 047		acc: 0.7751		nmi: 0.5739		ari: 0.5599		f1: 0.7653		
epoch: 048		acc: 0.7729		nmi: 0.5715		ari: 0.5555		f1: 0.7635		
epoch: 049		acc: 0.7718		nmi: 0.5734		ari: 0.5500		f1: 0.7641		
epoch: 050		acc: 0.7762		nmi: 0.5745		ari: 0.5609		f1: 0.7669		
The total number of parameters is: 0.220528M(1e6).
The max memory allocated to model is: 487.92 MB.
Time consuming: 3.2s or 0.05m
****************************************Training loop No.3****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=1433, out_features=128, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.7360		nmi: 0.5285		ari: 0.5007		f1: 0.7240		
epoch: 002		acc: 0.3405		nmi: 0.0820		ari: 0.0130		f1: 0.1623		
epoch: 003		acc: 0.6747		nmi: 0.4599		ari: 0.3886		f1: 0.6690		
epoch: 004		acc: 0.7910		nmi: 0.5833		ari: 0.5913		f1: 0.7805		
epoch: 005		acc: 0.7847		nmi: 0.5733		ari: 0.5843		f1: 0.7719		
epoch: 006		acc: 0.7681		nmi: 0.5535		ari: 0.5457		f1: 0.7594		
epoch: 007		acc: 0.7603		nmi: 0.5501		ari: 0.5306		f1: 0.7514		
epoch: 008		acc: 0.7773		nmi: 0.5714		ari: 0.5629		f1: 0.7679		
epoch: 009		acc: 0.7862		nmi: 0.5830		ari: 0.5803		f1: 0.7765		
epoch: 010		acc: 0.7821		nmi: 0.5795		ari: 0.5694		f1: 0.7737		
epoch: 011		acc: 0.7784		nmi: 0.5710		ari: 0.5665		f1: 0.7675		
epoch: 012		acc: 0.7770		nmi: 0.5725		ari: 0.5631		f1: 0.7658		
epoch: 013		acc: 0.7792		nmi: 0.5743		ari: 0.5664		f1: 0.7680		
epoch: 014		acc: 0.7862		nmi: 0.5848		ari: 0.5792		f1: 0.7755		
epoch: 015		acc: 0.7814		nmi: 0.5828		ari: 0.5689		f1: 0.7732		
epoch: 016		acc: 0.7851		nmi: 0.5844		ari: 0.5768		f1: 0.7753		
epoch: 017		acc: 0.7766		nmi: 0.5715		ari: 0.5621		f1: 0.7654		
epoch: 018		acc: 0.7840		nmi: 0.5847		ari: 0.5737		f1: 0.7738		
epoch: 019		acc: 0.7810		nmi: 0.5797		ari: 0.5689		f1: 0.7716		
epoch: 020		acc: 0.7740		nmi: 0.5696		ari: 0.5522		f1: 0.7663		
epoch: 021		acc: 0.7744		nmi: 0.5694		ari: 0.5540		f1: 0.7657		
epoch: 022		acc: 0.7722		nmi: 0.5682		ari: 0.5498		f1: 0.7645		
epoch: 023		acc: 0.7795		nmi: 0.5797		ari: 0.5660		f1: 0.7704		
epoch: 024		acc: 0.7814		nmi: 0.5840		ari: 0.5646		f1: 0.7746		
epoch: 025		acc: 0.7810		nmi: 0.5830		ari: 0.5667		f1: 0.7714		
epoch: 026		acc: 0.7880		nmi: 0.5879		ari: 0.5811		f1: 0.7780		
epoch: 027		acc: 0.7814		nmi: 0.5775		ari: 0.5680		f1: 0.7728		
epoch: 028		acc: 0.7821		nmi: 0.5782		ari: 0.5692		f1: 0.7741		
epoch: 029		acc: 0.7840		nmi: 0.5832		ari: 0.5679		f1: 0.7776		
epoch: 030		acc: 0.7758		nmi: 0.5742		ari: 0.5554		f1: 0.7687		
epoch: 031		acc: 0.7770		nmi: 0.5801		ari: 0.5578		f1: 0.7694		
epoch: 032		acc: 0.7747		nmi: 0.5710		ari: 0.5545		f1: 0.7660		
epoch: 033		acc: 0.7832		nmi: 0.5859		ari: 0.5687		f1: 0.7754		
epoch: 034		acc: 0.7725		nmi: 0.5707		ari: 0.5504		f1: 0.7650		
epoch: 035		acc: 0.7814		nmi: 0.5808		ari: 0.5656		f1: 0.7727		
epoch: 036		acc: 0.7762		nmi: 0.5730		ari: 0.5588		f1: 0.7668		
epoch: 037		acc: 0.7766		nmi: 0.5772		ari: 0.5585		f1: 0.7688		
epoch: 038		acc: 0.7766		nmi: 0.5746		ari: 0.5589		f1: 0.7682		
epoch: 039		acc: 0.7773		nmi: 0.5755		ari: 0.5580		f1: 0.7687		
epoch: 040		acc: 0.7762		nmi: 0.5765		ari: 0.5619		f1: 0.7659		
epoch: 041		acc: 0.7792		nmi: 0.5821		ari: 0.5643		f1: 0.7714		
epoch: 042		acc: 0.7773		nmi: 0.5752		ari: 0.5622		f1: 0.7679		
epoch: 043		acc: 0.7744		nmi: 0.5716		ari: 0.5554		f1: 0.7665		
epoch: 044		acc: 0.7747		nmi: 0.5717		ari: 0.5563		f1: 0.7653		
epoch: 045		acc: 0.7740		nmi: 0.5707		ari: 0.5561		f1: 0.7647		
epoch: 046		acc: 0.7685		nmi: 0.5643		ari: 0.5484		f1: 0.7580		
epoch: 047		acc: 0.7703		nmi: 0.5665		ari: 0.5512		f1: 0.7606		
epoch: 048		acc: 0.7699		nmi: 0.5653		ari: 0.5481		f1: 0.7609		
epoch: 049		acc: 0.7696		nmi: 0.5657		ari: 0.5490		f1: 0.7604		
epoch: 050		acc: 0.7703		nmi: 0.5686		ari: 0.5497		f1: 0.7610		
The total number of parameters is: 0.220528M(1e6).
The max memory allocated to model is: 487.92 MB.
Time consuming: 3.07s or 0.05m
****************************************Training loop No.4****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=1433, out_features=128, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.7319		nmi: 0.5238		ari: 0.4943		f1: 0.7198		
epoch: 002		acc: 0.3744		nmi: 0.1741		ari: 0.0325		f1: 0.2565		
epoch: 003		acc: 0.6824		nmi: 0.4763		ari: 0.4042		f1: 0.6791		
epoch: 004		acc: 0.7722		nmi: 0.5552		ari: 0.5552		f1: 0.7632		
epoch: 005		acc: 0.7725		nmi: 0.5572		ari: 0.5620		f1: 0.7557		
epoch: 006		acc: 0.7703		nmi: 0.5595		ari: 0.5503		f1: 0.7612		
epoch: 007		acc: 0.7541		nmi: 0.5412		ari: 0.5210		f1: 0.7445		
epoch: 008		acc: 0.7710		nmi: 0.5671		ari: 0.5480		f1: 0.7634		
epoch: 009		acc: 0.7755		nmi: 0.5711		ari: 0.5605		f1: 0.7656		
epoch: 010		acc: 0.7773		nmi: 0.5697		ari: 0.5657		f1: 0.7659		
epoch: 011		acc: 0.7773		nmi: 0.5703		ari: 0.5599		f1: 0.7691		
epoch: 012		acc: 0.7655		nmi: 0.5588		ari: 0.5378		f1: 0.7588		
epoch: 013		acc: 0.7722		nmi: 0.5663		ari: 0.5508		f1: 0.7639		
epoch: 014		acc: 0.7699		nmi: 0.5663		ari: 0.5448		f1: 0.7640		
epoch: 015		acc: 0.7733		nmi: 0.5678		ari: 0.5517		f1: 0.7658		
epoch: 016		acc: 0.7770		nmi: 0.5741		ari: 0.5586		f1: 0.7698		
epoch: 017		acc: 0.7740		nmi: 0.5729		ari: 0.5546		f1: 0.7653		
epoch: 018		acc: 0.7744		nmi: 0.5737		ari: 0.5550		f1: 0.7666		
epoch: 019		acc: 0.7696		nmi: 0.5677		ari: 0.5428		f1: 0.7635		
epoch: 020		acc: 0.7696		nmi: 0.5668		ari: 0.5441		f1: 0.7634		
epoch: 021		acc: 0.7662		nmi: 0.5643		ari: 0.5348		f1: 0.7611		
epoch: 022		acc: 0.7707		nmi: 0.5708		ari: 0.5449		f1: 0.7649		
epoch: 023		acc: 0.7784		nmi: 0.5795		ari: 0.5585		f1: 0.7714		
epoch: 024		acc: 0.7795		nmi: 0.5777		ari: 0.5633		f1: 0.7722		
epoch: 025		acc: 0.7784		nmi: 0.5758		ari: 0.5617		f1: 0.7710		
epoch: 026		acc: 0.7781		nmi: 0.5756		ari: 0.5598		f1: 0.7701		
epoch: 027		acc: 0.7784		nmi: 0.5753		ari: 0.5606		f1: 0.7707		
epoch: 028		acc: 0.7821		nmi: 0.5853		ari: 0.5638		f1: 0.7766		
epoch: 029		acc: 0.7762		nmi: 0.5763		ari: 0.5571		f1: 0.7682		
epoch: 030		acc: 0.7788		nmi: 0.5794		ari: 0.5624		f1: 0.7701		
epoch: 031		acc: 0.7814		nmi: 0.5831		ari: 0.5652		f1: 0.7749		
epoch: 032		acc: 0.7777		nmi: 0.5823		ari: 0.5575		f1: 0.7704		
epoch: 033		acc: 0.7755		nmi: 0.5770		ari: 0.5556		f1: 0.7670		
epoch: 034		acc: 0.7718		nmi: 0.5703		ari: 0.5478		f1: 0.7641		
epoch: 035		acc: 0.7758		nmi: 0.5787		ari: 0.5548		f1: 0.7688		
epoch: 036		acc: 0.7685		nmi: 0.5665		ari: 0.5431		f1: 0.7605		
epoch: 037		acc: 0.7762		nmi: 0.5781		ari: 0.5554		f1: 0.7690		
epoch: 038		acc: 0.7688		nmi: 0.5674		ari: 0.5461		f1: 0.7600		
epoch: 039		acc: 0.7722		nmi: 0.5713		ari: 0.5521		f1: 0.7628		
epoch: 040		acc: 0.7762		nmi: 0.5788		ari: 0.5625		f1: 0.7661		
epoch: 041		acc: 0.7758		nmi: 0.5812		ari: 0.5566		f1: 0.7683		
epoch: 042		acc: 0.7751		nmi: 0.5756		ari: 0.5567		f1: 0.7663		
epoch: 043		acc: 0.7766		nmi: 0.5819		ari: 0.5571		f1: 0.7685		
epoch: 044		acc: 0.7718		nmi: 0.5740		ari: 0.5507		f1: 0.7637		
epoch: 045		acc: 0.7714		nmi: 0.5666		ari: 0.5483		f1: 0.7634		
epoch: 046		acc: 0.7781		nmi: 0.5812		ari: 0.5614		f1: 0.7694		
epoch: 047		acc: 0.7736		nmi: 0.5729		ari: 0.5524		f1: 0.7664		
epoch: 048		acc: 0.7747		nmi: 0.5758		ari: 0.5542		f1: 0.7665		
epoch: 049		acc: 0.7677		nmi: 0.5671		ari: 0.5437		f1: 0.7592		
epoch: 050		acc: 0.7655		nmi: 0.5644		ari: 0.5399		f1: 0.7577		
The total number of parameters is: 0.220528M(1e6).
The max memory allocated to model is: 487.92 MB.
Time consuming: 3.11s or 0.05m
****************************************Training loop No.5****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=1433, out_features=128, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.7345		nmi: 0.5277		ari: 0.4975		f1: 0.7231		
epoch: 002		acc: 0.3863		nmi: 0.2036		ari: 0.0544		f1: 0.2682		
epoch: 003		acc: 0.6795		nmi: 0.4758		ari: 0.3960		f1: 0.6763		
epoch: 004		acc: 0.7662		nmi: 0.5453		ari: 0.5544		f1: 0.7502		
epoch: 005		acc: 0.7847		nmi: 0.5762		ari: 0.5778		f1: 0.7765		
epoch: 006		acc: 0.7566		nmi: 0.5481		ari: 0.5272		f1: 0.7494		
epoch: 007		acc: 0.7415		nmi: 0.5278		ari: 0.4987		f1: 0.7349		
epoch: 008		acc: 0.7559		nmi: 0.5450		ari: 0.5213		f1: 0.7487		
epoch: 009		acc: 0.7666		nmi: 0.5579		ari: 0.5475		f1: 0.7566		
epoch: 010		acc: 0.7825		nmi: 0.5785		ari: 0.5724		f1: 0.7751		
epoch: 011		acc: 0.7792		nmi: 0.5746		ari: 0.5672		f1: 0.7712		
epoch: 012		acc: 0.7692		nmi: 0.5648		ari: 0.5445		f1: 0.7633		
epoch: 013		acc: 0.7710		nmi: 0.5728		ari: 0.5492		f1: 0.7652		
epoch: 014		acc: 0.7714		nmi: 0.5669		ari: 0.5498		f1: 0.7650		
epoch: 015		acc: 0.7777		nmi: 0.5750		ari: 0.5619		f1: 0.7701		
epoch: 016		acc: 0.7758		nmi: 0.5731		ari: 0.5558		f1: 0.7692		
epoch: 017		acc: 0.7725		nmi: 0.5671		ari: 0.5511		f1: 0.7656		
epoch: 018		acc: 0.7696		nmi: 0.5636		ari: 0.5443		f1: 0.7633		
epoch: 019		acc: 0.7758		nmi: 0.5743		ari: 0.5600		f1: 0.7670		
epoch: 020		acc: 0.7729		nmi: 0.5709		ari: 0.5520		f1: 0.7651		
epoch: 021		acc: 0.7692		nmi: 0.5640		ari: 0.5434		f1: 0.7632		
epoch: 022		acc: 0.7688		nmi: 0.5642		ari: 0.5461		f1: 0.7618		
epoch: 023		acc: 0.7755		nmi: 0.5713		ari: 0.5569		f1: 0.7666		
epoch: 024		acc: 0.7733		nmi: 0.5688		ari: 0.5532		f1: 0.7658		
epoch: 025		acc: 0.7758		nmi: 0.5739		ari: 0.5558		f1: 0.7701		
epoch: 026		acc: 0.7718		nmi: 0.5696		ari: 0.5492		f1: 0.7660		
epoch: 027		acc: 0.7788		nmi: 0.5807		ari: 0.5628		f1: 0.7721		
epoch: 028		acc: 0.7773		nmi: 0.5769		ari: 0.5590		f1: 0.7722		
epoch: 029		acc: 0.7714		nmi: 0.5693		ari: 0.5535		f1: 0.7634		
epoch: 030		acc: 0.7755		nmi: 0.5722		ari: 0.5581		f1: 0.7670		
epoch: 031		acc: 0.7736		nmi: 0.5709		ari: 0.5565		f1: 0.7656		
epoch: 032		acc: 0.7692		nmi: 0.5667		ari: 0.5500		f1: 0.7603		
epoch: 033		acc: 0.7692		nmi: 0.5648		ari: 0.5503		f1: 0.7602		
epoch: 034		acc: 0.7670		nmi: 0.5625		ari: 0.5473		f1: 0.7579		
epoch: 035		acc: 0.7651		nmi: 0.5639		ari: 0.5445		f1: 0.7560		
epoch: 036		acc: 0.7692		nmi: 0.5698		ari: 0.5505		f1: 0.7606		
epoch: 037		acc: 0.7651		nmi: 0.5659		ari: 0.5430		f1: 0.7564		
epoch: 038		acc: 0.7633		nmi: 0.5620		ari: 0.5432		f1: 0.7530		
epoch: 039		acc: 0.7659		nmi: 0.5642		ari: 0.5445		f1: 0.7568		
epoch: 040		acc: 0.7637		nmi: 0.5637		ari: 0.5426		f1: 0.7546		
epoch: 041		acc: 0.7677		nmi: 0.5670		ari: 0.5537		f1: 0.7567		
epoch: 042		acc: 0.7688		nmi: 0.5691		ari: 0.5505		f1: 0.7600		
epoch: 043		acc: 0.7648		nmi: 0.5593		ari: 0.5463		f1: 0.7537		
epoch: 044		acc: 0.7670		nmi: 0.5647		ari: 0.5497		f1: 0.7565		
epoch: 045		acc: 0.7622		nmi: 0.5605		ari: 0.5434		f1: 0.7511		
epoch: 046		acc: 0.7666		nmi: 0.5668		ari: 0.5515		f1: 0.7559		
epoch: 047		acc: 0.7633		nmi: 0.5621		ari: 0.5434		f1: 0.7541		
epoch: 048		acc: 0.7662		nmi: 0.5662		ari: 0.5508		f1: 0.7552		
epoch: 049		acc: 0.7592		nmi: 0.5622		ari: 0.5361		f1: 0.7502		
epoch: 050		acc: 0.7640		nmi: 0.5673		ari: 0.5451		f1: 0.7541		
The total number of parameters is: 0.220528M(1e6).
The max memory allocated to model is: 487.92 MB.
Time consuming: 3.1s or 0.05m
****************************************Training loop No.6****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=1433, out_features=128, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.7341		nmi: 0.5283		ari: 0.4976		f1: 0.7222		
epoch: 002		acc: 0.3652		nmi: 0.1661		ari: 0.0210		f1: 0.2456		
epoch: 003		acc: 0.7072		nmi: 0.5013		ari: 0.4412		f1: 0.7000		
epoch: 004		acc: 0.7555		nmi: 0.5318		ari: 0.5285		f1: 0.7402		
epoch: 005		acc: 0.7733		nmi: 0.5646		ari: 0.5638		f1: 0.7570		
epoch: 006		acc: 0.7530		nmi: 0.5409		ari: 0.5198		f1: 0.7434		
epoch: 007		acc: 0.7470		nmi: 0.5330		ari: 0.5066		f1: 0.7380		
epoch: 008		acc: 0.7637		nmi: 0.5476		ari: 0.5367		f1: 0.7547		
epoch: 009		acc: 0.7773		nmi: 0.5639		ari: 0.5630		f1: 0.7669		
epoch: 010		acc: 0.7722		nmi: 0.5603		ari: 0.5549		f1: 0.7619		
epoch: 011		acc: 0.7755		nmi: 0.5738		ari: 0.5532		f1: 0.7689		
epoch: 012		acc: 0.7666		nmi: 0.5642		ari: 0.5362		f1: 0.7611		
epoch: 013		acc: 0.7733		nmi: 0.5706		ari: 0.5476		f1: 0.7672		
epoch: 014		acc: 0.7703		nmi: 0.5640		ari: 0.5422		f1: 0.7659		
epoch: 015		acc: 0.7788		nmi: 0.5761		ari: 0.5624		f1: 0.7718		
epoch: 016		acc: 0.7781		nmi: 0.5751		ari: 0.5586		f1: 0.7730		
epoch: 017		acc: 0.7755		nmi: 0.5695		ari: 0.5567		f1: 0.7674		
epoch: 018		acc: 0.7740		nmi: 0.5695		ari: 0.5506		f1: 0.7676		
epoch: 019		acc: 0.7740		nmi: 0.5721		ari: 0.5510		f1: 0.7678		
epoch: 020		acc: 0.7703		nmi: 0.5636		ari: 0.5426		f1: 0.7643		
epoch: 021		acc: 0.7677		nmi: 0.5653		ari: 0.5371		f1: 0.7629		
epoch: 022		acc: 0.7725		nmi: 0.5695		ari: 0.5508		f1: 0.7648		
epoch: 023		acc: 0.7766		nmi: 0.5765		ari: 0.5570		f1: 0.7691		
epoch: 024		acc: 0.7773		nmi: 0.5725		ari: 0.5594		f1: 0.7690		
epoch: 025		acc: 0.7792		nmi: 0.5753		ari: 0.5613		f1: 0.7718		
epoch: 026		acc: 0.7781		nmi: 0.5764		ari: 0.5644		f1: 0.7682		
epoch: 027		acc: 0.7799		nmi: 0.5765		ari: 0.5666		f1: 0.7707		
epoch: 028		acc: 0.7855		nmi: 0.5832		ari: 0.5726		f1: 0.7787		
epoch: 029		acc: 0.7810		nmi: 0.5774		ari: 0.5649		f1: 0.7731		
epoch: 030		acc: 0.7836		nmi: 0.5828		ari: 0.5702		f1: 0.7759		
epoch: 031		acc: 0.7818		nmi: 0.5776		ari: 0.5669		f1: 0.7736		
epoch: 032		acc: 0.7814		nmi: 0.5777		ari: 0.5690		f1: 0.7722		
epoch: 033		acc: 0.7818		nmi: 0.5788		ari: 0.5675		f1: 0.7732		
epoch: 034		acc: 0.7736		nmi: 0.5681		ari: 0.5556		f1: 0.7649		
epoch: 035		acc: 0.7747		nmi: 0.5703		ari: 0.5588		f1: 0.7655		
epoch: 036		acc: 0.7740		nmi: 0.5689		ari: 0.5551		f1: 0.7657		
epoch: 037		acc: 0.7710		nmi: 0.5687		ari: 0.5517		f1: 0.7620		
epoch: 038		acc: 0.7688		nmi: 0.5649		ari: 0.5474		f1: 0.7600		
epoch: 039		acc: 0.7699		nmi: 0.5676		ari: 0.5518		f1: 0.7600		
epoch: 040		acc: 0.7718		nmi: 0.5687		ari: 0.5561		f1: 0.7612		
epoch: 041		acc: 0.7744		nmi: 0.5703		ari: 0.5601		f1: 0.7645		
epoch: 042		acc: 0.7751		nmi: 0.5746		ari: 0.5611		f1: 0.7651		
epoch: 043		acc: 0.7670		nmi: 0.5644		ari: 0.5483		f1: 0.7571		
epoch: 044		acc: 0.7733		nmi: 0.5700		ari: 0.5561		f1: 0.7636		
epoch: 045		acc: 0.7707		nmi: 0.5718		ari: 0.5554		f1: 0.7606		
epoch: 046		acc: 0.7710		nmi: 0.5709		ari: 0.5534		f1: 0.7614		
epoch: 047		acc: 0.7729		nmi: 0.5709		ari: 0.5566		f1: 0.7638		
epoch: 048		acc: 0.7699		nmi: 0.5655		ari: 0.5528		f1: 0.7600		
epoch: 049		acc: 0.7714		nmi: 0.5688		ari: 0.5545		f1: 0.7624		
epoch: 050		acc: 0.7747		nmi: 0.5747		ari: 0.5601		f1: 0.7650		
The total number of parameters is: 0.220528M(1e6).
The max memory allocated to model is: 487.92 MB.
Time consuming: 3.11s or 0.05m
****************************************Training loop No.7****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=1433, out_features=128, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.7334		nmi: 0.5270		ari: 0.4960		f1: 0.7220		
epoch: 002		acc: 0.3246		nmi: 0.0485		ari: 0.0049		f1: 0.1150		
epoch: 003		acc: 0.7013		nmi: 0.4894		ari: 0.4354		f1: 0.6926		
epoch: 004		acc: 0.7699		nmi: 0.5482		ari: 0.5570		f1: 0.7540		
epoch: 005		acc: 0.7755		nmi: 0.5673		ari: 0.5681		f1: 0.7596		
epoch: 006		acc: 0.7596		nmi: 0.5514		ari: 0.5344		f1: 0.7498		
epoch: 007		acc: 0.7555		nmi: 0.5469		ari: 0.5213		f1: 0.7471		
epoch: 008		acc: 0.7666		nmi: 0.5552		ari: 0.5446		f1: 0.7559		
epoch: 009		acc: 0.7777		nmi: 0.5715		ari: 0.5634		f1: 0.7689		
epoch: 010		acc: 0.7751		nmi: 0.5650		ari: 0.5584		f1: 0.7652		
epoch: 011		acc: 0.7725		nmi: 0.5693		ari: 0.5516		f1: 0.7648		
epoch: 012		acc: 0.7733		nmi: 0.5721		ari: 0.5542		f1: 0.7642		
epoch: 013		acc: 0.7710		nmi: 0.5627		ari: 0.5525		f1: 0.7617		
epoch: 014		acc: 0.7744		nmi: 0.5670		ari: 0.5607		f1: 0.7632		
epoch: 015		acc: 0.7777		nmi: 0.5750		ari: 0.5677		f1: 0.7666		
epoch: 016		acc: 0.7818		nmi: 0.5785		ari: 0.5735		f1: 0.7714		
epoch: 017		acc: 0.7803		nmi: 0.5818		ari: 0.5683		f1: 0.7720		
epoch: 018		acc: 0.7718		nmi: 0.5702		ari: 0.5497		f1: 0.7643		
epoch: 019		acc: 0.7685		nmi: 0.5664		ari: 0.5462		f1: 0.7606		
epoch: 020		acc: 0.7677		nmi: 0.5633		ari: 0.5415		f1: 0.7605		
epoch: 021		acc: 0.7707		nmi: 0.5679		ari: 0.5465		f1: 0.7640		
epoch: 022		acc: 0.7755		nmi: 0.5732		ari: 0.5605		f1: 0.7671		
epoch: 023		acc: 0.7773		nmi: 0.5736		ari: 0.5626		f1: 0.7680		
epoch: 024		acc: 0.7814		nmi: 0.5821		ari: 0.5684		f1: 0.7743		
epoch: 025		acc: 0.7810		nmi: 0.5787		ari: 0.5688		f1: 0.7731		
epoch: 026		acc: 0.7799		nmi: 0.5806		ari: 0.5630		f1: 0.7739		
epoch: 027		acc: 0.7821		nmi: 0.5848		ari: 0.5718		f1: 0.7734		
epoch: 028		acc: 0.7773		nmi: 0.5744		ari: 0.5614		f1: 0.7694		
epoch: 029		acc: 0.7821		nmi: 0.5808		ari: 0.5712		f1: 0.7734		
epoch: 030		acc: 0.7832		nmi: 0.5858		ari: 0.5723		f1: 0.7740		
epoch: 031		acc: 0.7777		nmi: 0.5771		ari: 0.5599		f1: 0.7698		
epoch: 032		acc: 0.7762		nmi: 0.5756		ari: 0.5600		f1: 0.7678		
epoch: 033		acc: 0.7803		nmi: 0.5809		ari: 0.5668		f1: 0.7699		
epoch: 034		acc: 0.7736		nmi: 0.5712		ari: 0.5533		f1: 0.7650		
epoch: 035		acc: 0.7733		nmi: 0.5716		ari: 0.5529		f1: 0.7644		
epoch: 036		acc: 0.7806		nmi: 0.5811		ari: 0.5681		f1: 0.7705		
epoch: 037		acc: 0.7777		nmi: 0.5763		ari: 0.5593		f1: 0.7697		
epoch: 038		acc: 0.7784		nmi: 0.5803		ari: 0.5646		f1: 0.7681		
epoch: 039		acc: 0.7733		nmi: 0.5702		ari: 0.5540		f1: 0.7638		
epoch: 040		acc: 0.7803		nmi: 0.5818		ari: 0.5667		f1: 0.7706		
epoch: 041		acc: 0.7818		nmi: 0.5850		ari: 0.5691		f1: 0.7724		
epoch: 042		acc: 0.7777		nmi: 0.5771		ari: 0.5648		f1: 0.7675		
epoch: 043		acc: 0.7744		nmi: 0.5729		ari: 0.5598		f1: 0.7637		
epoch: 044		acc: 0.7784		nmi: 0.5767		ari: 0.5648		f1: 0.7684		
epoch: 045		acc: 0.7799		nmi: 0.5741		ari: 0.5677		f1: 0.7691		
epoch: 046		acc: 0.7795		nmi: 0.5817		ari: 0.5664		f1: 0.7704		
epoch: 047		acc: 0.7762		nmi: 0.5740		ari: 0.5591		f1: 0.7668		
epoch: 048		acc: 0.7710		nmi: 0.5676		ari: 0.5522		f1: 0.7603		
epoch: 049		acc: 0.7722		nmi: 0.5690		ari: 0.5520		f1: 0.7630		
epoch: 050		acc: 0.7762		nmi: 0.5718		ari: 0.5637		f1: 0.7644		
The total number of parameters is: 0.220528M(1e6).
The max memory allocated to model is: 487.92 MB.
Time consuming: 3.08s or 0.05m
****************************************Training loop No.8****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=1433, out_features=128, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.7315		nmi: 0.5262		ari: 0.4929		f1: 0.7203		
epoch: 002		acc: 0.3667		nmi: 0.2244		ari: 0.0602		f1: 0.3071		
epoch: 003		acc: 0.6795		nmi: 0.4737		ari: 0.3999		f1: 0.6771		
epoch: 004		acc: 0.7648		nmi: 0.5501		ari: 0.5430		f1: 0.7549		
epoch: 005		acc: 0.7932		nmi: 0.5850		ari: 0.5961		f1: 0.7824		
epoch: 006		acc: 0.7666		nmi: 0.5541		ari: 0.5545		f1: 0.7556		
epoch: 007		acc: 0.7496		nmi: 0.5387		ari: 0.5130		f1: 0.7412		
epoch: 008		acc: 0.7496		nmi: 0.5403		ari: 0.5138		f1: 0.7408		
epoch: 009		acc: 0.7692		nmi: 0.5604		ari: 0.5532		f1: 0.7571		
epoch: 010		acc: 0.7766		nmi: 0.5660		ari: 0.5685		f1: 0.7643		
epoch: 011		acc: 0.7733		nmi: 0.5612		ari: 0.5613		f1: 0.7624		
epoch: 012		acc: 0.7699		nmi: 0.5569		ari: 0.5510		f1: 0.7597		
epoch: 013		acc: 0.7714		nmi: 0.5653		ari: 0.5506		f1: 0.7625		
epoch: 014		acc: 0.7622		nmi: 0.5506		ari: 0.5332		f1: 0.7555		
epoch: 015		acc: 0.7710		nmi: 0.5606		ari: 0.5506		f1: 0.7619		
epoch: 016		acc: 0.7710		nmi: 0.5610		ari: 0.5514		f1: 0.7615		
epoch: 017		acc: 0.7703		nmi: 0.5596		ari: 0.5509		f1: 0.7599		
epoch: 018		acc: 0.7618		nmi: 0.5481		ari: 0.5377		f1: 0.7510		
epoch: 019		acc: 0.7696		nmi: 0.5612		ari: 0.5498		f1: 0.7596		
epoch: 020		acc: 0.7677		nmi: 0.5589		ari: 0.5463		f1: 0.7573		
epoch: 021		acc: 0.7648		nmi: 0.5547		ari: 0.5415		f1: 0.7551		
epoch: 022		acc: 0.7703		nmi: 0.5612		ari: 0.5499		f1: 0.7602		
epoch: 023		acc: 0.7681		nmi: 0.5617		ari: 0.5468		f1: 0.7590		
epoch: 024		acc: 0.7740		nmi: 0.5716		ari: 0.5556		f1: 0.7660		
epoch: 025		acc: 0.7651		nmi: 0.5560		ari: 0.5410		f1: 0.7562		
epoch: 026		acc: 0.7651		nmi: 0.5568		ari: 0.5418		f1: 0.7570		
epoch: 027		acc: 0.7644		nmi: 0.5610		ari: 0.5445		f1: 0.7555		
epoch: 028		acc: 0.7659		nmi: 0.5621		ari: 0.5450		f1: 0.7574		
epoch: 029		acc: 0.7699		nmi: 0.5660		ari: 0.5534		f1: 0.7594		
epoch: 030		acc: 0.7607		nmi: 0.5577		ari: 0.5372		f1: 0.7511		
epoch: 031		acc: 0.7655		nmi: 0.5657		ari: 0.5494		f1: 0.7549		
epoch: 032		acc: 0.7611		nmi: 0.5582		ari: 0.5391		f1: 0.7503		
epoch: 033		acc: 0.7566		nmi: 0.5513		ari: 0.5338		f1: 0.7462		
epoch: 034		acc: 0.7574		nmi: 0.5577		ari: 0.5366		f1: 0.7459		
epoch: 035		acc: 0.7589		nmi: 0.5611		ari: 0.5378		f1: 0.7482		
epoch: 036		acc: 0.7563		nmi: 0.5585		ari: 0.5341		f1: 0.7460		
epoch: 037		acc: 0.7544		nmi: 0.5527		ari: 0.5313		f1: 0.7434		
epoch: 038		acc: 0.7585		nmi: 0.5635		ari: 0.5376		f1: 0.7473		
epoch: 039		acc: 0.7533		nmi: 0.5532		ari: 0.5307		f1: 0.7422		
epoch: 040		acc: 0.7537		nmi: 0.5572		ari: 0.5324		f1: 0.7423		
epoch: 041		acc: 0.7574		nmi: 0.5628		ari: 0.5348		f1: 0.7472		
epoch: 042		acc: 0.7574		nmi: 0.5604		ari: 0.5379		f1: 0.7461		
epoch: 043		acc: 0.7559		nmi: 0.5563		ari: 0.5333		f1: 0.7449		
epoch: 044		acc: 0.7581		nmi: 0.5618		ari: 0.5368		f1: 0.7478		
epoch: 045		acc: 0.7515		nmi: 0.5519		ari: 0.5295		f1: 0.7400		
epoch: 046		acc: 0.7507		nmi: 0.5545		ari: 0.5275		f1: 0.7392		
epoch: 047		acc: 0.7507		nmi: 0.5509		ari: 0.5268		f1: 0.7395		
epoch: 048		acc: 0.7522		nmi: 0.5560		ari: 0.5278		f1: 0.7420		
epoch: 049		acc: 0.7518		nmi: 0.5586		ari: 0.5303		f1: 0.7402		
epoch: 050		acc: 0.7541		nmi: 0.5599		ari: 0.5342		f1: 0.7428		
The total number of parameters is: 0.220528M(1e6).
The max memory allocated to model is: 487.92 MB.
Time consuming: 3.07s or 0.05m
****************************************Training loop No.9****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=1433, out_features=128, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.7363		nmi: 0.5332		ari: 0.5014		f1: 0.7244		
epoch: 002		acc: 0.3131		nmi: 0.0400		ari: -0.0002		f1: 0.0980		
epoch: 003		acc: 0.6846		nmi: 0.4805		ari: 0.4112		f1: 0.6817		
epoch: 004		acc: 0.7648		nmi: 0.5550		ari: 0.5536		f1: 0.7399		
epoch: 005		acc: 0.7773		nmi: 0.5697		ari: 0.5658		f1: 0.7667		
epoch: 006		acc: 0.7600		nmi: 0.5485		ari: 0.5325		f1: 0.7503		
epoch: 007		acc: 0.7614		nmi: 0.5546		ari: 0.5293		f1: 0.7540		
epoch: 008		acc: 0.7777		nmi: 0.5761		ari: 0.5657		f1: 0.7673		
epoch: 009		acc: 0.7814		nmi: 0.5805		ari: 0.5738		f1: 0.7695		
epoch: 010		acc: 0.7818		nmi: 0.5821		ari: 0.5682		f1: 0.7719		
epoch: 011		acc: 0.7703		nmi: 0.5648		ari: 0.5499		f1: 0.7585		
epoch: 012		acc: 0.7821		nmi: 0.5818		ari: 0.5708		f1: 0.7721		
epoch: 013		acc: 0.7840		nmi: 0.5864		ari: 0.5728		f1: 0.7725		
epoch: 014		acc: 0.7781		nmi: 0.5796		ari: 0.5667		f1: 0.7656		
epoch: 015		acc: 0.7777		nmi: 0.5765		ari: 0.5608		f1: 0.7681		
epoch: 016		acc: 0.7781		nmi: 0.5790		ari: 0.5632		f1: 0.7692		
epoch: 017		acc: 0.7788		nmi: 0.5811		ari: 0.5631		f1: 0.7700		
epoch: 018		acc: 0.7733		nmi: 0.5736		ari: 0.5555		f1: 0.7627		
epoch: 019		acc: 0.7733		nmi: 0.5742		ari: 0.5514		f1: 0.7643		
epoch: 020		acc: 0.7751		nmi: 0.5770		ari: 0.5551		f1: 0.7658		
epoch: 021		acc: 0.7818		nmi: 0.5841		ari: 0.5659		f1: 0.7730		
epoch: 022		acc: 0.7810		nmi: 0.5813		ari: 0.5659		f1: 0.7723		
epoch: 023		acc: 0.7788		nmi: 0.5787		ari: 0.5629		f1: 0.7711		
epoch: 024		acc: 0.7829		nmi: 0.5838		ari: 0.5720		f1: 0.7732		
epoch: 025		acc: 0.7832		nmi: 0.5850		ari: 0.5709		f1: 0.7739		
epoch: 026		acc: 0.7810		nmi: 0.5843		ari: 0.5678		f1: 0.7727		
epoch: 027		acc: 0.7762		nmi: 0.5756		ari: 0.5611		f1: 0.7660		
epoch: 028		acc: 0.7773		nmi: 0.5786		ari: 0.5586		f1: 0.7689		
epoch: 029		acc: 0.7766		nmi: 0.5750		ari: 0.5562		f1: 0.7693		
epoch: 030		acc: 0.7792		nmi: 0.5783		ari: 0.5621		f1: 0.7708		
epoch: 031		acc: 0.7762		nmi: 0.5763		ari: 0.5552		f1: 0.7690		
epoch: 032		acc: 0.7795		nmi: 0.5773		ari: 0.5646		f1: 0.7700		
epoch: 033		acc: 0.7722		nmi: 0.5681		ari: 0.5507		f1: 0.7626		
epoch: 034		acc: 0.7758		nmi: 0.5747		ari: 0.5570		f1: 0.7661		
epoch: 035		acc: 0.7792		nmi: 0.5774		ari: 0.5637		f1: 0.7693		
epoch: 036		acc: 0.7773		nmi: 0.5706		ari: 0.5601		f1: 0.7677		
epoch: 037		acc: 0.7788		nmi: 0.5767		ari: 0.5633		f1: 0.7694		
epoch: 038		acc: 0.7821		nmi: 0.5799		ari: 0.5685		f1: 0.7728		
epoch: 039		acc: 0.7792		nmi: 0.5772		ari: 0.5633		f1: 0.7696		
epoch: 040		acc: 0.7810		nmi: 0.5819		ari: 0.5660		f1: 0.7720		
epoch: 041		acc: 0.7810		nmi: 0.5817		ari: 0.5665		f1: 0.7713		
epoch: 042		acc: 0.7747		nmi: 0.5731		ari: 0.5576		f1: 0.7648		
epoch: 043		acc: 0.7799		nmi: 0.5796		ari: 0.5667		f1: 0.7704		
epoch: 044		acc: 0.7736		nmi: 0.5686		ari: 0.5526		f1: 0.7661		
epoch: 045		acc: 0.7788		nmi: 0.5790		ari: 0.5642		f1: 0.7694		
epoch: 046		acc: 0.7773		nmi: 0.5726		ari: 0.5613		f1: 0.7676		
epoch: 047		acc: 0.7784		nmi: 0.5766		ari: 0.5638		f1: 0.7689		
epoch: 048		acc: 0.7766		nmi: 0.5736		ari: 0.5597		f1: 0.7674		
epoch: 049		acc: 0.7744		nmi: 0.5718		ari: 0.5561		f1: 0.7648		
epoch: 050		acc: 0.7699		nmi: 0.5650		ari: 0.5520		f1: 0.7594		
The total number of parameters is: 0.220528M(1e6).
The max memory allocated to model is: 487.92 MB.
Time consuming: 3.13s or 0.05m
****************************************Training loop No.10****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=1433, out_features=128, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.7323		nmi: 0.5287		ari: 0.4977		f1: 0.7195		
epoch: 002		acc: 0.3264		nmi: 0.1225		ari: 0.0024		f1: 0.1816		
epoch: 003		acc: 0.6883		nmi: 0.4832		ari: 0.4116		f1: 0.6871		
epoch: 004		acc: 0.7677		nmi: 0.5545		ari: 0.5489		f1: 0.7491		
epoch: 005		acc: 0.7855		nmi: 0.5748		ari: 0.5833		f1: 0.7750		
epoch: 006		acc: 0.7651		nmi: 0.5520		ari: 0.5433		f1: 0.7562		
epoch: 007		acc: 0.7482		nmi: 0.5362		ari: 0.5025		f1: 0.7437		
epoch: 008		acc: 0.7578		nmi: 0.5550		ari: 0.5187		f1: 0.7534		
epoch: 009		acc: 0.7736		nmi: 0.5675		ari: 0.5507		f1: 0.7672		
epoch: 010		acc: 0.7747		nmi: 0.5614		ari: 0.5547		f1: 0.7658		
epoch: 011		acc: 0.7792		nmi: 0.5650		ari: 0.5632		f1: 0.7699		
epoch: 012		acc: 0.7740		nmi: 0.5602		ari: 0.5553		f1: 0.7627		
epoch: 013		acc: 0.7758		nmi: 0.5710		ari: 0.5542		f1: 0.7687		
epoch: 014		acc: 0.7733		nmi: 0.5674		ari: 0.5498		f1: 0.7661		
epoch: 015		acc: 0.7781		nmi: 0.5722		ari: 0.5568		f1: 0.7708		
epoch: 016		acc: 0.7770		nmi: 0.5737		ari: 0.5570		f1: 0.7697		
epoch: 017		acc: 0.7725		nmi: 0.5670		ari: 0.5482		f1: 0.7660		
epoch: 018		acc: 0.7751		nmi: 0.5680		ari: 0.5537		f1: 0.7678		
epoch: 019		acc: 0.7755		nmi: 0.5693		ari: 0.5542		f1: 0.7673		
epoch: 020		acc: 0.7773		nmi: 0.5718		ari: 0.5594		f1: 0.7690		
epoch: 021		acc: 0.7777		nmi: 0.5741		ari: 0.5572		f1: 0.7704		
epoch: 022		acc: 0.7733		nmi: 0.5686		ari: 0.5519		f1: 0.7657		
epoch: 023		acc: 0.7762		nmi: 0.5707		ari: 0.5578		f1: 0.7676		
epoch: 024		acc: 0.7770		nmi: 0.5729		ari: 0.5634		f1: 0.7668		
epoch: 025		acc: 0.7755		nmi: 0.5714		ari: 0.5638		f1: 0.7642		
epoch: 026		acc: 0.7795		nmi: 0.5720		ari: 0.5665		f1: 0.7694		
epoch: 027		acc: 0.7762		nmi: 0.5689		ari: 0.5640		f1: 0.7649		
epoch: 028		acc: 0.7755		nmi: 0.5680		ari: 0.5605		f1: 0.7655		
epoch: 029		acc: 0.7751		nmi: 0.5672		ari: 0.5614		f1: 0.7633		
epoch: 030		acc: 0.7733		nmi: 0.5677		ari: 0.5586		f1: 0.7623		
epoch: 031		acc: 0.7707		nmi: 0.5658		ari: 0.5555		f1: 0.7595		
epoch: 032		acc: 0.7714		nmi: 0.5707		ari: 0.5571		f1: 0.7598		
epoch: 033		acc: 0.7714		nmi: 0.5680		ari: 0.5541		f1: 0.7613		
epoch: 034		acc: 0.7692		nmi: 0.5659		ari: 0.5507		f1: 0.7585		
epoch: 035		acc: 0.7688		nmi: 0.5666		ari: 0.5513		f1: 0.7582		
epoch: 036		acc: 0.7659		nmi: 0.5638		ari: 0.5482		f1: 0.7551		
epoch: 037		acc: 0.7666		nmi: 0.5639		ari: 0.5498		f1: 0.7550		
epoch: 038		acc: 0.7685		nmi: 0.5665		ari: 0.5531		f1: 0.7575		
epoch: 039		acc: 0.7681		nmi: 0.5690		ari: 0.5520		f1: 0.7573		
epoch: 040		acc: 0.7688		nmi: 0.5651		ari: 0.5564		f1: 0.7561		
epoch: 041		acc: 0.7611		nmi: 0.5580		ari: 0.5399		f1: 0.7507		
epoch: 042		acc: 0.7622		nmi: 0.5602		ari: 0.5417		f1: 0.7520		
epoch: 043		acc: 0.7603		nmi: 0.5557		ari: 0.5399		f1: 0.7490		
epoch: 044		acc: 0.7603		nmi: 0.5579		ari: 0.5393		f1: 0.7496		
epoch: 045		acc: 0.7563		nmi: 0.5525		ari: 0.5332		f1: 0.7450		
epoch: 046		acc: 0.7548		nmi: 0.5501		ari: 0.5307		f1: 0.7437		
epoch: 047		acc: 0.7566		nmi: 0.5534		ari: 0.5345		f1: 0.7450		
epoch: 048		acc: 0.7544		nmi: 0.5494		ari: 0.5311		f1: 0.7430		
epoch: 049		acc: 0.7537		nmi: 0.5489		ari: 0.5294		f1: 0.7432		
epoch: 050		acc: 0.7511		nmi: 0.5499		ari: 0.5261		f1: 0.7407		
The total number of parameters is: 0.220528M(1e6).
The max memory allocated to model is: 487.92 MB.
Time consuming: 3.17s or 0.05m
Namespace(is_pretrain=False, plot_clustering_tsne=False, plot_embedding_heatmap=False, adj_norm=False, adj_loop=True, adj_symmetric=True, desc='default', model_name='SYNC', dataset_name='cora', root=None, k=None, t=None, loops=10, feature_type='tensor', label_type='npy', adj_type='tensor', seed=325, epsilon=0.0, device='cuda', clusters=7, nodes=2708, lr=0.005, max_epoch=50, pretrain_lr=0.001, pretrain_epoch=30, input_dim=1433, log_save_path='./logs/SYNC/cora/', dataset_path='../data/', clustering_tsne_save_path='./img/clustering/SYNC/cora/', embedding_heatmap_save_path='./img/heatmap/SYNC/cora/', pretrain_save_path='./pretrain/pretrain_tigae/SYNC/cora/', hidden_dim=256, embedding_dim=16, linear_dim=128, beta=0)
Total loops: 10
****************************************Mean value:****************************************
acc: 0.7863±0.0034		nmi: 0.5819±0.0047		ari: 0.5794±0.0101		f1: 0.7771±0.0028
Training over! Punch out!
Loading amap dataset from local
****************************************Training loop No.1****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=745, out_features=512, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.8111		nmi: 0.6924		ari: 0.6197		f1: 0.7997		
epoch: 002		acc: 0.7922		nmi: 0.6737		ari: 0.5814		f1: 0.7831		
epoch: 003		acc: 0.7692		nmi: 0.6657		ari: 0.5548		f1: 0.7581		
epoch: 004		acc: 0.7976		nmi: 0.6859		ari: 0.5968		f1: 0.7886		
epoch: 005		acc: 0.8058		nmi: 0.6846		ari: 0.6097		f1: 0.7914		
epoch: 006		acc: 0.8247		nmi: 0.6963		ari: 0.6509		f1: 0.8066		
epoch: 007		acc: 0.8254		nmi: 0.6997		ari: 0.6504		f1: 0.8080		
epoch: 008		acc: 0.8078		nmi: 0.6885		ari: 0.6154		f1: 0.7939		
epoch: 009		acc: 0.8022		nmi: 0.6911		ari: 0.6037		f1: 0.7919		
epoch: 010		acc: 0.7946		nmi: 0.6867		ari: 0.5921		f1: 0.7873		
epoch: 011		acc: 0.8008		nmi: 0.6891		ari: 0.6020		f1: 0.7928		
epoch: 012		acc: 0.8060		nmi: 0.6906		ari: 0.6121		f1: 0.7940		
epoch: 013		acc: 0.8084		nmi: 0.6886		ari: 0.6171		f1: 0.7935		
epoch: 014		acc: 0.8149		nmi: 0.6944		ari: 0.6291		f1: 0.7991		
epoch: 015		acc: 0.8150		nmi: 0.6916		ari: 0.6299		f1: 0.7983		
epoch: 016		acc: 0.8192		nmi: 0.6973		ari: 0.6382		f1: 0.8032		
epoch: 017		acc: 0.8169		nmi: 0.6951		ari: 0.6331		f1: 0.8016		
epoch: 018		acc: 0.8108		nmi: 0.6927		ari: 0.6208		f1: 0.7973		
epoch: 019		acc: 0.8081		nmi: 0.6899		ari: 0.6153		f1: 0.7943		
epoch: 020		acc: 0.8108		nmi: 0.6949		ari: 0.6192		f1: 0.7995		
epoch: 021		acc: 0.8082		nmi: 0.6915		ari: 0.6150		f1: 0.7969		
epoch: 022		acc: 0.8081		nmi: 0.6917		ari: 0.6159		f1: 0.7954		
epoch: 023		acc: 0.8077		nmi: 0.6884		ari: 0.6154		f1: 0.7927		
epoch: 024		acc: 0.8097		nmi: 0.6896		ari: 0.6177		f1: 0.7972		
epoch: 025		acc: 0.8093		nmi: 0.6882		ari: 0.6178		f1: 0.7955		
epoch: 026		acc: 0.8131		nmi: 0.6924		ari: 0.6250		f1: 0.7993		
epoch: 027		acc: 0.8132		nmi: 0.6971		ari: 0.6242		f1: 0.8010		
epoch: 028		acc: 0.8125		nmi: 0.6944		ari: 0.6225		f1: 0.8008		
epoch: 029		acc: 0.8102		nmi: 0.6928		ari: 0.6188		f1: 0.7977		
epoch: 030		acc: 0.8103		nmi: 0.6923		ari: 0.6177		f1: 0.7997		
epoch: 031		acc: 0.8076		nmi: 0.6900		ari: 0.6130		f1: 0.7958		
epoch: 032		acc: 0.8098		nmi: 0.6918		ari: 0.6181		f1: 0.7966		
epoch: 033		acc: 0.8112		nmi: 0.6938		ari: 0.6197		f1: 0.7995		
epoch: 034		acc: 0.8088		nmi: 0.6902		ari: 0.6161		f1: 0.7960		
epoch: 035		acc: 0.8093		nmi: 0.6920		ari: 0.6166		f1: 0.7977		
epoch: 036		acc: 0.8092		nmi: 0.6889		ari: 0.6169		f1: 0.7970		
epoch: 037		acc: 0.8118		nmi: 0.6943		ari: 0.6202		f1: 0.8014		
epoch: 038		acc: 0.8123		nmi: 0.6961		ari: 0.6215		f1: 0.8016		
epoch: 039		acc: 0.8110		nmi: 0.6947		ari: 0.6196		f1: 0.7999		
epoch: 040		acc: 0.8108		nmi: 0.6951		ari: 0.6187		f1: 0.8001		
epoch: 041		acc: 0.8132		nmi: 0.6990		ari: 0.6226		f1: 0.8024		
epoch: 042		acc: 0.8116		nmi: 0.6946		ari: 0.6201		f1: 0.8006		
epoch: 043		acc: 0.8111		nmi: 0.6948		ari: 0.6192		f1: 0.7996		
epoch: 044		acc: 0.8105		nmi: 0.6938		ari: 0.6181		f1: 0.7995		
epoch: 045		acc: 0.8108		nmi: 0.6937		ari: 0.6185		f1: 0.8004		
epoch: 046		acc: 0.8125		nmi: 0.6965		ari: 0.6211		f1: 0.8030		
epoch: 047		acc: 0.8118		nmi: 0.6958		ari: 0.6197		f1: 0.8013		
epoch: 048		acc: 0.8124		nmi: 0.6973		ari: 0.6217		f1: 0.8020		
epoch: 049		acc: 0.8123		nmi: 0.6951		ari: 0.6214		f1: 0.8009		
epoch: 050		acc: 0.8133		nmi: 0.6962		ari: 0.6231		f1: 0.8025		
The total number of parameters is: 0.517248M(1e6).
The max memory allocated to model is: 3661.78 MB.
Time consuming: 46.33s or 0.77m
****************************************Training loop No.2****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=745, out_features=512, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.8103		nmi: 0.6908		ari: 0.6186		f1: 0.7983		
epoch: 002		acc: 0.7925		nmi: 0.6728		ari: 0.5818		f1: 0.7828		
epoch: 003		acc: 0.7659		nmi: 0.6611		ari: 0.5502		f1: 0.7545		
epoch: 004		acc: 0.7986		nmi: 0.6878		ari: 0.5983		f1: 0.7889		
epoch: 005		acc: 0.8039		nmi: 0.6822		ari: 0.6071		f1: 0.7898		
epoch: 006		acc: 0.8234		nmi: 0.6946		ari: 0.6490		f1: 0.8034		
epoch: 007		acc: 0.8227		nmi: 0.6970		ari: 0.6451		f1: 0.8061		
epoch: 008		acc: 0.8085		nmi: 0.6903		ari: 0.6164		f1: 0.7947		
epoch: 009		acc: 0.8016		nmi: 0.6893		ari: 0.6032		f1: 0.7909		
epoch: 010		acc: 0.7937		nmi: 0.6852		ari: 0.5899		f1: 0.7863		
epoch: 011		acc: 0.7999		nmi: 0.6870		ari: 0.6005		f1: 0.7914		
epoch: 012		acc: 0.8058		nmi: 0.6881		ari: 0.6114		f1: 0.7932		
epoch: 013		acc: 0.8093		nmi: 0.6889		ari: 0.6187		f1: 0.7934		
epoch: 014		acc: 0.8146		nmi: 0.6933		ari: 0.6277		f1: 0.8004		
epoch: 015		acc: 0.8197		nmi: 0.6980		ari: 0.6393		f1: 0.8022		
epoch: 016		acc: 0.8179		nmi: 0.6950		ari: 0.6363		f1: 0.8006		
epoch: 017		acc: 0.8157		nmi: 0.6931		ari: 0.6302		f1: 0.8017		
epoch: 018		acc: 0.8120		nmi: 0.6915		ari: 0.6222		f1: 0.7987		
epoch: 019		acc: 0.8097		nmi: 0.6947		ari: 0.6172		f1: 0.7984		
epoch: 020		acc: 0.8071		nmi: 0.6909		ari: 0.6124		f1: 0.7963		
epoch: 021		acc: 0.8073		nmi: 0.6903		ari: 0.6133		f1: 0.7954		
epoch: 022		acc: 0.8084		nmi: 0.6902		ari: 0.6151		f1: 0.7970		
epoch: 023		acc: 0.8099		nmi: 0.6906		ari: 0.6187		f1: 0.7970		
epoch: 024		acc: 0.8110		nmi: 0.6936		ari: 0.6208		f1: 0.7978		
epoch: 025		acc: 0.8122		nmi: 0.6952		ari: 0.6225		f1: 0.7988		
epoch: 026		acc: 0.8129		nmi: 0.6946		ari: 0.6241		f1: 0.8009		
epoch: 027		acc: 0.8142		nmi: 0.6964		ari: 0.6262		f1: 0.8016		
epoch: 028		acc: 0.8111		nmi: 0.6920		ari: 0.6207		f1: 0.7989		
epoch: 029		acc: 0.8114		nmi: 0.6938		ari: 0.6207		f1: 0.7997		
epoch: 030		acc: 0.8114		nmi: 0.6940		ari: 0.6191		f1: 0.8008		
epoch: 031		acc: 0.8103		nmi: 0.6946		ari: 0.6175		f1: 0.8008		
epoch: 032		acc: 0.8107		nmi: 0.6928		ari: 0.6196		f1: 0.7990		
epoch: 033		acc: 0.8073		nmi: 0.6862		ari: 0.6144		f1: 0.7933		
epoch: 034		acc: 0.8092		nmi: 0.6912		ari: 0.6161		f1: 0.7972		
epoch: 035		acc: 0.8102		nmi: 0.6935		ari: 0.6185		f1: 0.7980		
epoch: 036		acc: 0.8118		nmi: 0.6960		ari: 0.6202		f1: 0.8012		
epoch: 037		acc: 0.8108		nmi: 0.6922		ari: 0.6197		f1: 0.7993		
epoch: 038		acc: 0.8124		nmi: 0.6948		ari: 0.6208		f1: 0.8023		
epoch: 039		acc: 0.8103		nmi: 0.6918		ari: 0.6176		f1: 0.7994		
epoch: 040		acc: 0.8112		nmi: 0.6931		ari: 0.6196		f1: 0.7995		
epoch: 041		acc: 0.8092		nmi: 0.6916		ari: 0.6167		f1: 0.7965		
epoch: 042		acc: 0.8095		nmi: 0.6914		ari: 0.6170		f1: 0.7974		
epoch: 043		acc: 0.8107		nmi: 0.6938		ari: 0.6193		f1: 0.7977		
epoch: 044		acc: 0.8108		nmi: 0.6942		ari: 0.6189		f1: 0.7997		
epoch: 045		acc: 0.8119		nmi: 0.6957		ari: 0.6204		f1: 0.8014		
epoch: 046		acc: 0.8137		nmi: 0.7003		ari: 0.6235		f1: 0.8036		
epoch: 047		acc: 0.8132		nmi: 0.6978		ari: 0.6227		f1: 0.8031		
epoch: 048		acc: 0.8124		nmi: 0.6946		ari: 0.6217		f1: 0.8014		
epoch: 049		acc: 0.8150		nmi: 0.6985		ari: 0.6251		f1: 0.8054		
epoch: 050		acc: 0.8125		nmi: 0.6957		ari: 0.6212		f1: 0.8017		
The total number of parameters is: 0.517248M(1e6).
The max memory allocated to model is: 3666.66 MB.
Time consuming: 43.67s or 0.73m
****************************************Training loop No.3****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=745, out_features=512, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.8103		nmi: 0.6909		ari: 0.6179		f1: 0.7985		
epoch: 002		acc: 0.7928		nmi: 0.6725		ari: 0.5817		f1: 0.7835		
epoch: 003		acc: 0.7688		nmi: 0.6643		ari: 0.5545		f1: 0.7576		
epoch: 004		acc: 0.7991		nmi: 0.6887		ari: 0.5994		f1: 0.7903		
epoch: 005		acc: 0.8031		nmi: 0.6793		ari: 0.6068		f1: 0.7864		
epoch: 006		acc: 0.8255		nmi: 0.6971		ari: 0.6516		f1: 0.8066		
epoch: 007		acc: 0.8230		nmi: 0.6968		ari: 0.6472		f1: 0.8047		
epoch: 008		acc: 0.8095		nmi: 0.6906		ari: 0.6173		f1: 0.7965		
epoch: 009		acc: 0.8003		nmi: 0.6887		ari: 0.6005		f1: 0.7902		
epoch: 010		acc: 0.7946		nmi: 0.6863		ari: 0.5915		f1: 0.7882		
epoch: 011		acc: 0.7987		nmi: 0.6863		ari: 0.5992		f1: 0.7903		
epoch: 012		acc: 0.8064		nmi: 0.6900		ari: 0.6112		f1: 0.7956		
epoch: 013		acc: 0.8102		nmi: 0.6912		ari: 0.6194		f1: 0.7959		
epoch: 014		acc: 0.8124		nmi: 0.6904		ari: 0.6254		f1: 0.7965		
epoch: 015		acc: 0.8184		nmi: 0.6944		ari: 0.6362		f1: 0.8017		
epoch: 016		acc: 0.8178		nmi: 0.6942		ari: 0.6354		f1: 0.8024		
epoch: 017		acc: 0.8162		nmi: 0.6965		ari: 0.6305		f1: 0.8029		
epoch: 018		acc: 0.8125		nmi: 0.6953		ari: 0.6229		f1: 0.8001		
epoch: 019		acc: 0.8073		nmi: 0.6913		ari: 0.6139		f1: 0.7951		
epoch: 020		acc: 0.8103		nmi: 0.6953		ari: 0.6177		f1: 0.7998		
epoch: 021		acc: 0.8082		nmi: 0.6899		ari: 0.6153		f1: 0.7960		
epoch: 022		acc: 0.8097		nmi: 0.6933		ari: 0.6177		f1: 0.7977		
epoch: 023		acc: 0.8090		nmi: 0.6895		ari: 0.6164		f1: 0.7966		
epoch: 024		acc: 0.8099		nmi: 0.6919		ari: 0.6191		f1: 0.7966		
epoch: 025		acc: 0.8101		nmi: 0.6886		ari: 0.6191		f1: 0.7970		
epoch: 026		acc: 0.8106		nmi: 0.6914		ari: 0.6194		f1: 0.7979		
epoch: 027		acc: 0.8119		nmi: 0.6926		ari: 0.6218		f1: 0.7997		
epoch: 028		acc: 0.8107		nmi: 0.6922		ari: 0.6206		f1: 0.7979		
epoch: 029		acc: 0.8115		nmi: 0.6948		ari: 0.6207		f1: 0.7997		
epoch: 030		acc: 0.8115		nmi: 0.6948		ari: 0.6197		f1: 0.8016		
epoch: 031		acc: 0.8094		nmi: 0.6924		ari: 0.6167		f1: 0.7984		
epoch: 032		acc: 0.8105		nmi: 0.6936		ari: 0.6188		f1: 0.7988		
epoch: 033		acc: 0.8098		nmi: 0.6928		ari: 0.6177		f1: 0.7972		
epoch: 034		acc: 0.8086		nmi: 0.6898		ari: 0.6157		f1: 0.7958		
epoch: 035		acc: 0.8090		nmi: 0.6912		ari: 0.6163		f1: 0.7969		
epoch: 036		acc: 0.8112		nmi: 0.6938		ari: 0.6188		f1: 0.8011		
epoch: 037		acc: 0.8119		nmi: 0.6947		ari: 0.6204		f1: 0.8014		
epoch: 038		acc: 0.8140		nmi: 0.6960		ari: 0.6235		f1: 0.8039		
epoch: 039		acc: 0.8114		nmi: 0.6934		ari: 0.6193		f1: 0.8004		
epoch: 040		acc: 0.8105		nmi: 0.6934		ari: 0.6180		f1: 0.7996		
epoch: 041		acc: 0.8112		nmi: 0.6962		ari: 0.6199		f1: 0.7997		
epoch: 042		acc: 0.8111		nmi: 0.6947		ari: 0.6194		f1: 0.7997		
epoch: 043		acc: 0.8105		nmi: 0.6937		ari: 0.6175		f1: 0.8001		
epoch: 044		acc: 0.8092		nmi: 0.6912		ari: 0.6160		f1: 0.7972		
epoch: 045		acc: 0.8116		nmi: 0.6972		ari: 0.6198		f1: 0.8012		
epoch: 046		acc: 0.8112		nmi: 0.6934		ari: 0.6188		f1: 0.8006		
epoch: 047		acc: 0.8125		nmi: 0.6941		ari: 0.6209		f1: 0.8026		
epoch: 048		acc: 0.8137		nmi: 0.6983		ari: 0.6223		f1: 0.8046		
epoch: 049		acc: 0.8132		nmi: 0.6981		ari: 0.6228		f1: 0.8022		
epoch: 050		acc: 0.8154		nmi: 0.7009		ari: 0.6260		f1: 0.8058		
The total number of parameters is: 0.517248M(1e6).
The max memory allocated to model is: 3666.66 MB.
Time consuming: 43.64s or 0.73m
****************************************Training loop No.4****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=745, out_features=512, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.8105		nmi: 0.6919		ari: 0.6176		f1: 0.7986		
epoch: 002		acc: 0.7919		nmi: 0.6764		ari: 0.5808		f1: 0.7836		
epoch: 003		acc: 0.7680		nmi: 0.6626		ari: 0.5516		f1: 0.7575		
epoch: 004		acc: 0.7988		nmi: 0.6877		ari: 0.5981		f1: 0.7890		
epoch: 005		acc: 0.8021		nmi: 0.6771		ari: 0.6044		f1: 0.7860		
epoch: 006		acc: 0.8241		nmi: 0.6951		ari: 0.6505		f1: 0.8046		
epoch: 007		acc: 0.8241		nmi: 0.6982		ari: 0.6485		f1: 0.8059		
epoch: 008		acc: 0.8095		nmi: 0.6919		ari: 0.6179		f1: 0.7960		
epoch: 009		acc: 0.7984		nmi: 0.6858		ari: 0.5974		f1: 0.7878		
epoch: 010		acc: 0.7939		nmi: 0.6858		ari: 0.5909		f1: 0.7867		
epoch: 011		acc: 0.8007		nmi: 0.6897		ari: 0.6019		f1: 0.7929		
epoch: 012		acc: 0.8067		nmi: 0.6921		ari: 0.6132		f1: 0.7954		
epoch: 013		acc: 0.8084		nmi: 0.6899		ari: 0.6168		f1: 0.7942		
epoch: 014		acc: 0.8141		nmi: 0.6938		ari: 0.6278		f1: 0.7988		
epoch: 015		acc: 0.8156		nmi: 0.6914		ari: 0.6317		f1: 0.7983		
epoch: 016		acc: 0.8180		nmi: 0.6944		ari: 0.6356		f1: 0.8022		
epoch: 017		acc: 0.8152		nmi: 0.6941		ari: 0.6288		f1: 0.8009		
epoch: 018		acc: 0.8114		nmi: 0.6947		ari: 0.6219		f1: 0.7984		
epoch: 019		acc: 0.8093		nmi: 0.6937		ari: 0.6174		f1: 0.7969		
epoch: 020		acc: 0.8090		nmi: 0.6930		ari: 0.6166		f1: 0.7971		
epoch: 021		acc: 0.8084		nmi: 0.6926		ari: 0.6159		f1: 0.7969		
epoch: 022		acc: 0.8110		nmi: 0.6944		ari: 0.6202		f1: 0.7982		
epoch: 023		acc: 0.8089		nmi: 0.6899		ari: 0.6171		f1: 0.7956		
epoch: 024		acc: 0.8103		nmi: 0.6909		ari: 0.6195		f1: 0.7974		
epoch: 025		acc: 0.8105		nmi: 0.6920		ari: 0.6194		f1: 0.7969		
epoch: 026		acc: 0.8110		nmi: 0.6909		ari: 0.6204		f1: 0.7982		
epoch: 027		acc: 0.8123		nmi: 0.6921		ari: 0.6223		f1: 0.7999		
epoch: 028		acc: 0.8111		nmi: 0.6913		ari: 0.6202		f1: 0.7992		
epoch: 029		acc: 0.8111		nmi: 0.6946		ari: 0.6200		f1: 0.7992		
epoch: 030		acc: 0.8098		nmi: 0.6923		ari: 0.6176		f1: 0.7981		
epoch: 031		acc: 0.8105		nmi: 0.6938		ari: 0.6184		f1: 0.7995		
epoch: 032		acc: 0.8106		nmi: 0.6936		ari: 0.6193		f1: 0.7978		
epoch: 033		acc: 0.8114		nmi: 0.6947		ari: 0.6209		f1: 0.7988		
epoch: 034		acc: 0.8089		nmi: 0.6906		ari: 0.6162		f1: 0.7964		
epoch: 035		acc: 0.8097		nmi: 0.6922		ari: 0.6178		f1: 0.7974		
epoch: 036		acc: 0.8095		nmi: 0.6897		ari: 0.6181		f1: 0.7964		
epoch: 037		acc: 0.8129		nmi: 0.6968		ari: 0.6230		f1: 0.8019		
epoch: 038		acc: 0.8118		nmi: 0.6930		ari: 0.6206		f1: 0.8007		
epoch: 039		acc: 0.8131		nmi: 0.6967		ari: 0.6234		f1: 0.8015		
epoch: 040		acc: 0.8108		nmi: 0.6935		ari: 0.6182		f1: 0.8005		
epoch: 041		acc: 0.8115		nmi: 0.6948		ari: 0.6195		f1: 0.8012		
epoch: 042		acc: 0.8101		nmi: 0.6946		ari: 0.6168		f1: 0.7996		
epoch: 043		acc: 0.8098		nmi: 0.6933		ari: 0.6166		f1: 0.7988		
epoch: 044		acc: 0.8114		nmi: 0.6949		ari: 0.6198		f1: 0.7998		
epoch: 045		acc: 0.8111		nmi: 0.6955		ari: 0.6183		f1: 0.8013		
epoch: 046		acc: 0.8107		nmi: 0.6951		ari: 0.6184		f1: 0.8007		
epoch: 047		acc: 0.8114		nmi: 0.6932		ari: 0.6191		f1: 0.8013		
epoch: 048		acc: 0.8129		nmi: 0.6960		ari: 0.6224		f1: 0.8019		
epoch: 049		acc: 0.8108		nmi: 0.6927		ari: 0.6179		f1: 0.8005		
epoch: 050		acc: 0.8145		nmi: 0.6992		ari: 0.6249		f1: 0.8035		
The total number of parameters is: 0.517248M(1e6).
The max memory allocated to model is: 3666.66 MB.
Time consuming: 43.79s or 0.73m
****************************************Training loop No.5****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=745, out_features=512, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.8133		nmi: 0.6958		ari: 0.6229		f1: 0.8026		
epoch: 002		acc: 0.7919		nmi: 0.6725		ari: 0.5807		f1: 0.7827		
epoch: 003		acc: 0.7655		nmi: 0.6605		ari: 0.5503		f1: 0.7540		
epoch: 004		acc: 0.7966		nmi: 0.6851		ari: 0.5939		f1: 0.7892		
epoch: 005		acc: 0.8056		nmi: 0.6831		ari: 0.6115		f1: 0.7890		
epoch: 006		acc: 0.8242		nmi: 0.6954		ari: 0.6494		f1: 0.8058		
epoch: 007		acc: 0.8250		nmi: 0.6985		ari: 0.6495		f1: 0.8081		
epoch: 008		acc: 0.8093		nmi: 0.6922		ari: 0.6183		f1: 0.7953		
epoch: 009		acc: 0.7997		nmi: 0.6868		ari: 0.6000		f1: 0.7882		
epoch: 010		acc: 0.7942		nmi: 0.6864		ari: 0.5918		f1: 0.7864		
epoch: 011		acc: 0.7995		nmi: 0.6884		ari: 0.5999		f1: 0.7921		
epoch: 012		acc: 0.8068		nmi: 0.6904		ari: 0.6131		f1: 0.7953		
epoch: 013		acc: 0.8080		nmi: 0.6891		ari: 0.6159		f1: 0.7941		
epoch: 014		acc: 0.8149		nmi: 0.6938		ari: 0.6293		f1: 0.7991		
epoch: 015		acc: 0.8149		nmi: 0.6903		ari: 0.6309		f1: 0.7982		
epoch: 016		acc: 0.8165		nmi: 0.6903		ari: 0.6338		f1: 0.7997		
epoch: 017		acc: 0.8156		nmi: 0.6942		ari: 0.6298		f1: 0.8008		
epoch: 018		acc: 0.8112		nmi: 0.6954		ari: 0.6212		f1: 0.7979		
epoch: 019		acc: 0.8077		nmi: 0.6927		ari: 0.6151		f1: 0.7947		
epoch: 020		acc: 0.8090		nmi: 0.6935		ari: 0.6157		f1: 0.7984		
epoch: 021		acc: 0.8078		nmi: 0.6897		ari: 0.6134		f1: 0.7968		
epoch: 022		acc: 0.8110		nmi: 0.6945		ari: 0.6205		f1: 0.7981		
epoch: 023		acc: 0.8072		nmi: 0.6864		ari: 0.6139		f1: 0.7940		
epoch: 024		acc: 0.8103		nmi: 0.6908		ari: 0.6186		f1: 0.7975		
epoch: 025		acc: 0.8089		nmi: 0.6904		ari: 0.6171		f1: 0.7956		
epoch: 026		acc: 0.8135		nmi: 0.6961		ari: 0.6247		f1: 0.8010		
epoch: 027		acc: 0.8122		nmi: 0.6922		ari: 0.6223		f1: 0.8004		
epoch: 028		acc: 0.8127		nmi: 0.6944		ari: 0.6233		f1: 0.8004		
epoch: 029		acc: 0.8102		nmi: 0.6915		ari: 0.6180		f1: 0.7990		
epoch: 030		acc: 0.8099		nmi: 0.6925		ari: 0.6179		f1: 0.7985		
epoch: 031		acc: 0.8098		nmi: 0.6923		ari: 0.6174		f1: 0.7988		
epoch: 032		acc: 0.8086		nmi: 0.6900		ari: 0.6153		f1: 0.7975		
epoch: 033		acc: 0.8077		nmi: 0.6903		ari: 0.6148		f1: 0.7944		
epoch: 034		acc: 0.8095		nmi: 0.6929		ari: 0.6162		f1: 0.7981		
epoch: 035		acc: 0.8115		nmi: 0.6955		ari: 0.6195		f1: 0.8004		
epoch: 036		acc: 0.8125		nmi: 0.6944		ari: 0.6223		f1: 0.8005		
epoch: 037		acc: 0.8119		nmi: 0.6945		ari: 0.6215		f1: 0.8003		
epoch: 038		acc: 0.8114		nmi: 0.6942		ari: 0.6205		f1: 0.7995		
epoch: 039		acc: 0.8135		nmi: 0.6968		ari: 0.6228		f1: 0.8035		
epoch: 040		acc: 0.8114		nmi: 0.6945		ari: 0.6195		f1: 0.8006		
epoch: 041		acc: 0.8107		nmi: 0.6928		ari: 0.6187		f1: 0.7996		
epoch: 042		acc: 0.8092		nmi: 0.6905		ari: 0.6158		f1: 0.7974		
epoch: 043		acc: 0.8118		nmi: 0.6954		ari: 0.6198		f1: 0.8016		
epoch: 044		acc: 0.8103		nmi: 0.6933		ari: 0.6179		f1: 0.7993		
epoch: 045		acc: 0.8106		nmi: 0.6943		ari: 0.6186		f1: 0.7998		
epoch: 046		acc: 0.8124		nmi: 0.6968		ari: 0.6214		f1: 0.8025		
epoch: 047		acc: 0.8136		nmi: 0.6980		ari: 0.6229		f1: 0.8041		
epoch: 048		acc: 0.8118		nmi: 0.6954		ari: 0.6207		f1: 0.8004		
epoch: 049		acc: 0.8115		nmi: 0.6948		ari: 0.6196		f1: 0.8001		
epoch: 050		acc: 0.8139		nmi: 0.6979		ari: 0.6247		f1: 0.8023		
The total number of parameters is: 0.517248M(1e6).
The max memory allocated to model is: 3666.66 MB.
Time consuming: 43.63s or 0.73m
****************************************Training loop No.6****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=745, out_features=512, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.8114		nmi: 0.6942		ari: 0.6203		f1: 0.7999		
epoch: 002		acc: 0.7916		nmi: 0.6727		ari: 0.5799		f1: 0.7830		
epoch: 003		acc: 0.7633		nmi: 0.6579		ari: 0.5453		f1: 0.7531		
epoch: 004		acc: 0.7978		nmi: 0.6864		ari: 0.5963		f1: 0.7885		
epoch: 005		acc: 0.8026		nmi: 0.6783		ari: 0.6061		f1: 0.7860		
epoch: 006		acc: 0.8252		nmi: 0.6959		ari: 0.6521		f1: 0.8065		
epoch: 007		acc: 0.8224		nmi: 0.6967		ari: 0.6454		f1: 0.8046		
epoch: 008		acc: 0.8075		nmi: 0.6879		ari: 0.6154		f1: 0.7928		
epoch: 009		acc: 0.8016		nmi: 0.6887		ari: 0.6023		f1: 0.7912		
epoch: 010		acc: 0.7942		nmi: 0.6853		ari: 0.5913		f1: 0.7870		
epoch: 011		acc: 0.7997		nmi: 0.6887		ari: 0.6002		f1: 0.7918		
epoch: 012		acc: 0.8056		nmi: 0.6887		ari: 0.6116		f1: 0.7936		
epoch: 013		acc: 0.8103		nmi: 0.6903		ari: 0.6194		f1: 0.7971		
epoch: 014		acc: 0.8152		nmi: 0.6942		ari: 0.6295		f1: 0.8000		
epoch: 015		acc: 0.8179		nmi: 0.6935		ari: 0.6357		f1: 0.8004		
epoch: 016		acc: 0.8208		nmi: 0.6979		ari: 0.6401		f1: 0.8052		
epoch: 017		acc: 0.8170		nmi: 0.6961		ari: 0.6326		f1: 0.8032		
epoch: 018		acc: 0.8118		nmi: 0.6924		ari: 0.6216		f1: 0.7990		
epoch: 019		acc: 0.8092		nmi: 0.6924		ari: 0.6159		f1: 0.7972		
epoch: 020		acc: 0.8092		nmi: 0.6924		ari: 0.6161		f1: 0.7982		
epoch: 021		acc: 0.8099		nmi: 0.6938		ari: 0.6183		f1: 0.7977		
epoch: 022		acc: 0.8072		nmi: 0.6887		ari: 0.6135		f1: 0.7946		
epoch: 023		acc: 0.8108		nmi: 0.6929		ari: 0.6198		f1: 0.7978		
epoch: 024		acc: 0.8090		nmi: 0.6906		ari: 0.6169		f1: 0.7964		
epoch: 025		acc: 0.8106		nmi: 0.6909		ari: 0.6204		f1: 0.7965		
epoch: 026		acc: 0.8118		nmi: 0.6931		ari: 0.6216		f1: 0.7990		
epoch: 027		acc: 0.8123		nmi: 0.6922		ari: 0.6228		f1: 0.8001		
epoch: 028		acc: 0.8122		nmi: 0.6930		ari: 0.6229		f1: 0.7987		
epoch: 029		acc: 0.8132		nmi: 0.6955		ari: 0.6230		f1: 0.8022		
epoch: 030		acc: 0.8114		nmi: 0.6945		ari: 0.6204		f1: 0.8001		
epoch: 031		acc: 0.8107		nmi: 0.6955		ari: 0.6183		f1: 0.8000		
epoch: 032		acc: 0.8090		nmi: 0.6917		ari: 0.6156		f1: 0.7981		
epoch: 033		acc: 0.8103		nmi: 0.6919		ari: 0.6192		f1: 0.7968		
epoch: 034		acc: 0.8097		nmi: 0.6922		ari: 0.6176		f1: 0.7971		
epoch: 035		acc: 0.8103		nmi: 0.6931		ari: 0.6178		f1: 0.7991		
epoch: 036		acc: 0.8118		nmi: 0.6941		ari: 0.6212		f1: 0.8006		
epoch: 037		acc: 0.8111		nmi: 0.6935		ari: 0.6194		f1: 0.7997		
epoch: 038		acc: 0.8119		nmi: 0.6937		ari: 0.6206		f1: 0.8011		
epoch: 039		acc: 0.8114		nmi: 0.6947		ari: 0.6200		f1: 0.8002		
epoch: 040		acc: 0.8129		nmi: 0.6958		ari: 0.6228		f1: 0.8021		
epoch: 041		acc: 0.8116		nmi: 0.6938		ari: 0.6202		f1: 0.8006		
epoch: 042		acc: 0.8119		nmi: 0.6948		ari: 0.6208		f1: 0.8006		
epoch: 043		acc: 0.8102		nmi: 0.6910		ari: 0.6176		f1: 0.7985		
epoch: 044		acc: 0.8115		nmi: 0.6964		ari: 0.6203		f1: 0.7994		
epoch: 045		acc: 0.8098		nmi: 0.6931		ari: 0.6173		f1: 0.7979		
epoch: 046		acc: 0.8119		nmi: 0.6956		ari: 0.6197		f1: 0.8021		
epoch: 047		acc: 0.8118		nmi: 0.6951		ari: 0.6207		f1: 0.8006		
epoch: 048		acc: 0.8129		nmi: 0.6968		ari: 0.6216		f1: 0.8031		
epoch: 049		acc: 0.8136		nmi: 0.6977		ari: 0.6233		f1: 0.8027		
epoch: 050		acc: 0.8127		nmi: 0.6962		ari: 0.6224		f1: 0.8011		
The total number of parameters is: 0.517248M(1e6).
The max memory allocated to model is: 3666.66 MB.
Time consuming: 43.5s or 0.72m
****************************************Training loop No.7****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=745, out_features=512, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.8103		nmi: 0.6919		ari: 0.6185		f1: 0.7983		
epoch: 002		acc: 0.7915		nmi: 0.6735		ari: 0.5806		f1: 0.7828		
epoch: 003		acc: 0.7675		nmi: 0.6609		ari: 0.5511		f1: 0.7571		
epoch: 004		acc: 0.7983		nmi: 0.6867		ari: 0.5971		f1: 0.7897		
epoch: 005		acc: 0.8058		nmi: 0.6836		ari: 0.6108		f1: 0.7905		
epoch: 006		acc: 0.8235		nmi: 0.6936		ari: 0.6495		f1: 0.8045		
epoch: 007		acc: 0.8248		nmi: 0.6991		ari: 0.6492		f1: 0.8081		
epoch: 008		acc: 0.8081		nmi: 0.6902		ari: 0.6163		f1: 0.7939		
epoch: 009		acc: 0.8022		nmi: 0.6920		ari: 0.6043		f1: 0.7909		
epoch: 010		acc: 0.7940		nmi: 0.6849		ari: 0.5912		f1: 0.7862		
epoch: 011		acc: 0.7991		nmi: 0.6886		ari: 0.5991		f1: 0.7923		
epoch: 012		acc: 0.8055		nmi: 0.6882		ari: 0.6101		f1: 0.7951		
epoch: 013		acc: 0.8082		nmi: 0.6887		ari: 0.6167		f1: 0.7938		
epoch: 014		acc: 0.8119		nmi: 0.6886		ari: 0.6240		f1: 0.7958		
epoch: 015		acc: 0.8183		nmi: 0.6949		ari: 0.6362		f1: 0.8012		
epoch: 016		acc: 0.8156		nmi: 0.6919		ari: 0.6321		f1: 0.7989		
epoch: 017		acc: 0.8124		nmi: 0.6887		ari: 0.6253		f1: 0.7965		
epoch: 018		acc: 0.8112		nmi: 0.6933		ari: 0.6219		f1: 0.7974		
epoch: 019		acc: 0.8089		nmi: 0.6935		ari: 0.6162		f1: 0.7965		
epoch: 020		acc: 0.8086		nmi: 0.6937		ari: 0.6154		f1: 0.7975		
epoch: 021		acc: 0.8069		nmi: 0.6906		ari: 0.6136		f1: 0.7947		
epoch: 022		acc: 0.8075		nmi: 0.6897		ari: 0.6138		f1: 0.7955		
epoch: 023		acc: 0.8099		nmi: 0.6903		ari: 0.6187		f1: 0.7973		
epoch: 024		acc: 0.8114		nmi: 0.6938		ari: 0.6204		f1: 0.7996		
epoch: 025		acc: 0.8097		nmi: 0.6898		ari: 0.6190		f1: 0.7951		
epoch: 026		acc: 0.8122		nmi: 0.6935		ari: 0.6225		f1: 0.7994		
epoch: 027		acc: 0.8122		nmi: 0.6936		ari: 0.6229		f1: 0.7990		
epoch: 028		acc: 0.8135		nmi: 0.6940		ari: 0.6247		f1: 0.8014		
epoch: 029		acc: 0.8107		nmi: 0.6918		ari: 0.6195		f1: 0.7980		
epoch: 030		acc: 0.8098		nmi: 0.6938		ari: 0.6178		f1: 0.7983		
epoch: 031		acc: 0.8123		nmi: 0.6961		ari: 0.6210		f1: 0.8019		
epoch: 032		acc: 0.8108		nmi: 0.6938		ari: 0.6192		f1: 0.7990		
epoch: 033		acc: 0.8082		nmi: 0.6896		ari: 0.6157		f1: 0.7958		
epoch: 034		acc: 0.8077		nmi: 0.6885		ari: 0.6140		f1: 0.7938		
epoch: 035		acc: 0.8098		nmi: 0.6921		ari: 0.6171		f1: 0.7978		
epoch: 036		acc: 0.8095		nmi: 0.6929		ari: 0.6167		f1: 0.7980		
epoch: 037		acc: 0.8119		nmi: 0.6933		ari: 0.6210		f1: 0.7999		
epoch: 038		acc: 0.8129		nmi: 0.6948		ari: 0.6230		f1: 0.8020		
epoch: 039		acc: 0.8122		nmi: 0.6965		ari: 0.6208		f1: 0.8014		
epoch: 040		acc: 0.8124		nmi: 0.6973		ari: 0.6204		f1: 0.8030		
epoch: 041		acc: 0.8108		nmi: 0.6947		ari: 0.6186		f1: 0.8001		
epoch: 042		acc: 0.8118		nmi: 0.6942		ari: 0.6202		f1: 0.8002		
epoch: 043		acc: 0.8122		nmi: 0.6945		ari: 0.6215		f1: 0.8003		
epoch: 044		acc: 0.8123		nmi: 0.6966		ari: 0.6203		f1: 0.8023		
epoch: 045		acc: 0.8107		nmi: 0.6945		ari: 0.6181		f1: 0.7999		
epoch: 046		acc: 0.8110		nmi: 0.6948		ari: 0.6187		f1: 0.8007		
epoch: 047		acc: 0.8119		nmi: 0.6963		ari: 0.6207		f1: 0.8014		
epoch: 048		acc: 0.8139		nmi: 0.6978		ari: 0.6238		f1: 0.8033		
epoch: 049		acc: 0.8128		nmi: 0.6947		ari: 0.6216		f1: 0.8025		
epoch: 050		acc: 0.8131		nmi: 0.6973		ari: 0.6224		f1: 0.8024		
The total number of parameters is: 0.517248M(1e6).
The max memory allocated to model is: 3666.66 MB.
Time consuming: 43.44s or 0.72m
****************************************Training loop No.8****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=745, out_features=512, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.8110		nmi: 0.6934		ari: 0.6194		f1: 0.7991		
epoch: 002		acc: 0.7923		nmi: 0.6728		ari: 0.5808		f1: 0.7835		
epoch: 003		acc: 0.7672		nmi: 0.6624		ari: 0.5518		f1: 0.7562		
epoch: 004		acc: 0.7969		nmi: 0.6853		ari: 0.5947		f1: 0.7884		
epoch: 005		acc: 0.8025		nmi: 0.6791		ari: 0.6047		f1: 0.7874		
epoch: 006		acc: 0.8230		nmi: 0.6919		ari: 0.6480		f1: 0.8039		
epoch: 007		acc: 0.8237		nmi: 0.6983		ari: 0.6471		f1: 0.8058		
epoch: 008		acc: 0.8101		nmi: 0.6923		ari: 0.6197		f1: 0.7961		
epoch: 009		acc: 0.8009		nmi: 0.6873		ari: 0.6016		f1: 0.7895		
epoch: 010		acc: 0.7950		nmi: 0.6855		ari: 0.5925		f1: 0.7881		
epoch: 011		acc: 0.7996		nmi: 0.6889		ari: 0.6008		f1: 0.7917		
epoch: 012		acc: 0.8054		nmi: 0.6888		ari: 0.6104		f1: 0.7938		
epoch: 013		acc: 0.8086		nmi: 0.6886		ari: 0.6167		f1: 0.7951		
epoch: 014		acc: 0.8140		nmi: 0.6918		ari: 0.6269		f1: 0.7996		
epoch: 015		acc: 0.8173		nmi: 0.6958		ari: 0.6339		f1: 0.8014		
epoch: 016		acc: 0.8193		nmi: 0.6962		ari: 0.6382		f1: 0.8032		
epoch: 017		acc: 0.8144		nmi: 0.6927		ari: 0.6280		f1: 0.8005		
epoch: 018		acc: 0.8110		nmi: 0.6933		ari: 0.6212		f1: 0.7974		
epoch: 019		acc: 0.8077		nmi: 0.6910		ari: 0.6148		f1: 0.7952		
epoch: 020		acc: 0.8077		nmi: 0.6917		ari: 0.6139		f1: 0.7972		
epoch: 021		acc: 0.8086		nmi: 0.6920		ari: 0.6161		f1: 0.7967		
epoch: 022		acc: 0.8082		nmi: 0.6910		ari: 0.6156		f1: 0.7965		
epoch: 023		acc: 0.8088		nmi: 0.6908		ari: 0.6165		f1: 0.7957		
epoch: 024		acc: 0.8077		nmi: 0.6889		ari: 0.6154		f1: 0.7943		
epoch: 025		acc: 0.8103		nmi: 0.6908		ari: 0.6208		f1: 0.7958		
epoch: 026		acc: 0.8110		nmi: 0.6895		ari: 0.6205		f1: 0.7973		
epoch: 027		acc: 0.8125		nmi: 0.6943		ari: 0.6235		f1: 0.8006		
epoch: 028		acc: 0.8125		nmi: 0.6940		ari: 0.6238		f1: 0.7998		
epoch: 029		acc: 0.8102		nmi: 0.6915		ari: 0.6185		f1: 0.7982		
epoch: 030		acc: 0.8092		nmi: 0.6919		ari: 0.6168		f1: 0.7967		
epoch: 031		acc: 0.8108		nmi: 0.6941		ari: 0.6193		f1: 0.7998		
epoch: 032		acc: 0.8088		nmi: 0.6906		ari: 0.6166		f1: 0.7958		
epoch: 033		acc: 0.8088		nmi: 0.6890		ari: 0.6166		f1: 0.7957		
epoch: 034		acc: 0.8123		nmi: 0.6966		ari: 0.6210		f1: 0.8014		
epoch: 035		acc: 0.8110		nmi: 0.6939		ari: 0.6196		f1: 0.7996		
epoch: 036		acc: 0.8114		nmi: 0.6941		ari: 0.6202		f1: 0.7996		
epoch: 037		acc: 0.8118		nmi: 0.6951		ari: 0.6207		f1: 0.8004		
epoch: 038		acc: 0.8119		nmi: 0.6943		ari: 0.6209		f1: 0.8009		
epoch: 039		acc: 0.8115		nmi: 0.6930		ari: 0.6204		f1: 0.7996		
epoch: 040		acc: 0.8106		nmi: 0.6937		ari: 0.6178		f1: 0.8001		
epoch: 041		acc: 0.8122		nmi: 0.6952		ari: 0.6200		f1: 0.8021		
epoch: 042		acc: 0.8122		nmi: 0.6948		ari: 0.6219		f1: 0.8000		
epoch: 043		acc: 0.8114		nmi: 0.6948		ari: 0.6201		f1: 0.7999		
epoch: 044		acc: 0.8107		nmi: 0.6945		ari: 0.6182		f1: 0.7999		
epoch: 045		acc: 0.8103		nmi: 0.6941		ari: 0.6171		f1: 0.8002		
epoch: 046		acc: 0.8114		nmi: 0.6948		ari: 0.6199		f1: 0.8001		
epoch: 047		acc: 0.8125		nmi: 0.6954		ari: 0.6207		f1: 0.8032		
epoch: 048		acc: 0.8140		nmi: 0.6979		ari: 0.6236		f1: 0.8040		
epoch: 049		acc: 0.8144		nmi: 0.6972		ari: 0.6248		f1: 0.8031		
epoch: 050		acc: 0.8137		nmi: 0.6973		ari: 0.6234		f1: 0.8034		
The total number of parameters is: 0.517248M(1e6).
The max memory allocated to model is: 3666.66 MB.
Time consuming: 43.38s or 0.72m
****************************************Training loop No.9****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=745, out_features=512, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.8129		nmi: 0.6954		ari: 0.6229		f1: 0.8014		
epoch: 002		acc: 0.7925		nmi: 0.6715		ari: 0.5813		f1: 0.7836		
epoch: 003		acc: 0.7675		nmi: 0.6626		ari: 0.5514		f1: 0.7568		
epoch: 004		acc: 0.7975		nmi: 0.6867		ari: 0.5958		f1: 0.7890		
epoch: 005		acc: 0.8037		nmi: 0.6798		ari: 0.6078		f1: 0.7880		
epoch: 006		acc: 0.8246		nmi: 0.6960		ari: 0.6506		f1: 0.8059		
epoch: 007		acc: 0.8224		nmi: 0.6959		ari: 0.6459		f1: 0.8049		
epoch: 008		acc: 0.8098		nmi: 0.6909		ari: 0.6176		f1: 0.7968		
epoch: 009		acc: 0.8022		nmi: 0.6916		ari: 0.6041		f1: 0.7919		
epoch: 010		acc: 0.7948		nmi: 0.6868		ari: 0.5917		f1: 0.7885		
epoch: 011		acc: 0.8003		nmi: 0.6883		ari: 0.6013		f1: 0.7914		
epoch: 012		acc: 0.8048		nmi: 0.6874		ari: 0.6100		f1: 0.7918		
epoch: 013		acc: 0.8089		nmi: 0.6901		ari: 0.6173		f1: 0.7952		
epoch: 014		acc: 0.8125		nmi: 0.6900		ari: 0.6240		f1: 0.7979		
epoch: 015		acc: 0.8173		nmi: 0.6950		ari: 0.6342		f1: 0.8010		
epoch: 016		acc: 0.8159		nmi: 0.6920		ari: 0.6320		f1: 0.7998		
epoch: 017		acc: 0.8152		nmi: 0.6934		ari: 0.6278		f1: 0.8024		
epoch: 018		acc: 0.8112		nmi: 0.6914		ari: 0.6205		f1: 0.7986		
epoch: 019		acc: 0.8071		nmi: 0.6898		ari: 0.6136		f1: 0.7947		
epoch: 020		acc: 0.8092		nmi: 0.6931		ari: 0.6173		f1: 0.7977		
epoch: 021		acc: 0.8086		nmi: 0.6923		ari: 0.6155		f1: 0.7973		
epoch: 022		acc: 0.8084		nmi: 0.6892		ari: 0.6153		f1: 0.7959		
epoch: 023		acc: 0.8105		nmi: 0.6926		ari: 0.6193		f1: 0.7976		
epoch: 024		acc: 0.8108		nmi: 0.6918		ari: 0.6202		f1: 0.7978		
epoch: 025		acc: 0.8123		nmi: 0.6932		ari: 0.6240		f1: 0.7976		
epoch: 026		acc: 0.8131		nmi: 0.6934		ari: 0.6241		f1: 0.8003		
epoch: 027		acc: 0.8132		nmi: 0.6952		ari: 0.6239		f1: 0.8019		
epoch: 028		acc: 0.8115		nmi: 0.6949		ari: 0.6209		f1: 0.7998		
epoch: 029		acc: 0.8102		nmi: 0.6928		ari: 0.6182		f1: 0.7989		
epoch: 030		acc: 0.8116		nmi: 0.6952		ari: 0.6198		f1: 0.8019		
epoch: 031		acc: 0.8110		nmi: 0.6964		ari: 0.6190		f1: 0.8007		
epoch: 032		acc: 0.8088		nmi: 0.6898		ari: 0.6157		f1: 0.7967		
epoch: 033		acc: 0.8084		nmi: 0.6879		ari: 0.6153		f1: 0.7955		
epoch: 034		acc: 0.8098		nmi: 0.6923		ari: 0.6174		f1: 0.7985		
epoch: 035		acc: 0.8097		nmi: 0.6930		ari: 0.6166		f1: 0.7994		
epoch: 036		acc: 0.8112		nmi: 0.6950		ari: 0.6201		f1: 0.7996		
epoch: 037		acc: 0.8128		nmi: 0.6961		ari: 0.6220		f1: 0.8023		
epoch: 038		acc: 0.8131		nmi: 0.6968		ari: 0.6222		f1: 0.8028		
epoch: 039		acc: 0.8118		nmi: 0.6954		ari: 0.6196		f1: 0.8020		
epoch: 040		acc: 0.8115		nmi: 0.6953		ari: 0.6198		f1: 0.8007		
epoch: 041		acc: 0.8111		nmi: 0.6930		ari: 0.6203		f1: 0.7992		
epoch: 042		acc: 0.8114		nmi: 0.6936		ari: 0.6196		f1: 0.7999		
epoch: 043		acc: 0.8093		nmi: 0.6910		ari: 0.6153		f1: 0.7980		
epoch: 044		acc: 0.8115		nmi: 0.6956		ari: 0.6200		f1: 0.8007		
epoch: 045		acc: 0.8105		nmi: 0.6940		ari: 0.6185		f1: 0.7991		
epoch: 046		acc: 0.8136		nmi: 0.6994		ari: 0.6242		f1: 0.8028		
epoch: 047		acc: 0.8140		nmi: 0.6970		ari: 0.6237		f1: 0.8040		
epoch: 048		acc: 0.8136		nmi: 0.6982		ari: 0.6225		f1: 0.8041		
epoch: 049		acc: 0.8132		nmi: 0.6975		ari: 0.6226		f1: 0.8022		
epoch: 050		acc: 0.8127		nmi: 0.6970		ari: 0.6223		f1: 0.8008		
The total number of parameters is: 0.517248M(1e6).
The max memory allocated to model is: 3666.66 MB.
Time consuming: 43.59s or 0.73m
****************************************Training loop No.10****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=745, out_features=512, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.8118		nmi: 0.6950		ari: 0.6215		f1: 0.7997		
epoch: 002		acc: 0.7911		nmi: 0.6723		ari: 0.5799		f1: 0.7811		
epoch: 003		acc: 0.7654		nmi: 0.6586		ari: 0.5490		f1: 0.7545		
epoch: 004		acc: 0.7979		nmi: 0.6860		ari: 0.5971		f1: 0.7884		
epoch: 005		acc: 0.8014		nmi: 0.6759		ari: 0.6026		f1: 0.7863		
epoch: 006		acc: 0.8243		nmi: 0.6949		ari: 0.6507		f1: 0.8050		
epoch: 007		acc: 0.8244		nmi: 0.6973		ari: 0.6486		f1: 0.8074		
epoch: 008		acc: 0.8085		nmi: 0.6895		ari: 0.6169		f1: 0.7945		
epoch: 009		acc: 0.8014		nmi: 0.6898		ari: 0.6026		f1: 0.7907		
epoch: 010		acc: 0.7916		nmi: 0.6815		ari: 0.5865		f1: 0.7851		
epoch: 011		acc: 0.7999		nmi: 0.6885		ari: 0.6008		f1: 0.7914		
epoch: 012		acc: 0.8064		nmi: 0.6896		ari: 0.6121		f1: 0.7951		
epoch: 013		acc: 0.8080		nmi: 0.6894		ari: 0.6162		f1: 0.7942		
epoch: 014		acc: 0.8156		nmi: 0.6944		ari: 0.6306		f1: 0.7995		
epoch: 015		acc: 0.8184		nmi: 0.6938		ari: 0.6376		f1: 0.8002		
epoch: 016		acc: 0.8173		nmi: 0.6928		ari: 0.6342		f1: 0.8015		
epoch: 017		acc: 0.8149		nmi: 0.6946		ari: 0.6289		f1: 0.8005		
epoch: 018		acc: 0.8105		nmi: 0.6925		ari: 0.6210		f1: 0.7961		
epoch: 019		acc: 0.8082		nmi: 0.6903		ari: 0.6156		f1: 0.7954		
epoch: 020		acc: 0.8099		nmi: 0.6943		ari: 0.6172		f1: 0.8002		
epoch: 021		acc: 0.8085		nmi: 0.6910		ari: 0.6153		f1: 0.7974		
epoch: 022		acc: 0.8101		nmi: 0.6919		ari: 0.6182		f1: 0.7987		
epoch: 023		acc: 0.8081		nmi: 0.6880		ari: 0.6152		f1: 0.7953		
epoch: 024		acc: 0.8107		nmi: 0.6917		ari: 0.6197		f1: 0.7977		
epoch: 025		acc: 0.8089		nmi: 0.6884		ari: 0.6171		f1: 0.7956		
epoch: 026		acc: 0.8111		nmi: 0.6920		ari: 0.6209		f1: 0.7988		
epoch: 027		acc: 0.8139		nmi: 0.6949		ari: 0.6257		f1: 0.8018		
epoch: 028		acc: 0.8107		nmi: 0.6907		ari: 0.6204		f1: 0.7983		
epoch: 029		acc: 0.8106		nmi: 0.6926		ari: 0.6188		f1: 0.7993		
epoch: 030		acc: 0.8112		nmi: 0.6938		ari: 0.6194		f1: 0.8008		
epoch: 031		acc: 0.8077		nmi: 0.6886		ari: 0.6136		f1: 0.7969		
epoch: 032		acc: 0.8101		nmi: 0.6922		ari: 0.6181		f1: 0.7979		
epoch: 033		acc: 0.8099		nmi: 0.6932		ari: 0.6178		f1: 0.7977		
epoch: 034		acc: 0.8093		nmi: 0.6907		ari: 0.6162		f1: 0.7978		
epoch: 035		acc: 0.8086		nmi: 0.6888		ari: 0.6151		f1: 0.7967		
epoch: 036		acc: 0.8101		nmi: 0.6908		ari: 0.6178		f1: 0.7980		
epoch: 037		acc: 0.8086		nmi: 0.6896		ari: 0.6161		f1: 0.7962		
epoch: 038		acc: 0.8120		nmi: 0.6950		ari: 0.6208		f1: 0.8012		
epoch: 039		acc: 0.8112		nmi: 0.6927		ari: 0.6195		f1: 0.8002		
epoch: 040		acc: 0.8132		nmi: 0.6987		ari: 0.6224		f1: 0.8029		
epoch: 041		acc: 0.8112		nmi: 0.6933		ari: 0.6195		f1: 0.8005		
epoch: 042		acc: 0.8118		nmi: 0.6964		ari: 0.6208		f1: 0.8009		
epoch: 043		acc: 0.8127		nmi: 0.6964		ari: 0.6210		f1: 0.8025		
epoch: 044		acc: 0.8123		nmi: 0.6977		ari: 0.6210		f1: 0.8015		
epoch: 045		acc: 0.8105		nmi: 0.6943		ari: 0.6181		f1: 0.7997		
epoch: 046		acc: 0.8132		nmi: 0.6979		ari: 0.6217		f1: 0.8041		
epoch: 047		acc: 0.8120		nmi: 0.6957		ari: 0.6210		f1: 0.8015		
epoch: 048		acc: 0.8131		nmi: 0.6969		ari: 0.6221		f1: 0.8035		
epoch: 049		acc: 0.8156		nmi: 0.7007		ari: 0.6270		f1: 0.8046		
epoch: 050		acc: 0.8128		nmi: 0.6949		ari: 0.6220		f1: 0.8014		
The total number of parameters is: 0.517248M(1e6).
The max memory allocated to model is: 3666.66 MB.
Time consuming: 43.62s or 0.73m
Namespace(is_pretrain=False, plot_clustering_tsne=False, plot_embedding_heatmap=False, adj_norm=False, adj_loop=True, adj_symmetric=True, desc='default', model_name='SYNC', dataset_name='amap', root=None, k=None, t=None, loops=10, feature_type='tensor', label_type='npy', adj_type='tensor', seed=325, epsilon=0.0, device='cuda', clusters=8, nodes=7650, lr=0.0001, max_epoch=50, pretrain_lr=0.001, pretrain_epoch=30, input_dim=745, log_save_path='./logs/SYNC/amap/', dataset_path='../data/', clustering_tsne_save_path='./img/clustering/SYNC/amap/', embedding_heatmap_save_path='./img/heatmap/SYNC/amap/', pretrain_save_path='./pretrain/pretrain_tigae/SYNC/amap/', hidden_dim=256, embedding_dim=16, linear_dim=512, beta=1)
Total loops: 10
****************************************Mean value:****************************************
acc: 0.8246±0.0007		nmi: 0.6972±0.0017		ari: 0.6499±0.0014		f1: 0.8064±0.0015
Training over! Punch out!
Loading uat dataset from local
****************************************Training loop No.1****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=239, out_features=128, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.5580		nmi: 0.2749		ari: 0.2456		f1: 0.5637		
epoch: 002		acc: 0.5639		nmi: 0.2788		ari: 0.2473		f1: 0.5716		
epoch: 003		acc: 0.5689		nmi: 0.2844		ari: 0.2609		f1: 0.5718		
epoch: 004		acc: 0.5672		nmi: 0.2821		ari: 0.2588		f1: 0.5696		
epoch: 005		acc: 0.5630		nmi: 0.2771		ari: 0.2564		f1: 0.5641		
epoch: 006		acc: 0.5664		nmi: 0.2815		ari: 0.2604		f1: 0.5677		
epoch: 007		acc: 0.5689		nmi: 0.2828		ari: 0.2601		f1: 0.5707		
epoch: 008		acc: 0.5630		nmi: 0.2789		ari: 0.2562		f1: 0.5638		
epoch: 009		acc: 0.5647		nmi: 0.2757		ari: 0.2549		f1: 0.5663		
epoch: 010		acc: 0.5630		nmi: 0.2773		ari: 0.2534		f1: 0.5649		
epoch: 011		acc: 0.5655		nmi: 0.2812		ari: 0.2584		f1: 0.5670		
epoch: 012		acc: 0.5613		nmi: 0.2778		ari: 0.2539		f1: 0.5624		
epoch: 013		acc: 0.5672		nmi: 0.2824		ari: 0.2601		f1: 0.5674		
epoch: 014		acc: 0.5748		nmi: 0.2859		ari: 0.2679		f1: 0.5742		
epoch: 015		acc: 0.5723		nmi: 0.2809		ari: 0.2626		f1: 0.5716		
epoch: 016		acc: 0.5689		nmi: 0.2773		ari: 0.2590		f1: 0.5676		
epoch: 017		acc: 0.5681		nmi: 0.2802		ari: 0.2609		f1: 0.5668		
epoch: 018		acc: 0.5689		nmi: 0.2808		ari: 0.2607		f1: 0.5670		
epoch: 019		acc: 0.5681		nmi: 0.2790		ari: 0.2591		f1: 0.5668		
epoch: 020		acc: 0.5647		nmi: 0.2755		ari: 0.2568		f1: 0.5632		
epoch: 021		acc: 0.5672		nmi: 0.2765		ari: 0.2579		f1: 0.5651		
epoch: 022		acc: 0.5655		nmi: 0.2803		ari: 0.2592		f1: 0.5646		
epoch: 023		acc: 0.5655		nmi: 0.2742		ari: 0.2547		f1: 0.5638		
epoch: 024		acc: 0.5672		nmi: 0.2729		ari: 0.2548		f1: 0.5651		
epoch: 025		acc: 0.5622		nmi: 0.2743		ari: 0.2536		f1: 0.5603		
epoch: 026		acc: 0.5672		nmi: 0.2764		ari: 0.2576		f1: 0.5649		
epoch: 027		acc: 0.5639		nmi: 0.2728		ari: 0.2527		f1: 0.5609		
epoch: 028		acc: 0.5681		nmi: 0.2763		ari: 0.2579		f1: 0.5644		
epoch: 029		acc: 0.5706		nmi: 0.2756		ari: 0.2589		f1: 0.5669		
epoch: 030		acc: 0.5630		nmi: 0.2678		ari: 0.2493		f1: 0.5593		
epoch: 031		acc: 0.5697		nmi: 0.2789		ari: 0.2617		f1: 0.5655		
epoch: 032		acc: 0.5664		nmi: 0.2763		ari: 0.2574		f1: 0.5627		
epoch: 033		acc: 0.5672		nmi: 0.2716		ari: 0.2527		f1: 0.5646		
epoch: 034		acc: 0.5664		nmi: 0.2754		ari: 0.2575		f1: 0.5623		
epoch: 035		acc: 0.5639		nmi: 0.2678		ari: 0.2510		f1: 0.5605		
epoch: 036		acc: 0.5639		nmi: 0.2700		ari: 0.2515		f1: 0.5615		
epoch: 037		acc: 0.5630		nmi: 0.2682		ari: 0.2488		f1: 0.5591		
epoch: 038		acc: 0.5655		nmi: 0.2748		ari: 0.2544		f1: 0.5619		
epoch: 039		acc: 0.5655		nmi: 0.2743		ari: 0.2559		f1: 0.5614		
epoch: 040		acc: 0.5622		nmi: 0.2711		ari: 0.2508		f1: 0.5588		
epoch: 041		acc: 0.5647		nmi: 0.2731		ari: 0.2542		f1: 0.5609		
epoch: 042		acc: 0.5639		nmi: 0.2690		ari: 0.2507		f1: 0.5602		
epoch: 043		acc: 0.5639		nmi: 0.2703		ari: 0.2525		f1: 0.5595		
epoch: 044		acc: 0.5689		nmi: 0.2763		ari: 0.2593		f1: 0.5652		
epoch: 045		acc: 0.5630		nmi: 0.2690		ari: 0.2495		f1: 0.5596		
epoch: 046		acc: 0.5588		nmi: 0.2662		ari: 0.2461		f1: 0.5553		
epoch: 047		acc: 0.5697		nmi: 0.2736		ari: 0.2566		f1: 0.5657		
epoch: 048		acc: 0.5672		nmi: 0.2744		ari: 0.2550		f1: 0.5640		
epoch: 049		acc: 0.5613		nmi: 0.2691		ari: 0.2490		f1: 0.5578		
epoch: 050		acc: 0.5664		nmi: 0.2752		ari: 0.2563		f1: 0.5628		
The total number of parameters is: 0.067648M(1e6).
The max memory allocated to model is: 106.84 MB.
Time consuming: 3.68s or 0.06m
****************************************Training loop No.2****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=239, out_features=128, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.5630		nmi: 0.2757		ari: 0.2500		f1: 0.5686		
epoch: 002		acc: 0.5622		nmi: 0.2858		ari: 0.2519		f1: 0.5690		
epoch: 003		acc: 0.5588		nmi: 0.2732		ari: 0.2463		f1: 0.5634		
epoch: 004		acc: 0.5672		nmi: 0.2860		ari: 0.2618		f1: 0.5696		
epoch: 005		acc: 0.5647		nmi: 0.2811		ari: 0.2588		f1: 0.5669		
epoch: 006		acc: 0.5672		nmi: 0.2830		ari: 0.2613		f1: 0.5680		
epoch: 007		acc: 0.5689		nmi: 0.2769		ari: 0.2582		f1: 0.5700		
epoch: 008		acc: 0.5605		nmi: 0.2737		ari: 0.2534		f1: 0.5617		
epoch: 009		acc: 0.5706		nmi: 0.2841		ari: 0.2629		f1: 0.5727		
epoch: 010		acc: 0.5672		nmi: 0.2831		ari: 0.2614		f1: 0.5687		
epoch: 011		acc: 0.5672		nmi: 0.2799		ari: 0.2595		f1: 0.5684		
epoch: 012		acc: 0.5681		nmi: 0.2838		ari: 0.2610		f1: 0.5696		
epoch: 013		acc: 0.5613		nmi: 0.2737		ari: 0.2524		f1: 0.5617		
epoch: 014		acc: 0.5664		nmi: 0.2763		ari: 0.2564		f1: 0.5668		
epoch: 015		acc: 0.5664		nmi: 0.2808		ari: 0.2612		f1: 0.5646		
epoch: 016		acc: 0.5689		nmi: 0.2737		ari: 0.2559		f1: 0.5679		
epoch: 017		acc: 0.5689		nmi: 0.2826		ari: 0.2634		f1: 0.5676		
epoch: 018		acc: 0.5647		nmi: 0.2731		ari: 0.2537		f1: 0.5637		
epoch: 019		acc: 0.5681		nmi: 0.2784		ari: 0.2596		f1: 0.5671		
epoch: 020		acc: 0.5655		nmi: 0.2797		ari: 0.2602		f1: 0.5640		
epoch: 021		acc: 0.5639		nmi: 0.2751		ari: 0.2558		f1: 0.5617		
epoch: 022		acc: 0.5672		nmi: 0.2818		ari: 0.2614		f1: 0.5652		
epoch: 023		acc: 0.5689		nmi: 0.2787		ari: 0.2600		f1: 0.5672		
epoch: 024		acc: 0.5655		nmi: 0.2757		ari: 0.2561		f1: 0.5641		
epoch: 025		acc: 0.5655		nmi: 0.2736		ari: 0.2540		f1: 0.5631		
epoch: 026		acc: 0.5697		nmi: 0.2767		ari: 0.2594		f1: 0.5667		
epoch: 027		acc: 0.5697		nmi: 0.2773		ari: 0.2597		f1: 0.5666		
epoch: 028		acc: 0.5655		nmi: 0.2762		ari: 0.2574		f1: 0.5625		
epoch: 029		acc: 0.5622		nmi: 0.2713		ari: 0.2514		f1: 0.5596		
epoch: 030		acc: 0.5664		nmi: 0.2729		ari: 0.2536		f1: 0.5641		
epoch: 031		acc: 0.5655		nmi: 0.2723		ari: 0.2530		f1: 0.5623		
epoch: 032		acc: 0.5639		nmi: 0.2722		ari: 0.2537		f1: 0.5604		
epoch: 033		acc: 0.5672		nmi: 0.2783		ari: 0.2571		f1: 0.5642		
epoch: 034		acc: 0.5647		nmi: 0.2706		ari: 0.2513		f1: 0.5620		
epoch: 035		acc: 0.5664		nmi: 0.2738		ari: 0.2557		f1: 0.5623		
epoch: 036		acc: 0.5664		nmi: 0.2715		ari: 0.2538		f1: 0.5626		
epoch: 037		acc: 0.5630		nmi: 0.2709		ari: 0.2520		f1: 0.5593		
epoch: 038		acc: 0.5672		nmi: 0.2772		ari: 0.2576		f1: 0.5633		
epoch: 039		acc: 0.5630		nmi: 0.2696		ari: 0.2502		f1: 0.5594		
epoch: 040		acc: 0.5647		nmi: 0.2704		ari: 0.2511		f1: 0.5617		
epoch: 041		acc: 0.5639		nmi: 0.2682		ari: 0.2503		f1: 0.5598		
epoch: 042		acc: 0.5655		nmi: 0.2705		ari: 0.2532		f1: 0.5617		
epoch: 043		acc: 0.5664		nmi: 0.2715		ari: 0.2523		f1: 0.5634		
epoch: 044		acc: 0.5672		nmi: 0.2747		ari: 0.2555		f1: 0.5641		
epoch: 045		acc: 0.5689		nmi: 0.2788		ari: 0.2590		f1: 0.5650		
epoch: 046		acc: 0.5664		nmi: 0.2718		ari: 0.2536		f1: 0.5625		
epoch: 047		acc: 0.5605		nmi: 0.2658		ari: 0.2468		f1: 0.5574		
epoch: 048		acc: 0.5672		nmi: 0.2712		ari: 0.2539		f1: 0.5634		
epoch: 049		acc: 0.5622		nmi: 0.2690		ari: 0.2497		f1: 0.5591		
epoch: 050		acc: 0.5630		nmi: 0.2727		ari: 0.2532		f1: 0.5597		
The total number of parameters is: 0.067648M(1e6).
The max memory allocated to model is: 106.97 MB.
Time consuming: 0.94s or 0.02m
****************************************Training loop No.3****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=239, out_features=128, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.5605		nmi: 0.2812		ari: 0.2515		f1: 0.5660		
epoch: 002		acc: 0.5563		nmi: 0.2692		ari: 0.2357		f1: 0.5647		
epoch: 003		acc: 0.5639		nmi: 0.2829		ari: 0.2535		f1: 0.5688		
epoch: 004		acc: 0.5647		nmi: 0.2843		ari: 0.2555		f1: 0.5686		
epoch: 005		acc: 0.5647		nmi: 0.2791		ari: 0.2574		f1: 0.5667		
epoch: 006		acc: 0.5655		nmi: 0.2790		ari: 0.2580		f1: 0.5672		
epoch: 007		acc: 0.5647		nmi: 0.2806		ari: 0.2587		f1: 0.5660		
epoch: 008		acc: 0.5639		nmi: 0.2822		ari: 0.2573		f1: 0.5666		
epoch: 009		acc: 0.5605		nmi: 0.2759		ari: 0.2514		f1: 0.5624		
epoch: 010		acc: 0.5731		nmi: 0.2906		ari: 0.2677		f1: 0.5751		
epoch: 011		acc: 0.5723		nmi: 0.2889		ari: 0.2657		f1: 0.5740		
epoch: 012		acc: 0.5731		nmi: 0.2861		ari: 0.2641		f1: 0.5747		
epoch: 013		acc: 0.5664		nmi: 0.2792		ari: 0.2563		f1: 0.5681		
epoch: 014		acc: 0.5639		nmi: 0.2791		ari: 0.2581		f1: 0.5643		
epoch: 015		acc: 0.5630		nmi: 0.2731		ari: 0.2536		f1: 0.5632		
epoch: 016		acc: 0.5672		nmi: 0.2764		ari: 0.2581		f1: 0.5660		
epoch: 017		acc: 0.5689		nmi: 0.2833		ari: 0.2624		f1: 0.5683		
epoch: 018		acc: 0.5655		nmi: 0.2783		ari: 0.2595		f1: 0.5635		
epoch: 019		acc: 0.5672		nmi: 0.2766		ari: 0.2561		f1: 0.5661		
epoch: 020		acc: 0.5664		nmi: 0.2810		ari: 0.2598		f1: 0.5653		
epoch: 021		acc: 0.5664		nmi: 0.2792		ari: 0.2562		f1: 0.5670		
epoch: 022		acc: 0.5697		nmi: 0.2795		ari: 0.2593		f1: 0.5686		
epoch: 023		acc: 0.5664		nmi: 0.2741		ari: 0.2546		f1: 0.5651		
epoch: 024		acc: 0.5681		nmi: 0.2788		ari: 0.2594		f1: 0.5665		
epoch: 025		acc: 0.5622		nmi: 0.2726		ari: 0.2535		f1: 0.5604		
epoch: 026		acc: 0.5613		nmi: 0.2686		ari: 0.2496		f1: 0.5586		
epoch: 027		acc: 0.5689		nmi: 0.2806		ari: 0.2598		f1: 0.5657		
epoch: 028		acc: 0.5639		nmi: 0.2719		ari: 0.2510		f1: 0.5623		
epoch: 029		acc: 0.5672		nmi: 0.2732		ari: 0.2556		f1: 0.5636		
epoch: 030		acc: 0.5664		nmi: 0.2748		ari: 0.2566		f1: 0.5630		
epoch: 031		acc: 0.5647		nmi: 0.2753		ari: 0.2556		f1: 0.5616		
epoch: 032		acc: 0.5672		nmi: 0.2751		ari: 0.2554		f1: 0.5643		
epoch: 033		acc: 0.5630		nmi: 0.2722		ari: 0.2544		f1: 0.5593		
epoch: 034		acc: 0.5664		nmi: 0.2720		ari: 0.2529		f1: 0.5632		
epoch: 035		acc: 0.5672		nmi: 0.2755		ari: 0.2575		f1: 0.5640		
epoch: 036		acc: 0.5613		nmi: 0.2667		ari: 0.2477		f1: 0.5584		
epoch: 037		acc: 0.5681		nmi: 0.2780		ari: 0.2584		f1: 0.5646		
epoch: 038		acc: 0.5622		nmi: 0.2720		ari: 0.2513		f1: 0.5589		
epoch: 039		acc: 0.5630		nmi: 0.2665		ari: 0.2483		f1: 0.5599		
epoch: 040		acc: 0.5664		nmi: 0.2741		ari: 0.2545		f1: 0.5632		
epoch: 041		acc: 0.5655		nmi: 0.2710		ari: 0.2530		f1: 0.5614		
epoch: 042		acc: 0.5622		nmi: 0.2695		ari: 0.2482		f1: 0.5594		
epoch: 043		acc: 0.5672		nmi: 0.2706		ari: 0.2537		f1: 0.5632		
epoch: 044		acc: 0.5689		nmi: 0.2761		ari: 0.2575		f1: 0.5653		
epoch: 045		acc: 0.5647		nmi: 0.2717		ari: 0.2526		f1: 0.5612		
epoch: 046		acc: 0.5639		nmi: 0.2700		ari: 0.2521		f1: 0.5601		
epoch: 047		acc: 0.5647		nmi: 0.2730		ari: 0.2544		f1: 0.5606		
epoch: 048		acc: 0.5672		nmi: 0.2740		ari: 0.2558		f1: 0.5637		
epoch: 049		acc: 0.5681		nmi: 0.2717		ari: 0.2549		f1: 0.5641		
epoch: 050		acc: 0.5681		nmi: 0.2745		ari: 0.2580		f1: 0.5640		
The total number of parameters is: 0.067648M(1e6).
The max memory allocated to model is: 106.97 MB.
Time consuming: 0.87s or 0.01m
****************************************Training loop No.4****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=239, out_features=128, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.5647		nmi: 0.2816		ari: 0.2528		f1: 0.5708		
epoch: 002		acc: 0.5622		nmi: 0.2790		ari: 0.2460		f1: 0.5693		
epoch: 003		acc: 0.5723		nmi: 0.2896		ari: 0.2614		f1: 0.5774		
epoch: 004		acc: 0.5664		nmi: 0.2787		ari: 0.2575		f1: 0.5682		
epoch: 005		acc: 0.5613		nmi: 0.2774		ari: 0.2554		f1: 0.5635		
epoch: 006		acc: 0.5706		nmi: 0.2829		ari: 0.2634		f1: 0.5714		
epoch: 007		acc: 0.5739		nmi: 0.2857		ari: 0.2675		f1: 0.5744		
epoch: 008		acc: 0.5689		nmi: 0.2815		ari: 0.2600		f1: 0.5707		
epoch: 009		acc: 0.5672		nmi: 0.2838		ari: 0.2609		f1: 0.5687		
epoch: 010		acc: 0.5706		nmi: 0.2896		ari: 0.2659		f1: 0.5717		
epoch: 011		acc: 0.5664		nmi: 0.2785		ari: 0.2581		f1: 0.5674		
epoch: 012		acc: 0.5706		nmi: 0.2799		ari: 0.2601		f1: 0.5720		
epoch: 013		acc: 0.5697		nmi: 0.2818		ari: 0.2616		f1: 0.5707		
epoch: 014		acc: 0.5689		nmi: 0.2845		ari: 0.2616		f1: 0.5695		
epoch: 015		acc: 0.5697		nmi: 0.2862		ari: 0.2650		f1: 0.5687		
epoch: 016		acc: 0.5672		nmi: 0.2771		ari: 0.2580		f1: 0.5662		
epoch: 017		acc: 0.5714		nmi: 0.2873		ari: 0.2674		f1: 0.5709		
epoch: 018		acc: 0.5647		nmi: 0.2726		ari: 0.2539		f1: 0.5634		
epoch: 019		acc: 0.5655		nmi: 0.2751		ari: 0.2553		f1: 0.5650		
epoch: 020		acc: 0.5706		nmi: 0.2824		ari: 0.2623		f1: 0.5697		
epoch: 021		acc: 0.5664		nmi: 0.2814		ari: 0.2608		f1: 0.5647		
epoch: 022		acc: 0.5689		nmi: 0.2779		ari: 0.2572		f1: 0.5679		
epoch: 023		acc: 0.5622		nmi: 0.2751		ari: 0.2542		f1: 0.5626		
epoch: 024		acc: 0.5664		nmi: 0.2820		ari: 0.2603		f1: 0.5643		
epoch: 025		acc: 0.5622		nmi: 0.2701		ari: 0.2520		f1: 0.5598		
epoch: 026		acc: 0.5689		nmi: 0.2797		ari: 0.2628		f1: 0.5662		
epoch: 027		acc: 0.5681		nmi: 0.2755		ari: 0.2575		f1: 0.5646		
epoch: 028		acc: 0.5630		nmi: 0.2733		ari: 0.2526		f1: 0.5605		
epoch: 029		acc: 0.5639		nmi: 0.2700		ari: 0.2512		f1: 0.5604		
epoch: 030		acc: 0.5613		nmi: 0.2693		ari: 0.2497		f1: 0.5584		
epoch: 031		acc: 0.5613		nmi: 0.2696		ari: 0.2493		f1: 0.5585		
epoch: 032		acc: 0.5630		nmi: 0.2714		ari: 0.2543		f1: 0.5592		
epoch: 033		acc: 0.5639		nmi: 0.2708		ari: 0.2506		f1: 0.5608		
epoch: 034		acc: 0.5647		nmi: 0.2720		ari: 0.2525		f1: 0.5616		
epoch: 035		acc: 0.5630		nmi: 0.2676		ari: 0.2492		f1: 0.5595		
epoch: 036		acc: 0.5630		nmi: 0.2726		ari: 0.2534		f1: 0.5599		
epoch: 037		acc: 0.5639		nmi: 0.2749		ari: 0.2533		f1: 0.5607		
epoch: 038		acc: 0.5655		nmi: 0.2725		ari: 0.2533		f1: 0.5625		
epoch: 039		acc: 0.5647		nmi: 0.2712		ari: 0.2512		f1: 0.5618		
epoch: 040		acc: 0.5647		nmi: 0.2731		ari: 0.2546		f1: 0.5608		
epoch: 041		acc: 0.5588		nmi: 0.2667		ari: 0.2474		f1: 0.5555		
epoch: 042		acc: 0.5613		nmi: 0.2687		ari: 0.2491		f1: 0.5583		
epoch: 043		acc: 0.5672		nmi: 0.2760		ari: 0.2575		f1: 0.5636		
epoch: 044		acc: 0.5613		nmi: 0.2694		ari: 0.2492		f1: 0.5582		
epoch: 045		acc: 0.5639		nmi: 0.2718		ari: 0.2526		f1: 0.5602		
epoch: 046		acc: 0.5605		nmi: 0.2684		ari: 0.2496		f1: 0.5572		
epoch: 047		acc: 0.5664		nmi: 0.2746		ari: 0.2549		f1: 0.5628		
epoch: 048		acc: 0.5639		nmi: 0.2709		ari: 0.2510		f1: 0.5602		
epoch: 049		acc: 0.5639		nmi: 0.2673		ari: 0.2501		f1: 0.5604		
epoch: 050		acc: 0.5622		nmi: 0.2684		ari: 0.2507		f1: 0.5582		
The total number of parameters is: 0.067648M(1e6).
The max memory allocated to model is: 106.97 MB.
Time consuming: 0.9s or 0.02m
****************************************Training loop No.5****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=239, out_features=128, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.5681		nmi: 0.2808		ari: 0.2554		f1: 0.5725		
epoch: 002		acc: 0.5613		nmi: 0.2748		ari: 0.2397		f1: 0.5694		
epoch: 003		acc: 0.5655		nmi: 0.2785		ari: 0.2523		f1: 0.5692		
epoch: 004		acc: 0.5689		nmi: 0.2841		ari: 0.2620		f1: 0.5707		
epoch: 005		acc: 0.5664		nmi: 0.2786		ari: 0.2586		f1: 0.5675		
epoch: 006		acc: 0.5681		nmi: 0.2844		ari: 0.2622		f1: 0.5689		
epoch: 007		acc: 0.5723		nmi: 0.2825		ari: 0.2632		f1: 0.5726		
epoch: 008		acc: 0.5689		nmi: 0.2832		ari: 0.2621		f1: 0.5702		
epoch: 009		acc: 0.5706		nmi: 0.2865		ari: 0.2629		f1: 0.5724		
epoch: 010		acc: 0.5655		nmi: 0.2777		ari: 0.2553		f1: 0.5671		
epoch: 011		acc: 0.5664		nmi: 0.2812		ari: 0.2600		f1: 0.5674		
epoch: 012		acc: 0.5647		nmi: 0.2832		ari: 0.2604		f1: 0.5656		
epoch: 013		acc: 0.5697		nmi: 0.2817		ari: 0.2611		f1: 0.5699		
epoch: 014		acc: 0.5723		nmi: 0.2862		ari: 0.2659		f1: 0.5714		
epoch: 015		acc: 0.5706		nmi: 0.2813		ari: 0.2631		f1: 0.5702		
epoch: 016		acc: 0.5681		nmi: 0.2787		ari: 0.2583		f1: 0.5674		
epoch: 017		acc: 0.5697		nmi: 0.2812		ari: 0.2625		f1: 0.5683		
epoch: 018		acc: 0.5630		nmi: 0.2686		ari: 0.2509		f1: 0.5619		
epoch: 019		acc: 0.5706		nmi: 0.2802		ari: 0.2619		f1: 0.5679		
epoch: 020		acc: 0.5672		nmi: 0.2796		ari: 0.2593		f1: 0.5655		
epoch: 021		acc: 0.5672		nmi: 0.2800		ari: 0.2605		f1: 0.5659		
epoch: 022		acc: 0.5630		nmi: 0.2732		ari: 0.2536		f1: 0.5612		
epoch: 023		acc: 0.5697		nmi: 0.2798		ari: 0.2614		f1: 0.5672		
epoch: 024		acc: 0.5655		nmi: 0.2759		ari: 0.2567		f1: 0.5630		
epoch: 025		acc: 0.5723		nmi: 0.2822		ari: 0.2639		f1: 0.5693		
epoch: 026		acc: 0.5672		nmi: 0.2779		ari: 0.2581		f1: 0.5643		
epoch: 027		acc: 0.5664		nmi: 0.2768		ari: 0.2585		f1: 0.5629		
epoch: 028		acc: 0.5681		nmi: 0.2802		ari: 0.2631		f1: 0.5647		
epoch: 029		acc: 0.5655		nmi: 0.2744		ari: 0.2554		f1: 0.5629		
epoch: 030		acc: 0.5672		nmi: 0.2759		ari: 0.2567		f1: 0.5642		
epoch: 031		acc: 0.5647		nmi: 0.2721		ari: 0.2545		f1: 0.5615		
epoch: 032		acc: 0.5630		nmi: 0.2744		ari: 0.2548		f1: 0.5596		
epoch: 033		acc: 0.5672		nmi: 0.2761		ari: 0.2583		f1: 0.5634		
epoch: 034		acc: 0.5697		nmi: 0.2793		ari: 0.2602		f1: 0.5662		
epoch: 035		acc: 0.5622		nmi: 0.2729		ari: 0.2532		f1: 0.5588		
epoch: 036		acc: 0.5731		nmi: 0.2817		ari: 0.2655		f1: 0.5686		
epoch: 037		acc: 0.5655		nmi: 0.2720		ari: 0.2531		f1: 0.5616		
epoch: 038		acc: 0.5647		nmi: 0.2735		ari: 0.2542		f1: 0.5601		
epoch: 039		acc: 0.5723		nmi: 0.2748		ari: 0.2589		f1: 0.5691		
epoch: 040		acc: 0.5630		nmi: 0.2701		ari: 0.2515		f1: 0.5589		
epoch: 041		acc: 0.5630		nmi: 0.2687		ari: 0.2492		f1: 0.5597		
epoch: 042		acc: 0.5689		nmi: 0.2738		ari: 0.2565		f1: 0.5645		
epoch: 043		acc: 0.5622		nmi: 0.2677		ari: 0.2489		f1: 0.5587		
epoch: 044		acc: 0.5597		nmi: 0.2669		ari: 0.2471		f1: 0.5564		
epoch: 045		acc: 0.5672		nmi: 0.2747		ari: 0.2576		f1: 0.5632		
epoch: 046		acc: 0.5664		nmi: 0.2760		ari: 0.2576		f1: 0.5624		
epoch: 047		acc: 0.5664		nmi: 0.2704		ari: 0.2523		f1: 0.5627		
epoch: 048		acc: 0.5630		nmi: 0.2704		ari: 0.2519		f1: 0.5593		
epoch: 049		acc: 0.5630		nmi: 0.2746		ari: 0.2547		f1: 0.5593		
epoch: 050		acc: 0.5664		nmi: 0.2739		ari: 0.2543		f1: 0.5624		
The total number of parameters is: 0.067648M(1e6).
The max memory allocated to model is: 106.97 MB.
Time consuming: 0.89s or 0.01m
****************************************Training loop No.6****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=239, out_features=128, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.5647		nmi: 0.2853		ari: 0.2550		f1: 0.5713		
epoch: 002		acc: 0.5605		nmi: 0.2774		ari: 0.2436		f1: 0.5682		
epoch: 003		acc: 0.5622		nmi: 0.2805		ari: 0.2510		f1: 0.5673		
epoch: 004		acc: 0.5664		nmi: 0.2801		ari: 0.2543		f1: 0.5697		
epoch: 005		acc: 0.5655		nmi: 0.2794		ari: 0.2581		f1: 0.5669		
epoch: 006		acc: 0.5613		nmi: 0.2738		ari: 0.2536		f1: 0.5619		
epoch: 007		acc: 0.5647		nmi: 0.2714		ari: 0.2518		f1: 0.5664		
epoch: 008		acc: 0.5731		nmi: 0.2847		ari: 0.2671		f1: 0.5741		
epoch: 009		acc: 0.5639		nmi: 0.2827		ari: 0.2590		f1: 0.5654		
epoch: 010		acc: 0.5655		nmi: 0.2764		ari: 0.2555		f1: 0.5674		
epoch: 011		acc: 0.5664		nmi: 0.2828		ari: 0.2578		f1: 0.5691		
epoch: 012		acc: 0.5739		nmi: 0.2896		ari: 0.2670		f1: 0.5755		
epoch: 013		acc: 0.5630		nmi: 0.2724		ari: 0.2511		f1: 0.5639		
epoch: 014		acc: 0.5664		nmi: 0.2790		ari: 0.2560		f1: 0.5681		
epoch: 015		acc: 0.5681		nmi: 0.2855		ari: 0.2638		f1: 0.5680		
epoch: 016		acc: 0.5689		nmi: 0.2800		ari: 0.2589		f1: 0.5684		
epoch: 017		acc: 0.5672		nmi: 0.2781		ari: 0.2594		f1: 0.5665		
epoch: 018		acc: 0.5697		nmi: 0.2850		ari: 0.2649		f1: 0.5684		
epoch: 019		acc: 0.5664		nmi: 0.2761		ari: 0.2549		f1: 0.5660		
epoch: 020		acc: 0.5664		nmi: 0.2743		ari: 0.2545		f1: 0.5652		
epoch: 021		acc: 0.5672		nmi: 0.2774		ari: 0.2589		f1: 0.5664		
epoch: 022		acc: 0.5697		nmi: 0.2808		ari: 0.2594		f1: 0.5687		
epoch: 023		acc: 0.5681		nmi: 0.2889		ari: 0.2647		f1: 0.5666		
epoch: 024		acc: 0.5664		nmi: 0.2773		ari: 0.2585		f1: 0.5635		
epoch: 025		acc: 0.5689		nmi: 0.2819		ari: 0.2613		f1: 0.5672		
epoch: 026		acc: 0.5681		nmi: 0.2765		ari: 0.2582		f1: 0.5651		
epoch: 027		acc: 0.5697		nmi: 0.2768		ari: 0.2584		f1: 0.5674		
epoch: 028		acc: 0.5639		nmi: 0.2693		ari: 0.2513		f1: 0.5610		
epoch: 029		acc: 0.5706		nmi: 0.2818		ari: 0.2629		f1: 0.5672		
epoch: 030		acc: 0.5664		nmi: 0.2748		ari: 0.2557		f1: 0.5631		
epoch: 031		acc: 0.5639		nmi: 0.2746		ari: 0.2561		f1: 0.5598		
epoch: 032		acc: 0.5681		nmi: 0.2754		ari: 0.2553		f1: 0.5648		
epoch: 033		acc: 0.5655		nmi: 0.2773		ari: 0.2570		f1: 0.5630		
epoch: 034		acc: 0.5672		nmi: 0.2768		ari: 0.2590		f1: 0.5632		
epoch: 035		acc: 0.5672		nmi: 0.2711		ari: 0.2533		f1: 0.5640		
epoch: 036		acc: 0.5672		nmi: 0.2788		ari: 0.2592		f1: 0.5636		
epoch: 037		acc: 0.5664		nmi: 0.2740		ari: 0.2560		f1: 0.5626		
epoch: 038		acc: 0.5664		nmi: 0.2704		ari: 0.2528		f1: 0.5625		
epoch: 039		acc: 0.5655		nmi: 0.2724		ari: 0.2547		f1: 0.5617		
epoch: 040		acc: 0.5647		nmi: 0.2744		ari: 0.2543		f1: 0.5612		
epoch: 041		acc: 0.5655		nmi: 0.2725		ari: 0.2523		f1: 0.5618		
epoch: 042		acc: 0.5672		nmi: 0.2717		ari: 0.2542		f1: 0.5631		
epoch: 043		acc: 0.5647		nmi: 0.2693		ari: 0.2514		f1: 0.5615		
epoch: 044		acc: 0.5613		nmi: 0.2667		ari: 0.2471		f1: 0.5577		
epoch: 045		acc: 0.5630		nmi: 0.2667		ari: 0.2486		f1: 0.5592		
epoch: 046		acc: 0.5613		nmi: 0.2684		ari: 0.2493		f1: 0.5580		
epoch: 047		acc: 0.5664		nmi: 0.2727		ari: 0.2558		f1: 0.5624		
epoch: 048		acc: 0.5689		nmi: 0.2753		ari: 0.2573		f1: 0.5655		
epoch: 049		acc: 0.5647		nmi: 0.2701		ari: 0.2521		f1: 0.5607		
epoch: 050		acc: 0.5689		nmi: 0.2734		ari: 0.2557		f1: 0.5651		
The total number of parameters is: 0.067648M(1e6).
The max memory allocated to model is: 106.97 MB.
Time consuming: 0.89s or 0.01m
****************************************Training loop No.7****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=239, out_features=128, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.5647		nmi: 0.2795		ari: 0.2504		f1: 0.5698		
epoch: 002		acc: 0.5613		nmi: 0.2858		ari: 0.2477		f1: 0.5694		
epoch: 003		acc: 0.5605		nmi: 0.2800		ari: 0.2525		f1: 0.5644		
epoch: 004		acc: 0.5723		nmi: 0.2845		ari: 0.2638		f1: 0.5738		
epoch: 005		acc: 0.5672		nmi: 0.2831		ari: 0.2599		f1: 0.5682		
epoch: 006		acc: 0.5664		nmi: 0.2786		ari: 0.2570		f1: 0.5685		
epoch: 007		acc: 0.5639		nmi: 0.2808		ari: 0.2592		f1: 0.5649		
epoch: 008		acc: 0.5672		nmi: 0.2874		ari: 0.2646		f1: 0.5690		
epoch: 009		acc: 0.5672		nmi: 0.2847		ari: 0.2608		f1: 0.5684		
epoch: 010		acc: 0.5697		nmi: 0.2876		ari: 0.2651		f1: 0.5713		
epoch: 011		acc: 0.5672		nmi: 0.2810		ari: 0.2587		f1: 0.5689		
epoch: 012		acc: 0.5647		nmi: 0.2816		ari: 0.2594		f1: 0.5653		
epoch: 013		acc: 0.5672		nmi: 0.2871		ari: 0.2638		f1: 0.5690		
epoch: 014		acc: 0.5655		nmi: 0.2757		ari: 0.2580		f1: 0.5648		
epoch: 015		acc: 0.5647		nmi: 0.2790		ari: 0.2585		f1: 0.5648		
epoch: 016		acc: 0.5689		nmi: 0.2821		ari: 0.2615		f1: 0.5681		
epoch: 017		acc: 0.5664		nmi: 0.2812		ari: 0.2620		f1: 0.5643		
epoch: 018		acc: 0.5639		nmi: 0.2742		ari: 0.2543		f1: 0.5625		
epoch: 019		acc: 0.5697		nmi: 0.2843		ari: 0.2633		f1: 0.5684		
epoch: 020		acc: 0.5714		nmi: 0.2858		ari: 0.2667		f1: 0.5698		
epoch: 021		acc: 0.5706		nmi: 0.2805		ari: 0.2628		f1: 0.5680		
epoch: 022		acc: 0.5689		nmi: 0.2783		ari: 0.2596		f1: 0.5670		
epoch: 023		acc: 0.5697		nmi: 0.2838		ari: 0.2625		f1: 0.5678		
epoch: 024		acc: 0.5655		nmi: 0.2794		ari: 0.2574		f1: 0.5637		
epoch: 025		acc: 0.5647		nmi: 0.2765		ari: 0.2562		f1: 0.5617		
epoch: 026		acc: 0.5647		nmi: 0.2761		ari: 0.2564		f1: 0.5627		
epoch: 027		acc: 0.5639		nmi: 0.2731		ari: 0.2547		f1: 0.5606		
epoch: 028		acc: 0.5672		nmi: 0.2771		ari: 0.2584		f1: 0.5642		
epoch: 029		acc: 0.5681		nmi: 0.2759		ari: 0.2573		f1: 0.5646		
epoch: 030		acc: 0.5655		nmi: 0.2736		ari: 0.2548		f1: 0.5626		
epoch: 031		acc: 0.5655		nmi: 0.2734		ari: 0.2555		f1: 0.5622		
epoch: 032		acc: 0.5639		nmi: 0.2710		ari: 0.2524		f1: 0.5601		
epoch: 033		acc: 0.5647		nmi: 0.2731		ari: 0.2536		f1: 0.5611		
epoch: 034		acc: 0.5664		nmi: 0.2742		ari: 0.2548		f1: 0.5636		
epoch: 035		acc: 0.5664		nmi: 0.2748		ari: 0.2563		f1: 0.5622		
epoch: 036		acc: 0.5689		nmi: 0.2777		ari: 0.2581		f1: 0.5655		
epoch: 037		acc: 0.5697		nmi: 0.2728		ari: 0.2545		f1: 0.5664		
epoch: 038		acc: 0.5605		nmi: 0.2672		ari: 0.2496		f1: 0.5565		
epoch: 039		acc: 0.5655		nmi: 0.2721		ari: 0.2538		f1: 0.5622		
epoch: 040		acc: 0.5613		nmi: 0.2673		ari: 0.2488		f1: 0.5580		
epoch: 041		acc: 0.5647		nmi: 0.2678		ari: 0.2510		f1: 0.5608		
epoch: 042		acc: 0.5639		nmi: 0.2728		ari: 0.2519		f1: 0.5605		
epoch: 043		acc: 0.5622		nmi: 0.2719		ari: 0.2543		f1: 0.5580		
epoch: 044		acc: 0.5630		nmi: 0.2744		ari: 0.2558		f1: 0.5590		
epoch: 045		acc: 0.5630		nmi: 0.2712		ari: 0.2521		f1: 0.5594		
epoch: 046		acc: 0.5655		nmi: 0.2734		ari: 0.2555		f1: 0.5624		
epoch: 047		acc: 0.5647		nmi: 0.2722		ari: 0.2541		f1: 0.5609		
epoch: 048		acc: 0.5664		nmi: 0.2729		ari: 0.2551		f1: 0.5626		
epoch: 049		acc: 0.5639		nmi: 0.2720		ari: 0.2530		f1: 0.5602		
epoch: 050		acc: 0.5630		nmi: 0.2728		ari: 0.2521		f1: 0.5597		
The total number of parameters is: 0.067648M(1e6).
The max memory allocated to model is: 106.97 MB.
Time consuming: 0.89s or 0.01m
****************************************Training loop No.8****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=239, out_features=128, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.5672		nmi: 0.2863		ari: 0.2571		f1: 0.5725		
epoch: 002		acc: 0.5672		nmi: 0.2783		ari: 0.2463		f1: 0.5747		
epoch: 003		acc: 0.5630		nmi: 0.2777		ari: 0.2499		f1: 0.5686		
epoch: 004		acc: 0.5723		nmi: 0.2868		ari: 0.2651		f1: 0.5743		
epoch: 005		acc: 0.5689		nmi: 0.2850		ari: 0.2631		f1: 0.5693		
epoch: 006		acc: 0.5681		nmi: 0.2870		ari: 0.2623		f1: 0.5704		
epoch: 007		acc: 0.5748		nmi: 0.2855		ari: 0.2653		f1: 0.5764		
epoch: 008		acc: 0.5689		nmi: 0.2839		ari: 0.2623		f1: 0.5704		
epoch: 009		acc: 0.5647		nmi: 0.2803		ari: 0.2572		f1: 0.5661		
epoch: 010		acc: 0.5639		nmi: 0.2760		ari: 0.2541		f1: 0.5652		
epoch: 011		acc: 0.5655		nmi: 0.2791		ari: 0.2553		f1: 0.5674		
epoch: 012		acc: 0.5731		nmi: 0.2887		ari: 0.2671		f1: 0.5737		
epoch: 013		acc: 0.5672		nmi: 0.2830		ari: 0.2587		f1: 0.5687		
epoch: 014		acc: 0.5697		nmi: 0.2804		ari: 0.2607		f1: 0.5695		
epoch: 015		acc: 0.5689		nmi: 0.2779		ari: 0.2583		f1: 0.5682		
epoch: 016		acc: 0.5681		nmi: 0.2771		ari: 0.2593		f1: 0.5676		
epoch: 017		acc: 0.5639		nmi: 0.2751		ari: 0.2546		f1: 0.5632		
epoch: 018		acc: 0.5647		nmi: 0.2730		ari: 0.2530		f1: 0.5643		
epoch: 019		acc: 0.5681		nmi: 0.2803		ari: 0.2605		f1: 0.5663		
epoch: 020		acc: 0.5714		nmi: 0.2863		ari: 0.2669		f1: 0.5696		
epoch: 021		acc: 0.5697		nmi: 0.2767		ari: 0.2596		f1: 0.5684		
epoch: 022		acc: 0.5664		nmi: 0.2777		ari: 0.2590		f1: 0.5645		
epoch: 023		acc: 0.5664		nmi: 0.2782		ari: 0.2588		f1: 0.5636		
epoch: 024		acc: 0.5655		nmi: 0.2758		ari: 0.2567		f1: 0.5635		
epoch: 025		acc: 0.5706		nmi: 0.2817		ari: 0.2636		f1: 0.5682		
epoch: 026		acc: 0.5639		nmi: 0.2689		ari: 0.2520		f1: 0.5616		
epoch: 027		acc: 0.5689		nmi: 0.2767		ari: 0.2588		f1: 0.5659		
epoch: 028		acc: 0.5655		nmi: 0.2744		ari: 0.2554		f1: 0.5623		
epoch: 029		acc: 0.5681		nmi: 0.2729		ari: 0.2562		f1: 0.5655		
epoch: 030		acc: 0.5681		nmi: 0.2745		ari: 0.2574		f1: 0.5642		
epoch: 031		acc: 0.5681		nmi: 0.2741		ari: 0.2561		f1: 0.5655		
epoch: 032		acc: 0.5664		nmi: 0.2754		ari: 0.2576		f1: 0.5632		
epoch: 033		acc: 0.5681		nmi: 0.2735		ari: 0.2555		f1: 0.5647		
epoch: 034		acc: 0.5672		nmi: 0.2728		ari: 0.2561		f1: 0.5630		
epoch: 035		acc: 0.5639		nmi: 0.2714		ari: 0.2531		f1: 0.5599		
epoch: 036		acc: 0.5613		nmi: 0.2697		ari: 0.2499		f1: 0.5577		
epoch: 037		acc: 0.5639		nmi: 0.2704		ari: 0.2520		f1: 0.5597		
epoch: 038		acc: 0.5672		nmi: 0.2732		ari: 0.2552		f1: 0.5629		
epoch: 039		acc: 0.5647		nmi: 0.2707		ari: 0.2523		f1: 0.5607		
epoch: 040		acc: 0.5655		nmi: 0.2739		ari: 0.2560		f1: 0.5615		
epoch: 041		acc: 0.5647		nmi: 0.2718		ari: 0.2554		f1: 0.5602		
epoch: 042		acc: 0.5664		nmi: 0.2714		ari: 0.2533		f1: 0.5630		
epoch: 043		acc: 0.5672		nmi: 0.2705		ari: 0.2525		f1: 0.5635		
epoch: 044		acc: 0.5655		nmi: 0.2712		ari: 0.2542		f1: 0.5612		
epoch: 045		acc: 0.5622		nmi: 0.2654		ari: 0.2476		f1: 0.5582		
epoch: 046		acc: 0.5613		nmi: 0.2664		ari: 0.2471		f1: 0.5574		
epoch: 047		acc: 0.5647		nmi: 0.2675		ari: 0.2497		f1: 0.5610		
epoch: 048		acc: 0.5655		nmi: 0.2726		ari: 0.2537		f1: 0.5616		
epoch: 049		acc: 0.5689		nmi: 0.2715		ari: 0.2560		f1: 0.5642		
epoch: 050		acc: 0.5647		nmi: 0.2715		ari: 0.2525		f1: 0.5607		
The total number of parameters is: 0.067648M(1e6).
The max memory allocated to model is: 106.97 MB.
Time consuming: 0.86s or 0.01m
****************************************Training loop No.9****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=239, out_features=128, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.5689		nmi: 0.2786		ari: 0.2531		f1: 0.5746		
epoch: 002		acc: 0.5613		nmi: 0.2746		ari: 0.2449		f1: 0.5687		
epoch: 003		acc: 0.5664		nmi: 0.2810		ari: 0.2546		f1: 0.5712		
epoch: 004		acc: 0.5697		nmi: 0.2841		ari: 0.2607		f1: 0.5724		
epoch: 005		acc: 0.5664		nmi: 0.2754		ari: 0.2568		f1: 0.5666		
epoch: 006		acc: 0.5664		nmi: 0.2794		ari: 0.2609		f1: 0.5669		
epoch: 007		acc: 0.5697		nmi: 0.2846		ari: 0.2611		f1: 0.5724		
epoch: 008		acc: 0.5672		nmi: 0.2799		ari: 0.2587		f1: 0.5674		
epoch: 009		acc: 0.5697		nmi: 0.2824		ari: 0.2624		f1: 0.5702		
epoch: 010		acc: 0.5639		nmi: 0.2816		ari: 0.2597		f1: 0.5647		
epoch: 011		acc: 0.5647		nmi: 0.2765		ari: 0.2569		f1: 0.5653		
epoch: 012		acc: 0.5681		nmi: 0.2773		ari: 0.2577		f1: 0.5688		
epoch: 013		acc: 0.5664		nmi: 0.2757		ari: 0.2568		f1: 0.5670		
epoch: 014		acc: 0.5655		nmi: 0.2803		ari: 0.2594		f1: 0.5658		
epoch: 015		acc: 0.5697		nmi: 0.2806		ari: 0.2617		f1: 0.5683		
epoch: 016		acc: 0.5672		nmi: 0.2811		ari: 0.2627		f1: 0.5655		
epoch: 017		acc: 0.5681		nmi: 0.2788		ari: 0.2606		f1: 0.5661		
epoch: 018		acc: 0.5664		nmi: 0.2764		ari: 0.2584		f1: 0.5649		
epoch: 019		acc: 0.5697		nmi: 0.2816		ari: 0.2613		f1: 0.5688		
epoch: 020		acc: 0.5655		nmi: 0.2787		ari: 0.2575		f1: 0.5643		
epoch: 021		acc: 0.5655		nmi: 0.2747		ari: 0.2569		f1: 0.5640		
epoch: 022		acc: 0.5723		nmi: 0.2839		ari: 0.2664		f1: 0.5699		
epoch: 023		acc: 0.5664		nmi: 0.2760		ari: 0.2582		f1: 0.5629		
epoch: 024		acc: 0.5672		nmi: 0.2767		ari: 0.2562		f1: 0.5653		
epoch: 025		acc: 0.5689		nmi: 0.2789		ari: 0.2622		f1: 0.5660		
epoch: 026		acc: 0.5630		nmi: 0.2733		ari: 0.2538		f1: 0.5610		
epoch: 027		acc: 0.5689		nmi: 0.2815		ari: 0.2619		f1: 0.5660		
epoch: 028		acc: 0.5622		nmi: 0.2723		ari: 0.2542		f1: 0.5590		
epoch: 029		acc: 0.5622		nmi: 0.2714		ari: 0.2519		f1: 0.5595		
epoch: 030		acc: 0.5647		nmi: 0.2708		ari: 0.2542		f1: 0.5610		
epoch: 031		acc: 0.5639		nmi: 0.2684		ari: 0.2497		f1: 0.5616		
epoch: 032		acc: 0.5672		nmi: 0.2770		ari: 0.2567		f1: 0.5643		
epoch: 033		acc: 0.5706		nmi: 0.2809		ari: 0.2616		f1: 0.5669		
epoch: 034		acc: 0.5655		nmi: 0.2741		ari: 0.2541		f1: 0.5622		
epoch: 035		acc: 0.5630		nmi: 0.2698		ari: 0.2494		f1: 0.5606		
epoch: 036		acc: 0.5681		nmi: 0.2756		ari: 0.2561		f1: 0.5649		
epoch: 037		acc: 0.5639		nmi: 0.2698		ari: 0.2512		f1: 0.5603		
epoch: 038		acc: 0.5664		nmi: 0.2729		ari: 0.2554		f1: 0.5627		
epoch: 039		acc: 0.5647		nmi: 0.2728		ari: 0.2539		f1: 0.5611		
epoch: 040		acc: 0.5630		nmi: 0.2688		ari: 0.2503		f1: 0.5592		
epoch: 041		acc: 0.5630		nmi: 0.2726		ari: 0.2525		f1: 0.5590		
epoch: 042		acc: 0.5681		nmi: 0.2745		ari: 0.2557		f1: 0.5645		
epoch: 043		acc: 0.5655		nmi: 0.2728		ari: 0.2524		f1: 0.5620		
epoch: 044		acc: 0.5672		nmi: 0.2724		ari: 0.2549		f1: 0.5635		
epoch: 045		acc: 0.5639		nmi: 0.2712		ari: 0.2517		f1: 0.5598		
epoch: 046		acc: 0.5622		nmi: 0.2667		ari: 0.2478		f1: 0.5584		
epoch: 047		acc: 0.5681		nmi: 0.2754		ari: 0.2552		f1: 0.5647		
epoch: 048		acc: 0.5647		nmi: 0.2705		ari: 0.2503		f1: 0.5614		
epoch: 049		acc: 0.5647		nmi: 0.2695		ari: 0.2521		f1: 0.5610		
epoch: 050		acc: 0.5655		nmi: 0.2740		ari: 0.2543		f1: 0.5614		
The total number of parameters is: 0.067648M(1e6).
The max memory allocated to model is: 106.97 MB.
Time consuming: 0.84s or 0.01m
****************************************Training loop No.10****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=239, out_features=128, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.5647		nmi: 0.2772		ari: 0.2517		f1: 0.5693		
epoch: 002		acc: 0.5622		nmi: 0.2820		ari: 0.2480		f1: 0.5706		
epoch: 003		acc: 0.5714		nmi: 0.2871		ari: 0.2588		f1: 0.5765		
epoch: 004		acc: 0.5630		nmi: 0.2770		ari: 0.2542		f1: 0.5647		
epoch: 005		acc: 0.5613		nmi: 0.2732		ari: 0.2539		f1: 0.5627		
epoch: 006		acc: 0.5664		nmi: 0.2799		ari: 0.2617		f1: 0.5665		
epoch: 007		acc: 0.5664		nmi: 0.2813		ari: 0.2609		f1: 0.5671		
epoch: 008		acc: 0.5681		nmi: 0.2868		ari: 0.2626		f1: 0.5701		
epoch: 009		acc: 0.5689		nmi: 0.2827		ari: 0.2621		f1: 0.5703		
epoch: 010		acc: 0.5647		nmi: 0.2867		ari: 0.2633		f1: 0.5651		
epoch: 011		acc: 0.5664		nmi: 0.2780		ari: 0.2585		f1: 0.5664		
epoch: 012		acc: 0.5689		nmi: 0.2766		ari: 0.2570		f1: 0.5699		
epoch: 013		acc: 0.5672		nmi: 0.2773		ari: 0.2588		f1: 0.5671		
epoch: 014		acc: 0.5681		nmi: 0.2823		ari: 0.2619		f1: 0.5681		
epoch: 015		acc: 0.5672		nmi: 0.2741		ari: 0.2569		f1: 0.5661		
epoch: 016		acc: 0.5664		nmi: 0.2783		ari: 0.2579		f1: 0.5646		
epoch: 017		acc: 0.5664		nmi: 0.2801		ari: 0.2582		f1: 0.5647		
epoch: 018		acc: 0.5664		nmi: 0.2774		ari: 0.2569		f1: 0.5651		
epoch: 019		acc: 0.5681		nmi: 0.2830		ari: 0.2632		f1: 0.5657		
epoch: 020		acc: 0.5689		nmi: 0.2785		ari: 0.2608		f1: 0.5675		
epoch: 021		acc: 0.5689		nmi: 0.2813		ari: 0.2613		f1: 0.5673		
epoch: 022		acc: 0.5689		nmi: 0.2814		ari: 0.2629		f1: 0.5665		
epoch: 023		acc: 0.5739		nmi: 0.2854		ari: 0.2670		f1: 0.5714		
epoch: 024		acc: 0.5664		nmi: 0.2775		ari: 0.2586		f1: 0.5636		
epoch: 025		acc: 0.5672		nmi: 0.2828		ari: 0.2634		f1: 0.5642		
epoch: 026		acc: 0.5622		nmi: 0.2716		ari: 0.2512		f1: 0.5590		
epoch: 027		acc: 0.5639		nmi: 0.2769		ari: 0.2553		f1: 0.5615		
epoch: 028		acc: 0.5655		nmi: 0.2723		ari: 0.2540		f1: 0.5623		
epoch: 029		acc: 0.5613		nmi: 0.2692		ari: 0.2495		f1: 0.5580		
epoch: 030		acc: 0.5655		nmi: 0.2724		ari: 0.2534		f1: 0.5621		
epoch: 031		acc: 0.5672		nmi: 0.2746		ari: 0.2563		f1: 0.5637		
epoch: 032		acc: 0.5681		nmi: 0.2792		ari: 0.2604		f1: 0.5637		
epoch: 033		acc: 0.5647		nmi: 0.2714		ari: 0.2514		f1: 0.5619		
epoch: 034		acc: 0.5697		nmi: 0.2760		ari: 0.2588		f1: 0.5657		
epoch: 035		acc: 0.5588		nmi: 0.2692		ari: 0.2476		f1: 0.5552		
epoch: 036		acc: 0.5647		nmi: 0.2671		ari: 0.2509		f1: 0.5607		
epoch: 037		acc: 0.5664		nmi: 0.2689		ari: 0.2512		f1: 0.5626		
epoch: 038		acc: 0.5655		nmi: 0.2743		ari: 0.2550		f1: 0.5617		
epoch: 039		acc: 0.5672		nmi: 0.2748		ari: 0.2568		f1: 0.5629		
epoch: 040		acc: 0.5672		nmi: 0.2730		ari: 0.2553		f1: 0.5625		
epoch: 041		acc: 0.5639		nmi: 0.2710		ari: 0.2523		f1: 0.5602		
epoch: 042		acc: 0.5613		nmi: 0.2650		ari: 0.2487		f1: 0.5572		
epoch: 043		acc: 0.5655		nmi: 0.2710		ari: 0.2517		f1: 0.5616		
epoch: 044		acc: 0.5588		nmi: 0.2665		ari: 0.2469		f1: 0.5550		
epoch: 045		acc: 0.5664		nmi: 0.2711		ari: 0.2527		f1: 0.5624		
epoch: 046		acc: 0.5613		nmi: 0.2660		ari: 0.2493		f1: 0.5572		
epoch: 047		acc: 0.5630		nmi: 0.2697		ari: 0.2523		f1: 0.5588		
epoch: 048		acc: 0.5647		nmi: 0.2681		ari: 0.2510		f1: 0.5609		
epoch: 049		acc: 0.5613		nmi: 0.2725		ari: 0.2514		f1: 0.5565		
epoch: 050		acc: 0.5613		nmi: 0.2654		ari: 0.2463		f1: 0.5572		
The total number of parameters is: 0.067648M(1e6).
The max memory allocated to model is: 106.97 MB.
Time consuming: 0.91s or 0.02m
Namespace(is_pretrain=False, plot_clustering_tsne=False, plot_embedding_heatmap=False, adj_norm=False, adj_loop=True, adj_symmetric=True, desc='default', model_name='SYNC', dataset_name='uat', root=None, k=None, t=None, loops=10, feature_type='tensor', label_type='npy', adj_type='tensor', seed=325, epsilon=0.0, device='cuda', clusters=4, nodes=1190, lr=0.001, max_epoch=50, pretrain_lr=0.001, pretrain_epoch=30, input_dim=239, log_save_path='./logs/SYNC/uat/', dataset_path='../data/', clustering_tsne_save_path='./img/clustering/SYNC/uat/', embedding_heatmap_save_path='./img/heatmap/SYNC/uat/', pretrain_save_path='./pretrain/pretrain_tigae/SYNC/uat/', hidden_dim=256, embedding_dim=16, linear_dim=128, beta=1)
Total loops: 10
****************************************Mean value:****************************************
acc: 0.5733±0.0012		nmi: 0.2857±0.0025		ari: 0.2661±0.0016		f1: 0.5732±0.0024
Training over! Punch out!
Loading wisc dataset from local
****************************************Training loop No.1****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=1703, out_features=512, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.4821		nmi: 0.2923		ari: 0.1967		f1: 0.3998		
epoch: 002		acc: 0.4861		nmi: 0.3206		ari: 0.2144		f1: 0.4113		
epoch: 003		acc: 0.4582		nmi: 0.2458		ari: 0.1451		f1: 0.3108		
epoch: 004		acc: 0.4462		nmi: 0.3247		ari: 0.2176		f1: 0.3590		
epoch: 005		acc: 0.4462		nmi: 0.3147		ari: 0.2060		f1: 0.3955		
epoch: 006		acc: 0.4582		nmi: 0.3026		ari: 0.2178		f1: 0.3756		
epoch: 007		acc: 0.4542		nmi: 0.2869		ari: 0.1982		f1: 0.3424		
epoch: 008		acc: 0.4502		nmi: 0.2769		ari: 0.1872		f1: 0.3610		
epoch: 009		acc: 0.5020		nmi: 0.3075		ari: 0.2262		f1: 0.4080		
epoch: 010		acc: 0.4940		nmi: 0.3093		ari: 0.2398		f1: 0.3937		
epoch: 011		acc: 0.5259		nmi: 0.3214		ari: 0.2598		f1: 0.4129		
epoch: 012		acc: 0.5020		nmi: 0.3175		ari: 0.2393		f1: 0.3764		
epoch: 013		acc: 0.5139		nmi: 0.3214		ari: 0.2449		f1: 0.3644		
epoch: 014		acc: 0.5179		nmi: 0.3030		ari: 0.2326		f1: 0.3684		
epoch: 015		acc: 0.5100		nmi: 0.2931		ari: 0.2160		f1: 0.3441		
epoch: 016		acc: 0.5299		nmi: 0.2971		ari: 0.2408		f1: 0.3546		
epoch: 017		acc: 0.5418		nmi: 0.3126		ari: 0.2514		f1: 0.3860		
epoch: 018		acc: 0.5378		nmi: 0.3191		ari: 0.2414		f1: 0.3655		
epoch: 019		acc: 0.5378		nmi: 0.3047		ari: 0.2398		f1: 0.3618		
epoch: 020		acc: 0.5498		nmi: 0.3081		ari: 0.2473		f1: 0.3797		
epoch: 021		acc: 0.5378		nmi: 0.3012		ari: 0.2345		f1: 0.3742		
epoch: 022		acc: 0.5498		nmi: 0.3214		ari: 0.2567		f1: 0.3914		
epoch: 023		acc: 0.5697		nmi: 0.3245		ari: 0.2731		f1: 0.3864		
epoch: 024		acc: 0.5618		nmi: 0.3186		ari: 0.2631		f1: 0.3831		
epoch: 025		acc: 0.5538		nmi: 0.3107		ari: 0.2402		f1: 0.3905		
epoch: 026		acc: 0.5737		nmi: 0.3149		ari: 0.2598		f1: 0.4066		
epoch: 027		acc: 0.5578		nmi: 0.3050		ari: 0.2379		f1: 0.3630		
epoch: 028		acc: 0.5697		nmi: 0.3127		ari: 0.2554		f1: 0.3692		
epoch: 029		acc: 0.5697		nmi: 0.3106		ari: 0.2548		f1: 0.3697		
epoch: 030		acc: 0.5737		nmi: 0.3056		ari: 0.2553		f1: 0.3698		
epoch: 031		acc: 0.5657		nmi: 0.3103		ari: 0.2538		f1: 0.3783		
epoch: 032		acc: 0.5697		nmi: 0.3173		ari: 0.2592		f1: 0.3716		
epoch: 033		acc: 0.5697		nmi: 0.3092		ari: 0.2584		f1: 0.3819		
epoch: 034		acc: 0.5578		nmi: 0.3061		ari: 0.2504		f1: 0.3782		
epoch: 035		acc: 0.4861		nmi: 0.2954		ari: 0.2180		f1: 0.3444		
epoch: 036		acc: 0.5179		nmi: 0.2994		ari: 0.2194		f1: 0.3378		
epoch: 037		acc: 0.5817		nmi: 0.3018		ari: 0.2462		f1: 0.3605		
epoch: 038		acc: 0.5896		nmi: 0.3015		ari: 0.2524		f1: 0.3629		
epoch: 039		acc: 0.5896		nmi: 0.3082		ari: 0.2532		f1: 0.3626		
epoch: 040		acc: 0.5936		nmi: 0.3197		ari: 0.2633		f1: 0.3648		
epoch: 041		acc: 0.5896		nmi: 0.3082		ari: 0.2532		f1: 0.3626		
epoch: 042		acc: 0.5936		nmi: 0.3107		ari: 0.2581		f1: 0.3648		
epoch: 043		acc: 0.5976		nmi: 0.3146		ari: 0.2638		f1: 0.3679		
epoch: 044		acc: 0.5817		nmi: 0.2942		ari: 0.2465		f1: 0.3616		
epoch: 045		acc: 0.5857		nmi: 0.3031		ari: 0.2598		f1: 0.3860		
epoch: 046		acc: 0.5896		nmi: 0.3085		ari: 0.2602		f1: 0.3659		
epoch: 047		acc: 0.5936		nmi: 0.3166		ari: 0.2643		f1: 0.3674		
epoch: 048		acc: 0.5777		nmi: 0.3020		ari: 0.2505		f1: 0.3808		
epoch: 049		acc: 0.5339		nmi: 0.2888		ari: 0.2212		f1: 0.3481		
epoch: 050		acc: 0.5219		nmi: 0.2948		ari: 0.2258		f1: 0.3647		
The total number of parameters is: 1.007696M(1e6).
The max memory allocated to model is: 40.90 MB.
Time consuming: 3.18s or 0.05m
****************************************Training loop No.2****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=1703, out_features=512, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.4861		nmi: 0.3219		ari: 0.2181		f1: 0.4224		
epoch: 002		acc: 0.4582		nmi: 0.2362		ari: 0.1406		f1: 0.3846		
epoch: 003		acc: 0.4303		nmi: 0.3122		ari: 0.1592		f1: 0.3403		
epoch: 004		acc: 0.5100		nmi: 0.3042		ari: 0.2285		f1: 0.3647		
epoch: 005		acc: 0.4661		nmi: 0.3110		ari: 0.2040		f1: 0.3553		
epoch: 006		acc: 0.5060		nmi: 0.3076		ari: 0.2407		f1: 0.3807		
epoch: 007		acc: 0.4980		nmi: 0.3129		ari: 0.2386		f1: 0.4205		
epoch: 008		acc: 0.4980		nmi: 0.3132		ari: 0.2406		f1: 0.4157		
epoch: 009		acc: 0.4861		nmi: 0.3189		ari: 0.2355		f1: 0.4043		
epoch: 010		acc: 0.4900		nmi: 0.3305		ari: 0.2396		f1: 0.3876		
epoch: 011		acc: 0.5100		nmi: 0.3083		ari: 0.2376		f1: 0.3790		
epoch: 012		acc: 0.5179		nmi: 0.3376		ari: 0.2561		f1: 0.3759		
epoch: 013		acc: 0.5219		nmi: 0.3186		ari: 0.2402		f1: 0.3674		
epoch: 014		acc: 0.5339		nmi: 0.3256		ari: 0.2664		f1: 0.3784		
epoch: 015		acc: 0.5219		nmi: 0.3147		ari: 0.2365		f1: 0.3582		
epoch: 016		acc: 0.5179		nmi: 0.3148		ari: 0.2427		f1: 0.3675		
epoch: 017		acc: 0.5060		nmi: 0.3295		ari: 0.2409		f1: 0.3705		
epoch: 018		acc: 0.4900		nmi: 0.3316		ari: 0.2467		f1: 0.3660		
epoch: 019		acc: 0.4343		nmi: 0.3070		ari: 0.2011		f1: 0.3382		
epoch: 020		acc: 0.4502		nmi: 0.2971		ari: 0.1911		f1: 0.3288		
epoch: 021		acc: 0.4422		nmi: 0.3284		ari: 0.2066		f1: 0.3238		
epoch: 022		acc: 0.4980		nmi: 0.3150		ari: 0.2181		f1: 0.3438		
epoch: 023		acc: 0.4980		nmi: 0.3116		ari: 0.2058		f1: 0.3417		
epoch: 024		acc: 0.5219		nmi: 0.3019		ari: 0.2163		f1: 0.3608		
epoch: 025		acc: 0.5378		nmi: 0.2996		ari: 0.2254		f1: 0.3653		
epoch: 026		acc: 0.5498		nmi: 0.3091		ari: 0.2317		f1: 0.3491		
epoch: 027		acc: 0.5578		nmi: 0.2979		ari: 0.2360		f1: 0.3640		
epoch: 028		acc: 0.5657		nmi: 0.3037		ari: 0.2433		f1: 0.3681		
epoch: 029		acc: 0.5737		nmi: 0.3016		ari: 0.2386		f1: 0.3684		
epoch: 030		acc: 0.5697		nmi: 0.3021		ari: 0.2365		f1: 0.3517		
epoch: 031		acc: 0.5697		nmi: 0.2993		ari: 0.2370		f1: 0.3660		
epoch: 032		acc: 0.5697		nmi: 0.3062		ari: 0.2405		f1: 0.3537		
epoch: 033		acc: 0.5777		nmi: 0.3041		ari: 0.2449		f1: 0.3546		
epoch: 034		acc: 0.5817		nmi: 0.3129		ari: 0.2512		f1: 0.3870		
epoch: 035		acc: 0.5777		nmi: 0.3041		ari: 0.2449		f1: 0.3546		
epoch: 036		acc: 0.5737		nmi: 0.3002		ari: 0.2395		f1: 0.3522		
epoch: 037		acc: 0.5817		nmi: 0.3122		ari: 0.2509		f1: 0.3569		
epoch: 038		acc: 0.5777		nmi: 0.3041		ari: 0.2449		f1: 0.3546		
epoch: 039		acc: 0.5777		nmi: 0.3041		ari: 0.2449		f1: 0.3546		
epoch: 040		acc: 0.5817		nmi: 0.3017		ari: 0.2480		f1: 0.3588		
epoch: 041		acc: 0.5817		nmi: 0.3062		ari: 0.2490		f1: 0.3569		
epoch: 042		acc: 0.5817		nmi: 0.3041		ari: 0.2502		f1: 0.3834		
epoch: 043		acc: 0.5777		nmi: 0.2944		ari: 0.2443		f1: 0.3574		
epoch: 044		acc: 0.5498		nmi: 0.2872		ari: 0.2226		f1: 0.3499		
epoch: 045		acc: 0.5219		nmi: 0.2777		ari: 0.2115		f1: 0.3522		
epoch: 046		acc: 0.5299		nmi: 0.2815		ari: 0.2200		f1: 0.3622		
epoch: 047		acc: 0.5578		nmi: 0.2829		ari: 0.2320		f1: 0.3541		
epoch: 048		acc: 0.5777		nmi: 0.2944		ari: 0.2445		f1: 0.3558		
epoch: 049		acc: 0.5817		nmi: 0.2993		ari: 0.2480		f1: 0.3572		
epoch: 050		acc: 0.5777		nmi: 0.2972		ari: 0.2438		f1: 0.3550		
The total number of parameters is: 1.007696M(1e6).
The max memory allocated to model is: 48.95 MB.
Time consuming: 0.54s or 0.01m
****************************************Training loop No.3****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=1703, out_features=512, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.5020		nmi: 0.3118		ari: 0.2045		f1: 0.4086		
epoch: 002		acc: 0.4701		nmi: 0.2965		ari: 0.1920		f1: 0.4109		
epoch: 003		acc: 0.5458		nmi: 0.3139		ari: 0.2181		f1: 0.3613		
epoch: 004		acc: 0.4781		nmi: 0.3158		ari: 0.2217		f1: 0.3564		
epoch: 005		acc: 0.4980		nmi: 0.3326		ari: 0.2398		f1: 0.4328		
epoch: 006		acc: 0.5020		nmi: 0.3344		ari: 0.2413		f1: 0.3954		
epoch: 007		acc: 0.4781		nmi: 0.3399		ari: 0.2345		f1: 0.3488		
epoch: 008		acc: 0.4622		nmi: 0.3190		ari: 0.2186		f1: 0.3657		
epoch: 009		acc: 0.5100		nmi: 0.3425		ari: 0.2572		f1: 0.4034		
epoch: 010		acc: 0.5339		nmi: 0.3238		ari: 0.2608		f1: 0.4094		
epoch: 011		acc: 0.5339		nmi: 0.3302		ari: 0.2635		f1: 0.3825		
epoch: 012		acc: 0.5378		nmi: 0.3370		ari: 0.2510		f1: 0.3780		
epoch: 013		acc: 0.5498		nmi: 0.3500		ari: 0.2692		f1: 0.3849		
epoch: 014		acc: 0.5578		nmi: 0.3519		ari: 0.2698		f1: 0.3920		
epoch: 015		acc: 0.5418		nmi: 0.3302		ari: 0.2414		f1: 0.3794		
epoch: 016		acc: 0.5418		nmi: 0.3444		ari: 0.2497		f1: 0.3661		
epoch: 017		acc: 0.5657		nmi: 0.3560		ari: 0.2707		f1: 0.3972		
epoch: 018		acc: 0.5657		nmi: 0.3407		ari: 0.2772		f1: 0.3989		
epoch: 019		acc: 0.5538		nmi: 0.3552		ari: 0.2647		f1: 0.4114		
epoch: 020		acc: 0.5657		nmi: 0.3595		ari: 0.2821		f1: 0.4025		
epoch: 021		acc: 0.5578		nmi: 0.3447		ari: 0.2637		f1: 0.3736		
epoch: 022		acc: 0.5618		nmi: 0.3467		ari: 0.2670		f1: 0.3965		
epoch: 023		acc: 0.5737		nmi: 0.3527		ari: 0.2805		f1: 0.4033		
epoch: 024		acc: 0.5578		nmi: 0.3527		ari: 0.2691		f1: 0.3753		
epoch: 025		acc: 0.5777		nmi: 0.3603		ari: 0.2864		f1: 0.4101		
epoch: 026		acc: 0.5777		nmi: 0.3806		ari: 0.3147		f1: 0.3898		
epoch: 027		acc: 0.5418		nmi: 0.3537		ari: 0.2726		f1: 0.3769		
epoch: 028		acc: 0.5139		nmi: 0.3459		ari: 0.2547		f1: 0.3677		
epoch: 029		acc: 0.5259		nmi: 0.3540		ari: 0.2386		f1: 0.3699		
epoch: 030		acc: 0.5777		nmi: 0.3365		ari: 0.2552		f1: 0.3771		
epoch: 031		acc: 0.5857		nmi: 0.3451		ari: 0.2647		f1: 0.3936		
epoch: 032		acc: 0.5817		nmi: 0.3480		ari: 0.2614		f1: 0.3636		
epoch: 033		acc: 0.5896		nmi: 0.3463		ari: 0.2701		f1: 0.3683		
epoch: 034		acc: 0.6016		nmi: 0.3522		ari: 0.2805		f1: 0.3706		
epoch: 035		acc: 0.6016		nmi: 0.3410		ari: 0.2795		f1: 0.3707		
epoch: 036		acc: 0.6056		nmi: 0.3565		ari: 0.2863		f1: 0.3731		
epoch: 037		acc: 0.6056		nmi: 0.3607		ari: 0.2888		f1: 0.3727		
epoch: 038		acc: 0.6056		nmi: 0.3565		ari: 0.2863		f1: 0.3731		
epoch: 039		acc: 0.6016		nmi: 0.3522		ari: 0.2805		f1: 0.3706		
epoch: 040		acc: 0.6056		nmi: 0.3565		ari: 0.2863		f1: 0.3731		
epoch: 041		acc: 0.6016		nmi: 0.3522		ari: 0.2805		f1: 0.3706		
epoch: 042		acc: 0.6056		nmi: 0.3571		ari: 0.2873		f1: 0.3731		
epoch: 043		acc: 0.6016		nmi: 0.3522		ari: 0.2805		f1: 0.3706		
epoch: 044		acc: 0.6056		nmi: 0.3565		ari: 0.2863		f1: 0.3731		
epoch: 045		acc: 0.6056		nmi: 0.3533		ari: 0.2872		f1: 0.3739		
epoch: 046		acc: 0.6056		nmi: 0.3528		ari: 0.2877		f1: 0.3756		
epoch: 047		acc: 0.5896		nmi: 0.3451		ari: 0.2782		f1: 0.3707		
epoch: 048		acc: 0.5737		nmi: 0.3344		ari: 0.2578		f1: 0.3638		
epoch: 049		acc: 0.4781		nmi: 0.3379		ari: 0.2424		f1: 0.3243		
epoch: 050		acc: 0.5657		nmi: 0.3422		ari: 0.2737		f1: 0.3771		
The total number of parameters is: 1.007696M(1e6).
The max memory allocated to model is: 48.95 MB.
Time consuming: 0.53s or 0.01m
****************************************Training loop No.4****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=1703, out_features=512, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.4661		nmi: 0.3108		ari: 0.1981		f1: 0.3341		
epoch: 002		acc: 0.4223		nmi: 0.1070		ari: 0.0128		f1: 0.2079		
epoch: 003		acc: 0.4701		nmi: 0.2266		ari: 0.1384		f1: 0.2994		
epoch: 004		acc: 0.4382		nmi: 0.2864		ari: 0.2013		f1: 0.3242		
epoch: 005		acc: 0.4821		nmi: 0.3257		ari: 0.1974		f1: 0.3446		
epoch: 006		acc: 0.5418		nmi: 0.3127		ari: 0.2241		f1: 0.4091		
epoch: 007		acc: 0.4661		nmi: 0.2817		ari: 0.1830		f1: 0.3813		
epoch: 008		acc: 0.4582		nmi: 0.2927		ari: 0.2019		f1: 0.3916		
epoch: 009		acc: 0.4542		nmi: 0.2917		ari: 0.2014		f1: 0.3734		
epoch: 010		acc: 0.4781		nmi: 0.3159		ari: 0.2257		f1: 0.3440		
epoch: 011		acc: 0.4781		nmi: 0.3182		ari: 0.2403		f1: 0.3396		
epoch: 012		acc: 0.4781		nmi: 0.3249		ari: 0.2389		f1: 0.3781		
epoch: 013		acc: 0.4940		nmi: 0.3000		ari: 0.2188		f1: 0.3867		
epoch: 014		acc: 0.4940		nmi: 0.3267		ari: 0.2361		f1: 0.3834		
epoch: 015		acc: 0.5020		nmi: 0.3105		ari: 0.2375		f1: 0.3894		
epoch: 016		acc: 0.5020		nmi: 0.3162		ari: 0.2454		f1: 0.3689		
epoch: 017		acc: 0.5179		nmi: 0.3070		ari: 0.2336		f1: 0.3625		
epoch: 018		acc: 0.5339		nmi: 0.3108		ari: 0.2480		f1: 0.3871		
epoch: 019		acc: 0.5219		nmi: 0.3000		ari: 0.2258		f1: 0.3796		
epoch: 020		acc: 0.5418		nmi: 0.3065		ari: 0.2360		f1: 0.3947		
epoch: 021		acc: 0.5498		nmi: 0.3189		ari: 0.2564		f1: 0.3848		
epoch: 022		acc: 0.5538		nmi: 0.3189		ari: 0.2539		f1: 0.3907		
epoch: 023		acc: 0.5458		nmi: 0.3170		ari: 0.2495		f1: 0.3877		
epoch: 024		acc: 0.5498		nmi: 0.3182		ari: 0.2498		f1: 0.3877		
epoch: 025		acc: 0.5697		nmi: 0.3279		ari: 0.2828		f1: 0.4064		
epoch: 026		acc: 0.5618		nmi: 0.3207		ari: 0.2675		f1: 0.3837		
epoch: 027		acc: 0.5538		nmi: 0.2987		ari: 0.2397		f1: 0.3681		
epoch: 028		acc: 0.5618		nmi: 0.3208		ari: 0.2649		f1: 0.3760		
epoch: 029		acc: 0.5578		nmi: 0.3269		ari: 0.2620		f1: 0.3751		
epoch: 030		acc: 0.4900		nmi: 0.2951		ari: 0.2059		f1: 0.3714		
epoch: 031		acc: 0.5179		nmi: 0.2844		ari: 0.2049		f1: 0.3606		
epoch: 032		acc: 0.5618		nmi: 0.3012		ari: 0.2288		f1: 0.3566		
epoch: 033		acc: 0.5777		nmi: 0.3075		ari: 0.2437		f1: 0.3615		
epoch: 034		acc: 0.5857		nmi: 0.3154		ari: 0.2519		f1: 0.3645		
epoch: 035		acc: 0.5936		nmi: 0.3200		ari: 0.2608		f1: 0.3674		
epoch: 036		acc: 0.5976		nmi: 0.3259		ari: 0.2655		f1: 0.3688		
epoch: 037		acc: 0.5896		nmi: 0.3059		ari: 0.2516		f1: 0.3644		
epoch: 038		acc: 0.5857		nmi: 0.3149		ari: 0.2516		f1: 0.3637		
epoch: 039		acc: 0.5936		nmi: 0.3092		ari: 0.2569		f1: 0.3667		
epoch: 040		acc: 0.5976		nmi: 0.3128		ari: 0.2593		f1: 0.3704		
epoch: 041		acc: 0.5976		nmi: 0.3116		ari: 0.2618		f1: 0.3690		
epoch: 042		acc: 0.5936		nmi: 0.3092		ari: 0.2569		f1: 0.3667		
epoch: 043		acc: 0.5857		nmi: 0.3034		ari: 0.2466		f1: 0.3628		
epoch: 044		acc: 0.5936		nmi: 0.3092		ari: 0.2569		f1: 0.3667		
epoch: 045		acc: 0.5936		nmi: 0.3183		ari: 0.2579		f1: 0.3985		
epoch: 046		acc: 0.5976		nmi: 0.3168		ari: 0.2634		f1: 0.3992		
epoch: 047		acc: 0.5976		nmi: 0.3161		ari: 0.2647		f1: 0.3961		
epoch: 048		acc: 0.5936		nmi: 0.3128		ari: 0.2622		f1: 0.3924		
epoch: 049		acc: 0.5817		nmi: 0.3011		ari: 0.2526		f1: 0.3666		
epoch: 050		acc: 0.4940		nmi: 0.2949		ari: 0.2172		f1: 0.3550		
The total number of parameters is: 1.007696M(1e6).
The max memory allocated to model is: 48.95 MB.
Time consuming: 0.53s or 0.01m
****************************************Training loop No.5****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=1703, out_features=512, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.4861		nmi: 0.3070		ari: 0.2106		f1: 0.4025		
epoch: 002		acc: 0.4980		nmi: 0.3454		ari: 0.2205		f1: 0.4289		
epoch: 003		acc: 0.4861		nmi: 0.2904		ari: 0.1836		f1: 0.3373		
epoch: 004		acc: 0.4622		nmi: 0.3465		ari: 0.2350		f1: 0.3982		
epoch: 005		acc: 0.4622		nmi: 0.3070		ari: 0.2192		f1: 0.4017		
epoch: 006		acc: 0.4661		nmi: 0.3034		ari: 0.2021		f1: 0.3472		
epoch: 007		acc: 0.4741		nmi: 0.3119		ari: 0.2183		f1: 0.3617		
epoch: 008		acc: 0.4980		nmi: 0.3218		ari: 0.2334		f1: 0.3975		
epoch: 009		acc: 0.5259		nmi: 0.3123		ari: 0.2489		f1: 0.4056		
epoch: 010		acc: 0.5139		nmi: 0.3181		ari: 0.2408		f1: 0.3970		
epoch: 011		acc: 0.5060		nmi: 0.3231		ari: 0.2324		f1: 0.3509		
epoch: 012		acc: 0.5179		nmi: 0.3108		ari: 0.2308		f1: 0.3711		
epoch: 013		acc: 0.5259		nmi: 0.3133		ari: 0.2243		f1: 0.3723		
epoch: 014		acc: 0.5219		nmi: 0.3186		ari: 0.2182		f1: 0.3701		
epoch: 015		acc: 0.5179		nmi: 0.3203		ari: 0.2278		f1: 0.3709		
epoch: 016		acc: 0.5299		nmi: 0.3233		ari: 0.2416		f1: 0.3656		
epoch: 017		acc: 0.5657		nmi: 0.3497		ari: 0.2766		f1: 0.4025		
epoch: 018		acc: 0.5498		nmi: 0.3325		ari: 0.2576		f1: 0.3909		
epoch: 019		acc: 0.5538		nmi: 0.3421		ari: 0.2620		f1: 0.3931		
epoch: 020		acc: 0.5538		nmi: 0.3346		ari: 0.2626		f1: 0.3951		
epoch: 021		acc: 0.5498		nmi: 0.3290		ari: 0.2537		f1: 0.3908		
epoch: 022		acc: 0.5498		nmi: 0.3203		ari: 0.2469		f1: 0.3682		
epoch: 023		acc: 0.5458		nmi: 0.3168		ari: 0.2390		f1: 0.3657		
epoch: 024		acc: 0.5578		nmi: 0.3274		ari: 0.2559		f1: 0.3936		
epoch: 025		acc: 0.5498		nmi: 0.3410		ari: 0.2611		f1: 0.3761		
epoch: 026		acc: 0.5618		nmi: 0.3211		ari: 0.2566		f1: 0.3984		
epoch: 027		acc: 0.5618		nmi: 0.3295		ari: 0.2686		f1: 0.3766		
epoch: 028		acc: 0.5538		nmi: 0.3409		ari: 0.2753		f1: 0.3787		
epoch: 029		acc: 0.5179		nmi: 0.3210		ari: 0.2408		f1: 0.3649		
epoch: 030		acc: 0.4741		nmi: 0.3068		ari: 0.2193		f1: 0.3501		
epoch: 031		acc: 0.5498		nmi: 0.3150		ari: 0.2350		f1: 0.3682		
epoch: 032		acc: 0.5777		nmi: 0.3213		ari: 0.2559		f1: 0.3796		
epoch: 033		acc: 0.5936		nmi: 0.3351		ari: 0.2726		f1: 0.3938		
epoch: 034		acc: 0.5976		nmi: 0.3412		ari: 0.2699		f1: 0.3692		
epoch: 035		acc: 0.5976		nmi: 0.3258		ari: 0.2657		f1: 0.3681		
epoch: 036		acc: 0.5936		nmi: 0.3220		ari: 0.2602		f1: 0.3656		
epoch: 037		acc: 0.6016		nmi: 0.3420		ari: 0.2733		f1: 0.3706		
epoch: 038		acc: 0.6016		nmi: 0.3282		ari: 0.2704		f1: 0.3703		
epoch: 039		acc: 0.5936		nmi: 0.3150		ari: 0.2591		f1: 0.3657		
epoch: 040		acc: 0.5976		nmi: 0.3258		ari: 0.2657		f1: 0.3681		
epoch: 041		acc: 0.6016		nmi: 0.3282		ari: 0.2704		f1: 0.3703		
epoch: 042		acc: 0.6056		nmi: 0.3307		ari: 0.2754		f1: 0.3725		
epoch: 043		acc: 0.6096		nmi: 0.3332		ari: 0.2805		f1: 0.3747		
epoch: 044		acc: 0.5896		nmi: 0.3162		ari: 0.2595		f1: 0.3690		
epoch: 045		acc: 0.6016		nmi: 0.3315		ari: 0.2710		f1: 0.3732		
epoch: 046		acc: 0.6016		nmi: 0.3273		ari: 0.2768		f1: 0.3740		
epoch: 047		acc: 0.5976		nmi: 0.3105		ari: 0.2660		f1: 0.3960		
epoch: 048		acc: 0.6016		nmi: 0.3295		ari: 0.2802		f1: 0.3735		
epoch: 049		acc: 0.5737		nmi: 0.3108		ari: 0.2506		f1: 0.3680		
epoch: 050		acc: 0.5179		nmi: 0.2987		ari: 0.2252		f1: 0.3534		
The total number of parameters is: 1.007696M(1e6).
The max memory allocated to model is: 48.95 MB.
Time consuming: 0.54s or 0.01m
****************************************Training loop No.6****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=1703, out_features=512, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.4781		nmi: 0.2912		ari: 0.2008		f1: 0.3934		
epoch: 002		acc: 0.5020		nmi: 0.3665		ari: 0.2570		f1: 0.3778		
epoch: 003		acc: 0.5100		nmi: 0.3375		ari: 0.2340		f1: 0.3562		
epoch: 004		acc: 0.4940		nmi: 0.3320		ari: 0.2439		f1: 0.4233		
epoch: 005		acc: 0.4701		nmi: 0.2984		ari: 0.2092		f1: 0.3484		
epoch: 006		acc: 0.4661		nmi: 0.3346		ari: 0.2351		f1: 0.3353		
epoch: 007		acc: 0.4821		nmi: 0.3274		ari: 0.2428		f1: 0.3944		
epoch: 008		acc: 0.5179		nmi: 0.3316		ari: 0.2667		f1: 0.4140		
epoch: 009		acc: 0.5299		nmi: 0.3189		ari: 0.2477		f1: 0.3757		
epoch: 010		acc: 0.4980		nmi: 0.3105		ari: 0.2280		f1: 0.3495		
epoch: 011		acc: 0.5139		nmi: 0.3223		ari: 0.2434		f1: 0.3729		
epoch: 012		acc: 0.5139		nmi: 0.3275		ari: 0.2524		f1: 0.3718		
epoch: 013		acc: 0.5179		nmi: 0.3093		ari: 0.2385		f1: 0.3731		
epoch: 014		acc: 0.5179		nmi: 0.3290		ari: 0.2500		f1: 0.3644		
epoch: 015		acc: 0.5299		nmi: 0.3145		ari: 0.2331		f1: 0.3798		
epoch: 016		acc: 0.5498		nmi: 0.3062		ari: 0.2436		f1: 0.3911		
epoch: 017		acc: 0.5378		nmi: 0.3100		ari: 0.2488		f1: 0.3714		
epoch: 018		acc: 0.5498		nmi: 0.3132		ari: 0.2513		f1: 0.3653		
epoch: 019		acc: 0.5339		nmi: 0.3045		ari: 0.2332		f1: 0.3778		
epoch: 020		acc: 0.5498		nmi: 0.2944		ari: 0.2455		f1: 0.3854		
epoch: 021		acc: 0.5458		nmi: 0.3025		ari: 0.2387		f1: 0.3831		
epoch: 022		acc: 0.5378		nmi: 0.3043		ari: 0.2349		f1: 0.3788		
epoch: 023		acc: 0.5418		nmi: 0.3143		ari: 0.2434		f1: 0.3620		
epoch: 024		acc: 0.5618		nmi: 0.3166		ari: 0.2636		f1: 0.3953		
epoch: 025		acc: 0.5418		nmi: 0.3093		ari: 0.2469		f1: 0.3857		
epoch: 026		acc: 0.5418		nmi: 0.3329		ari: 0.2731		f1: 0.3705		
epoch: 027		acc: 0.5139		nmi: 0.3154		ari: 0.2436		f1: 0.3863		
epoch: 028		acc: 0.4582		nmi: 0.2780		ari: 0.1934		f1: 0.3115		
epoch: 029		acc: 0.5060		nmi: 0.2952		ari: 0.2088		f1: 0.3283		
epoch: 030		acc: 0.5418		nmi: 0.2954		ari: 0.2204		f1: 0.3434		
epoch: 031		acc: 0.5697		nmi: 0.3066		ari: 0.2429		f1: 0.3540		
epoch: 032		acc: 0.5697		nmi: 0.3069		ari: 0.2460		f1: 0.3548		
epoch: 033		acc: 0.5737		nmi: 0.2909		ari: 0.2398		f1: 0.3548		
epoch: 034		acc: 0.5857		nmi: 0.3055		ari: 0.2514		f1: 0.3588		
epoch: 035		acc: 0.5857		nmi: 0.3131		ari: 0.2543		f1: 0.3589		
epoch: 036		acc: 0.5817		nmi: 0.3096		ari: 0.2490		f1: 0.3566		
epoch: 037		acc: 0.5817		nmi: 0.2963		ari: 0.2459		f1: 0.3569		
epoch: 038		acc: 0.5817		nmi: 0.2963		ari: 0.2459		f1: 0.3569		
epoch: 039		acc: 0.5817		nmi: 0.2963		ari: 0.2459		f1: 0.3569		
epoch: 040		acc: 0.5817		nmi: 0.2963		ari: 0.2459		f1: 0.3569		
epoch: 041		acc: 0.5817		nmi: 0.2963		ari: 0.2459		f1: 0.3569		
epoch: 042		acc: 0.5857		nmi: 0.3137		ari: 0.2574		f1: 0.3588		
epoch: 043		acc: 0.5817		nmi: 0.2963		ari: 0.2459		f1: 0.3569		
epoch: 044		acc: 0.5896		nmi: 0.3141		ari: 0.2561		f1: 0.3955		
epoch: 045		acc: 0.5857		nmi: 0.3158		ari: 0.2535		f1: 0.3907		
epoch: 046		acc: 0.5896		nmi: 0.3141		ari: 0.2561		f1: 0.3955		
epoch: 047		acc: 0.5896		nmi: 0.3141		ari: 0.2561		f1: 0.3955		
epoch: 048		acc: 0.5857		nmi: 0.3090		ari: 0.2524		f1: 0.3910		
epoch: 049		acc: 0.5896		nmi: 0.3135		ari: 0.2614		f1: 0.3902		
epoch: 050		acc: 0.5777		nmi: 0.2995		ari: 0.2452		f1: 0.3823		
The total number of parameters is: 1.007696M(1e6).
The max memory allocated to model is: 48.95 MB.
Time consuming: 0.55s or 0.01m
****************************************Training loop No.7****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=1703, out_features=512, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.4940		nmi: 0.3088		ari: 0.2070		f1: 0.4073		
epoch: 002		acc: 0.4422		nmi: 0.2120		ari: 0.0872		f1: 0.3281		
epoch: 003		acc: 0.4064		nmi: 0.2783		ari: 0.1256		f1: 0.2410		
epoch: 004		acc: 0.4622		nmi: 0.2958		ari: 0.2151		f1: 0.3500		
epoch: 005		acc: 0.4582		nmi: 0.3084		ari: 0.1773		f1: 0.3228		
epoch: 006		acc: 0.5060		nmi: 0.2553		ari: 0.1691		f1: 0.3724		
epoch: 007		acc: 0.4661		nmi: 0.3031		ari: 0.2071		f1: 0.3676		
epoch: 008		acc: 0.4980		nmi: 0.3393		ari: 0.2607		f1: 0.4095		
epoch: 009		acc: 0.4741		nmi: 0.3270		ari: 0.2414		f1: 0.3829		
epoch: 010		acc: 0.4741		nmi: 0.3220		ari: 0.2396		f1: 0.3803		
epoch: 011		acc: 0.4861		nmi: 0.3277		ari: 0.2385		f1: 0.3830		
epoch: 012		acc: 0.4821		nmi: 0.3125		ari: 0.2247		f1: 0.3736		
epoch: 013		acc: 0.5020		nmi: 0.3059		ari: 0.2295		f1: 0.3879		
epoch: 014		acc: 0.5259		nmi: 0.3146		ari: 0.2404		f1: 0.3806		
epoch: 015		acc: 0.5418		nmi: 0.3257		ari: 0.2527		f1: 0.3800		
epoch: 016		acc: 0.5458		nmi: 0.3092		ari: 0.2485		f1: 0.3760		
epoch: 017		acc: 0.5538		nmi: 0.3186		ari: 0.2587		f1: 0.3821		
epoch: 018		acc: 0.5538		nmi: 0.3189		ari: 0.2490		f1: 0.3803		
epoch: 019		acc: 0.5339		nmi: 0.2941		ari: 0.2204		f1: 0.3726		
epoch: 020		acc: 0.5538		nmi: 0.3102		ari: 0.2425		f1: 0.3750		
epoch: 021		acc: 0.5498		nmi: 0.3102		ari: 0.2473		f1: 0.3799		
epoch: 022		acc: 0.5578		nmi: 0.3135		ari: 0.2555		f1: 0.3888		
epoch: 023		acc: 0.5618		nmi: 0.3248		ari: 0.2633		f1: 0.3923		
epoch: 024		acc: 0.5458		nmi: 0.3009		ari: 0.2388		f1: 0.3862		
epoch: 025		acc: 0.5458		nmi: 0.3193		ari: 0.2508		f1: 0.3658		
epoch: 026		acc: 0.5538		nmi: 0.3027		ari: 0.2408		f1: 0.3644		
epoch: 027		acc: 0.5618		nmi: 0.3182		ari: 0.2460		f1: 0.3859		
epoch: 028		acc: 0.5737		nmi: 0.3248		ari: 0.2553		f1: 0.3919		
epoch: 029		acc: 0.5777		nmi: 0.3289		ari: 0.2534		f1: 0.3946		
epoch: 030		acc: 0.5777		nmi: 0.3218		ari: 0.2504		f1: 0.3651		
epoch: 031		acc: 0.5777		nmi: 0.3092		ari: 0.2431		f1: 0.3842		
epoch: 032		acc: 0.5657		nmi: 0.3116		ari: 0.2329		f1: 0.3578		
epoch: 033		acc: 0.5777		nmi: 0.3117		ari: 0.2403		f1: 0.3921		
epoch: 034		acc: 0.5777		nmi: 0.3119		ari: 0.2433		f1: 0.3615		
epoch: 035		acc: 0.5777		nmi: 0.3005		ari: 0.2378		f1: 0.3571		
epoch: 036		acc: 0.5857		nmi: 0.3164		ari: 0.2512		f1: 0.3818		
epoch: 037		acc: 0.5697		nmi: 0.3003		ari: 0.2293		f1: 0.3521		
epoch: 038		acc: 0.5777		nmi: 0.3018		ari: 0.2386		f1: 0.3572		
epoch: 039		acc: 0.5817		nmi: 0.3078		ari: 0.2410		f1: 0.3917		
epoch: 040		acc: 0.5777		nmi: 0.2982		ari: 0.2375		f1: 0.3555		
epoch: 041		acc: 0.5777		nmi: 0.2971		ari: 0.2396		f1: 0.3573		
epoch: 042		acc: 0.5458		nmi: 0.2867		ari: 0.2237		f1: 0.3567		
epoch: 043		acc: 0.5498		nmi: 0.2901		ari: 0.2304		f1: 0.3598		
epoch: 044		acc: 0.5498		nmi: 0.2957		ari: 0.2355		f1: 0.3620		
epoch: 045		acc: 0.5418		nmi: 0.2897		ari: 0.2280		f1: 0.3591		
epoch: 046		acc: 0.5179		nmi: 0.2815		ari: 0.2074		f1: 0.3501		
epoch: 047		acc: 0.5538		nmi: 0.2881		ari: 0.2272		f1: 0.3685		
epoch: 048		acc: 0.5458		nmi: 0.2839		ari: 0.2227		f1: 0.3676		
epoch: 049		acc: 0.5618		nmi: 0.2954		ari: 0.2357		f1: 0.3616		
epoch: 050		acc: 0.5618		nmi: 0.2875		ari: 0.2252		f1: 0.3530		
The total number of parameters is: 1.007696M(1e6).
The max memory allocated to model is: 48.95 MB.
Time consuming: 0.55s or 0.01m
****************************************Training loop No.8****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=1703, out_features=512, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.4821		nmi: 0.3078		ari: 0.2049		f1: 0.4034		
epoch: 002		acc: 0.4303		nmi: 0.2835		ari: 0.1352		f1: 0.3205		
epoch: 003		acc: 0.4303		nmi: 0.2139		ari: 0.1045		f1: 0.2769		
epoch: 004		acc: 0.4980		nmi: 0.2788		ari: 0.1748		f1: 0.3419		
epoch: 005		acc: 0.4462		nmi: 0.2904		ari: 0.1918		f1: 0.3465		
epoch: 006		acc: 0.3825		nmi: 0.2800		ari: 0.1691		f1: 0.3349		
epoch: 007		acc: 0.4382		nmi: 0.3124		ari: 0.1955		f1: 0.3926		
epoch: 008		acc: 0.4502		nmi: 0.2872		ari: 0.1919		f1: 0.3291		
epoch: 009		acc: 0.4462		nmi: 0.2858		ari: 0.1738		f1: 0.3400		
epoch: 010		acc: 0.4542		nmi: 0.2908		ari: 0.1990		f1: 0.3576		
epoch: 011		acc: 0.4821		nmi: 0.2978		ari: 0.2224		f1: 0.3858		
epoch: 012		acc: 0.5020		nmi: 0.3067		ari: 0.2394		f1: 0.3902		
epoch: 013		acc: 0.4980		nmi: 0.2883		ari: 0.2231		f1: 0.3927		
epoch: 014		acc: 0.5179		nmi: 0.3054		ari: 0.2337		f1: 0.3999		
epoch: 015		acc: 0.5139		nmi: 0.3126		ari: 0.2214		f1: 0.3955		
epoch: 016		acc: 0.5179		nmi: 0.3118		ari: 0.2308		f1: 0.3549		
epoch: 017		acc: 0.5219		nmi: 0.2814		ari: 0.2163		f1: 0.3589		
epoch: 018		acc: 0.5458		nmi: 0.3169		ari: 0.2343		f1: 0.3630		
epoch: 019		acc: 0.5498		nmi: 0.3039		ari: 0.2413		f1: 0.3706		
epoch: 020		acc: 0.5219		nmi: 0.3009		ari: 0.2339		f1: 0.3668		
epoch: 021		acc: 0.5339		nmi: 0.2980		ari: 0.2177		f1: 0.3727		
epoch: 022		acc: 0.5259		nmi: 0.2918		ari: 0.2231		f1: 0.3690		
epoch: 023		acc: 0.5458		nmi: 0.3124		ari: 0.2470		f1: 0.3856		
epoch: 024		acc: 0.5418		nmi: 0.3125		ari: 0.2473		f1: 0.3828		
epoch: 025		acc: 0.5378		nmi: 0.3114		ari: 0.2417		f1: 0.3623		
epoch: 026		acc: 0.5498		nmi: 0.3189		ari: 0.2438		f1: 0.3664		
epoch: 027		acc: 0.5538		nmi: 0.3182		ari: 0.2459		f1: 0.3670		
epoch: 028		acc: 0.5578		nmi: 0.3212		ari: 0.2545		f1: 0.3862		
epoch: 029		acc: 0.5458		nmi: 0.3107		ari: 0.2298		f1: 0.3836		
epoch: 030		acc: 0.5618		nmi: 0.3082		ari: 0.2431		f1: 0.3865		
epoch: 031		acc: 0.5697		nmi: 0.3146		ari: 0.2506		f1: 0.3635		
epoch: 032		acc: 0.5657		nmi: 0.3301		ari: 0.2592		f1: 0.3663		
epoch: 033		acc: 0.5618		nmi: 0.3034		ari: 0.2363		f1: 0.3590		
epoch: 034		acc: 0.5737		nmi: 0.3116		ari: 0.2475		f1: 0.3625		
epoch: 035		acc: 0.5777		nmi: 0.3153		ari: 0.2556		f1: 0.3639		
epoch: 036		acc: 0.5857		nmi: 0.3376		ari: 0.2679		f1: 0.3696		
epoch: 037		acc: 0.5697		nmi: 0.3047		ari: 0.2437		f1: 0.3609		
epoch: 038		acc: 0.5299		nmi: 0.2965		ari: 0.2272		f1: 0.3564		
epoch: 039		acc: 0.5418		nmi: 0.2992		ari: 0.2248		f1: 0.3440		
epoch: 040		acc: 0.5817		nmi: 0.3105		ari: 0.2489		f1: 0.3567		
epoch: 041		acc: 0.5857		nmi: 0.3127		ari: 0.2534		f1: 0.3590		
epoch: 042		acc: 0.5857		nmi: 0.3139		ari: 0.2536		f1: 0.3598		
epoch: 043		acc: 0.5817		nmi: 0.3118		ari: 0.2486		f1: 0.3583		
epoch: 044		acc: 0.5777		nmi: 0.3047		ari: 0.2465		f1: 0.3586		
epoch: 045		acc: 0.5777		nmi: 0.3052		ari: 0.2527		f1: 0.3611		
epoch: 046		acc: 0.5737		nmi: 0.3026		ari: 0.2494		f1: 0.3605		
epoch: 047		acc: 0.5618		nmi: 0.3032		ari: 0.2398		f1: 0.3606		
epoch: 048		acc: 0.4622		nmi: 0.2843		ari: 0.1996		f1: 0.3152		
epoch: 049		acc: 0.5100		nmi: 0.2966		ari: 0.2237		f1: 0.3517		
epoch: 050		acc: 0.5378		nmi: 0.2996		ari: 0.2314		f1: 0.3564		
The total number of parameters is: 1.007696M(1e6).
The max memory allocated to model is: 48.95 MB.
Time consuming: 0.54s or 0.01m
****************************************Training loop No.9****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=1703, out_features=512, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.4821		nmi: 0.3120		ari: 0.2067		f1: 0.3951		
epoch: 002		acc: 0.4821		nmi: 0.3330		ari: 0.2315		f1: 0.3542		
epoch: 003		acc: 0.5179		nmi: 0.3265		ari: 0.2342		f1: 0.3571		
epoch: 004		acc: 0.5179		nmi: 0.3484		ari: 0.2789		f1: 0.4386		
epoch: 005		acc: 0.5020		nmi: 0.3211		ari: 0.2290		f1: 0.3766		
epoch: 006		acc: 0.4701		nmi: 0.3287		ari: 0.2321		f1: 0.3905		
epoch: 007		acc: 0.4661		nmi: 0.3112		ari: 0.2317		f1: 0.4018		
epoch: 008		acc: 0.4861		nmi: 0.3078		ari: 0.2314		f1: 0.3896		
epoch: 009		acc: 0.4980		nmi: 0.3222		ari: 0.2339		f1: 0.3634		
epoch: 010		acc: 0.5100		nmi: 0.3203		ari: 0.2376		f1: 0.3697		
epoch: 011		acc: 0.5060		nmi: 0.3366		ari: 0.2543		f1: 0.3733		
epoch: 012		acc: 0.5100		nmi: 0.3314		ari: 0.2599		f1: 0.3818		
epoch: 013		acc: 0.5179		nmi: 0.3335		ari: 0.2512		f1: 0.3964		
epoch: 014		acc: 0.5179		nmi: 0.3306		ari: 0.2495		f1: 0.3822		
epoch: 015		acc: 0.5299		nmi: 0.3347		ari: 0.2620		f1: 0.3661		
epoch: 016		acc: 0.5339		nmi: 0.3133		ari: 0.2380		f1: 0.3690		
epoch: 017		acc: 0.5618		nmi: 0.3301		ari: 0.2736		f1: 0.3742		
epoch: 018		acc: 0.5657		nmi: 0.3376		ari: 0.2826		f1: 0.3879		
epoch: 019		acc: 0.5578		nmi: 0.3269		ari: 0.2706		f1: 0.3744		
epoch: 020		acc: 0.5498		nmi: 0.3310		ari: 0.2663		f1: 0.3729		
epoch: 021		acc: 0.5299		nmi: 0.3217		ari: 0.2469		f1: 0.3727		
epoch: 022		acc: 0.4622		nmi: 0.3111		ari: 0.2078		f1: 0.3182		
epoch: 023		acc: 0.5219		nmi: 0.3134		ari: 0.2246		f1: 0.3629		
epoch: 024		acc: 0.5578		nmi: 0.3180		ari: 0.2361		f1: 0.3553		
epoch: 025		acc: 0.5737		nmi: 0.3288		ari: 0.2506		f1: 0.3823		
epoch: 026		acc: 0.5697		nmi: 0.3248		ari: 0.2460		f1: 0.3584		
epoch: 027		acc: 0.5857		nmi: 0.3303		ari: 0.2635		f1: 0.3662		
epoch: 028		acc: 0.5976		nmi: 0.3407		ari: 0.2750		f1: 0.3686		
epoch: 029		acc: 0.6016		nmi: 0.3327		ari: 0.2756		f1: 0.3693		
epoch: 030		acc: 0.6096		nmi: 0.3361		ari: 0.2846		f1: 0.3729		
epoch: 031		acc: 0.6016		nmi: 0.3321		ari: 0.2747		f1: 0.3693		
epoch: 032		acc: 0.6056		nmi: 0.3335		ari: 0.2793		f1: 0.3707		
epoch: 033		acc: 0.6056		nmi: 0.3335		ari: 0.2793		f1: 0.3707		
epoch: 034		acc: 0.6135		nmi: 0.3459		ari: 0.2882		f1: 0.4091		
epoch: 035		acc: 0.6056		nmi: 0.3335		ari: 0.2793		f1: 0.3707		
epoch: 036		acc: 0.6056		nmi: 0.3335		ari: 0.2793		f1: 0.3707		
epoch: 037		acc: 0.6056		nmi: 0.3335		ari: 0.2793		f1: 0.3707		
epoch: 038		acc: 0.6056		nmi: 0.3335		ari: 0.2793		f1: 0.3707		
epoch: 039		acc: 0.6056		nmi: 0.3335		ari: 0.2793		f1: 0.3707		
epoch: 040		acc: 0.6056		nmi: 0.3335		ari: 0.2793		f1: 0.3707		
epoch: 041		acc: 0.6096		nmi: 0.3367		ari: 0.2856		f1: 0.3729		
epoch: 042		acc: 0.6096		nmi: 0.3361		ari: 0.2846		f1: 0.3729		
epoch: 043		acc: 0.6056		nmi: 0.3335		ari: 0.2793		f1: 0.3707		
epoch: 044		acc: 0.6056		nmi: 0.3305		ari: 0.2813		f1: 0.3724		
epoch: 045		acc: 0.6096		nmi: 0.3379		ari: 0.2889		f1: 0.3999		
epoch: 046		acc: 0.5578		nmi: 0.3130		ari: 0.2519		f1: 0.3602		
epoch: 047		acc: 0.5936		nmi: 0.3239		ari: 0.2701		f1: 0.3681		
epoch: 048		acc: 0.5896		nmi: 0.3229		ari: 0.2668		f1: 0.3666		
epoch: 049		acc: 0.5936		nmi: 0.3327		ari: 0.2699		f1: 0.3664		
epoch: 050		acc: 0.6016		nmi: 0.3334		ari: 0.2767		f1: 0.3693		
The total number of parameters is: 1.007696M(1e6).
The max memory allocated to model is: 48.95 MB.
Time consuming: 0.54s or 0.01m
****************************************Training loop No.10****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=1703, out_features=512, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.4821		nmi: 0.3163		ari: 0.2110		f1: 0.4172		
epoch: 002		acc: 0.5657		nmi: 0.3191		ari: 0.2331		f1: 0.3702		
epoch: 003		acc: 0.4263		nmi: 0.2779		ari: 0.1410		f1: 0.2548		
epoch: 004		acc: 0.4781		nmi: 0.3286		ari: 0.2285		f1: 0.3626		
epoch: 005		acc: 0.5020		nmi: 0.2815		ari: 0.2022		f1: 0.3691		
epoch: 006		acc: 0.4382		nmi: 0.2796		ari: 0.1857		f1: 0.3424		
epoch: 007		acc: 0.4741		nmi: 0.3360		ari: 0.2462		f1: 0.4020		
epoch: 008		acc: 0.4661		nmi: 0.3104		ari: 0.2276		f1: 0.4037		
epoch: 009		acc: 0.4980		nmi: 0.3105		ari: 0.2398		f1: 0.4202		
epoch: 010		acc: 0.5100		nmi: 0.3188		ari: 0.2480		f1: 0.4194		
epoch: 011		acc: 0.5179		nmi: 0.3154		ari: 0.2467		f1: 0.4009		
epoch: 012		acc: 0.5339		nmi: 0.3206		ari: 0.2542		f1: 0.4074		
epoch: 013		acc: 0.5299		nmi: 0.3002		ari: 0.2449		f1: 0.3975		
epoch: 014		acc: 0.5339		nmi: 0.3131		ari: 0.2517		f1: 0.3603		
epoch: 015		acc: 0.5378		nmi: 0.2992		ari: 0.2404		f1: 0.3762		
epoch: 016		acc: 0.5418		nmi: 0.3086		ari: 0.2441		f1: 0.3833		
epoch: 017		acc: 0.5339		nmi: 0.3062		ari: 0.2426		f1: 0.3814		
epoch: 018		acc: 0.5378		nmi: 0.3171		ari: 0.2559		f1: 0.3670		
epoch: 019		acc: 0.5100		nmi: 0.2879		ari: 0.2194		f1: 0.3718		
epoch: 020		acc: 0.4502		nmi: 0.2843		ari: 0.1890		f1: 0.3305		
epoch: 021		acc: 0.4622		nmi: 0.2792		ari: 0.1892		f1: 0.3241		
epoch: 022		acc: 0.4741		nmi: 0.2780		ari: 0.1894		f1: 0.3245		
epoch: 023		acc: 0.4821		nmi: 0.2725		ari: 0.1835		f1: 0.3274		
epoch: 024		acc: 0.5179		nmi: 0.2836		ari: 0.2118		f1: 0.3424		
epoch: 025		acc: 0.5418		nmi: 0.2919		ari: 0.2229		f1: 0.3668		
epoch: 026		acc: 0.5538		nmi: 0.3012		ari: 0.2268		f1: 0.3738		
epoch: 027		acc: 0.5618		nmi: 0.2914		ari: 0.2279		f1: 0.3674		
epoch: 028		acc: 0.5857		nmi: 0.3070		ari: 0.2576		f1: 0.3766		
epoch: 029		acc: 0.5657		nmi: 0.2965		ari: 0.2330		f1: 0.3532		
epoch: 030		acc: 0.5817		nmi: 0.3115		ari: 0.2487		f1: 0.3579		
epoch: 031		acc: 0.5817		nmi: 0.3057		ari: 0.2472		f1: 0.3582		
epoch: 032		acc: 0.5936		nmi: 0.3191		ari: 0.2646		f1: 0.3635		
epoch: 033		acc: 0.5936		nmi: 0.3178		ari: 0.2638		f1: 0.3634		
epoch: 034		acc: 0.5936		nmi: 0.3178		ari: 0.2638		f1: 0.3634		
epoch: 035		acc: 0.5857		nmi: 0.3093		ari: 0.2545		f1: 0.3606		
epoch: 036		acc: 0.5936		nmi: 0.3178		ari: 0.2638		f1: 0.3634		
epoch: 037		acc: 0.5896		nmi: 0.3010		ari: 0.2551		f1: 0.3613		
epoch: 038		acc: 0.5896		nmi: 0.3010		ari: 0.2551		f1: 0.3613		
epoch: 039		acc: 0.5936		nmi: 0.3034		ari: 0.2599		f1: 0.3636		
epoch: 040		acc: 0.5896		nmi: 0.3010		ari: 0.2551		f1: 0.3613		
epoch: 041		acc: 0.5857		nmi: 0.2918		ari: 0.2484		f1: 0.3590		
epoch: 042		acc: 0.5936		nmi: 0.3124		ari: 0.2651		f1: 0.3636		
epoch: 043		acc: 0.5896		nmi: 0.2990		ari: 0.2570		f1: 0.3638		
epoch: 044		acc: 0.5817		nmi: 0.2947		ari: 0.2514		f1: 0.3635		
epoch: 045		acc: 0.5976		nmi: 0.3221		ari: 0.2751		f1: 0.3916		
epoch: 046		acc: 0.5737		nmi: 0.2895		ari: 0.2483		f1: 0.3614		
epoch: 047		acc: 0.5538		nmi: 0.2929		ari: 0.2464		f1: 0.3646		
epoch: 048		acc: 0.5777		nmi: 0.2948		ari: 0.2459		f1: 0.3578		
epoch: 049		acc: 0.5896		nmi: 0.2983		ari: 0.2565		f1: 0.3630		
epoch: 050		acc: 0.5896		nmi: 0.3010		ari: 0.2551		f1: 0.3613		
The total number of parameters is: 1.007696M(1e6).
The max memory allocated to model is: 48.95 MB.
Time consuming: 0.54s or 0.01m
Namespace(is_pretrain=False, plot_clustering_tsne=False, plot_embedding_heatmap=False, adj_norm=False, adj_loop=True, adj_symmetric=True, desc='default', model_name='SYNC', dataset_name='wisc', root=None, k=None, t=None, loops=10, feature_type='tensor', label_type='npy', adj_type='tensor', seed=325, epsilon=0.0, device='cuda', clusters=5, nodes=251, lr=0.01, max_epoch=50, pretrain_lr=0.001, pretrain_epoch=30, input_dim=1703, log_save_path='./logs/SYNC/wisc/', dataset_path='../data/', clustering_tsne_save_path='./img/clustering/SYNC/wisc/', embedding_heatmap_save_path='./img/heatmap/SYNC/wisc/', pretrain_save_path='./pretrain/pretrain_tigae/SYNC/wisc/', hidden_dim=256, embedding_dim=16, linear_dim=512, beta=1)
Total loops: 10
****************************************Mean value:****************************************
acc: 0.5964±0.0102		nmi: 0.3279±0.0142		ari: 0.2686±0.0130		f1: 0.3819±0.0130
Training over! Punch out!
Loading texas dataset from local
****************************************Training loop No.1****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=1703, out_features=512, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.5410		nmi: 0.2754		ari: 0.1551		f1: 0.3843		
epoch: 002		acc: 0.5082		nmi: 0.1772		ari: 0.0937		f1: 0.2318		
epoch: 003		acc: 0.6393		nmi: 0.2867		ari: 0.3315		f1: 0.3856		
epoch: 004		acc: 0.4262		nmi: 0.1962		ari: 0.0136		f1: 0.2531		
epoch: 005		acc: 0.6284		nmi: 0.2643		ari: 0.3071		f1: 0.4193		
epoch: 006		acc: 0.5738		nmi: 0.2322		ari: 0.2417		f1: 0.3105		
epoch: 007		acc: 0.5082		nmi: 0.1742		ari: 0.0886		f1: 0.2873		
epoch: 008		acc: 0.5191		nmi: 0.1782		ari: 0.1202		f1: 0.2686		
epoch: 009		acc: 0.5792		nmi: 0.2007		ari: 0.2056		f1: 0.2907		
epoch: 010		acc: 0.5683		nmi: 0.1985		ari: 0.2025		f1: 0.2769		
epoch: 011		acc: 0.5792		nmi: 0.2158		ari: 0.2268		f1: 0.2895		
epoch: 012		acc: 0.5738		nmi: 0.1913		ari: 0.2035		f1: 0.2844		
epoch: 013		acc: 0.5628		nmi: 0.1882		ari: 0.1860		f1: 0.2802		
epoch: 014		acc: 0.5683		nmi: 0.2228		ari: 0.2312		f1: 0.2952		
epoch: 015		acc: 0.5574		nmi: 0.2071		ari: 0.2085		f1: 0.3135		
epoch: 016		acc: 0.5519		nmi: 0.1865		ari: 0.1760		f1: 0.3016		
epoch: 017		acc: 0.5574		nmi: 0.1965		ari: 0.1947		f1: 0.2817		
epoch: 018		acc: 0.5628		nmi: 0.1980		ari: 0.2009		f1: 0.2954		
epoch: 019		acc: 0.5519		nmi: 0.1791		ari: 0.1722		f1: 0.2902		
epoch: 020		acc: 0.5410		nmi: 0.1990		ari: 0.1632		f1: 0.2701		
epoch: 021		acc: 0.5410		nmi: 0.1767		ari: 0.1519		f1: 0.2967		
epoch: 022		acc: 0.5574		nmi: 0.1870		ari: 0.1750		f1: 0.2992		
epoch: 023		acc: 0.5410		nmi: 0.1910		ari: 0.1802		f1: 0.2854		
epoch: 024		acc: 0.5628		nmi: 0.1863		ari: 0.2033		f1: 0.3138		
epoch: 025		acc: 0.5574		nmi: 0.1940		ari: 0.1991		f1: 0.3077		
epoch: 026		acc: 0.5683		nmi: 0.2033		ari: 0.2321		f1: 0.3119		
epoch: 027		acc: 0.5464		nmi: 0.2108		ari: 0.2102		f1: 0.3227		
epoch: 028		acc: 0.5410		nmi: 0.2063		ari: 0.1933		f1: 0.3266		
epoch: 029		acc: 0.5027		nmi: 0.1935		ari: 0.1180		f1: 0.2818		
epoch: 030		acc: 0.4973		nmi: 0.1670		ari: 0.1209		f1: 0.2971		
epoch: 031		acc: 0.4918		nmi: 0.1711		ari: 0.1287		f1: 0.2875		
epoch: 032		acc: 0.4863		nmi: 0.1610		ari: 0.1226		f1: 0.2899		
epoch: 033		acc: 0.5137		nmi: 0.1830		ari: 0.1530		f1: 0.3282		
epoch: 034		acc: 0.5027		nmi: 0.1873		ari: 0.1578		f1: 0.3370		
epoch: 035		acc: 0.4863		nmi: 0.2046		ari: 0.1577		f1: 0.3307		
epoch: 036		acc: 0.4863		nmi: 0.1877		ari: 0.1531		f1: 0.3258		
epoch: 037		acc: 0.4699		nmi: 0.1814		ari: 0.1597		f1: 0.3210		
epoch: 038		acc: 0.4481		nmi: 0.1912		ari: 0.1466		f1: 0.3101		
epoch: 039		acc: 0.4536		nmi: 0.1680		ari: 0.0977		f1: 0.3200		
epoch: 040		acc: 0.4262		nmi: 0.1758		ari: 0.1085		f1: 0.3011		
epoch: 041		acc: 0.4699		nmi: 0.2004		ari: 0.1483		f1: 0.3464		
epoch: 042		acc: 0.4317		nmi: 0.1747		ari: 0.1181		f1: 0.3087		
epoch: 043		acc: 0.4481		nmi: 0.1742		ari: 0.1188		f1: 0.3409		
epoch: 044		acc: 0.4426		nmi: 0.1957		ari: 0.1268		f1: 0.3506		
epoch: 045		acc: 0.4317		nmi: 0.1747		ari: 0.1206		f1: 0.3214		
epoch: 046		acc: 0.4645		nmi: 0.2078		ari: 0.1455		f1: 0.3499		
epoch: 047		acc: 0.4645		nmi: 0.2291		ari: 0.1591		f1: 0.3645		
epoch: 048		acc: 0.4754		nmi: 0.1904		ari: 0.1520		f1: 0.3520		
epoch: 049		acc: 0.4481		nmi: 0.1837		ari: 0.1333		f1: 0.3400		
epoch: 050		acc: 0.4262		nmi: 0.1741		ari: 0.1059		f1: 0.3188		
The total number of parameters is: 1.007696M(1e6).
The max memory allocated to model is: 38.71 MB.
Time consuming: 3.2s or 0.05m
****************************************Training loop No.2****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=1703, out_features=512, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.5355		nmi: 0.2605		ari: 0.1604		f1: 0.3780		
epoch: 002		acc: 0.5464		nmi: 0.1997		ari: 0.1673		f1: 0.2459		
epoch: 003		acc: 0.6448		nmi: 0.2601		ari: 0.3260		f1: 0.3822		
epoch: 004		acc: 0.4426		nmi: 0.2059		ari: 0.0373		f1: 0.2654		
epoch: 005		acc: 0.6503		nmi: 0.2777		ari: 0.3507		f1: 0.4309		
epoch: 006		acc: 0.5574		nmi: 0.2186		ari: 0.2086		f1: 0.3072		
epoch: 007		acc: 0.5301		nmi: 0.1991		ari: 0.1258		f1: 0.3387		
epoch: 008		acc: 0.5574		nmi: 0.2138		ari: 0.1788		f1: 0.2916		
epoch: 009		acc: 0.5574		nmi: 0.1745		ari: 0.1655		f1: 0.2607		
epoch: 010		acc: 0.5574		nmi: 0.1801		ari: 0.1835		f1: 0.2645		
epoch: 011		acc: 0.5847		nmi: 0.2135		ari: 0.2349		f1: 0.2926		
epoch: 012		acc: 0.5683		nmi: 0.1888		ari: 0.1892		f1: 0.2720		
epoch: 013		acc: 0.5628		nmi: 0.1978		ari: 0.1947		f1: 0.2762		
epoch: 014		acc: 0.5464		nmi: 0.1724		ari: 0.1526		f1: 0.2742		
epoch: 015		acc: 0.5355		nmi: 0.1883		ari: 0.1489		f1: 0.2588		
epoch: 016		acc: 0.5301		nmi: 0.1652		ari: 0.1374		f1: 0.2799		
epoch: 017		acc: 0.5301		nmi: 0.1726		ari: 0.1381		f1: 0.2684		
epoch: 018		acc: 0.5464		nmi: 0.1755		ari: 0.1668		f1: 0.2868		
epoch: 019		acc: 0.5574		nmi: 0.1926		ari: 0.1851		f1: 0.2807		
epoch: 020		acc: 0.5683		nmi: 0.1934		ari: 0.1999		f1: 0.2938		
epoch: 021		acc: 0.5574		nmi: 0.2064		ari: 0.2090		f1: 0.3099		
epoch: 022		acc: 0.5574		nmi: 0.1820		ari: 0.1938		f1: 0.2915		
epoch: 023		acc: 0.5574		nmi: 0.1946		ari: 0.1827		f1: 0.3477		
epoch: 024		acc: 0.5738		nmi: 0.1958		ari: 0.2230		f1: 0.3214		
epoch: 025		acc: 0.5738		nmi: 0.2035		ari: 0.2338		f1: 0.3185		
epoch: 026		acc: 0.5519		nmi: 0.1910		ari: 0.2109		f1: 0.3040		
epoch: 027		acc: 0.5519		nmi: 0.1852		ari: 0.1918		f1: 0.3107		
epoch: 028		acc: 0.5410		nmi: 0.1843		ari: 0.1793		f1: 0.3083		
epoch: 029		acc: 0.5355		nmi: 0.1894		ari: 0.1856		f1: 0.3061		
epoch: 030		acc: 0.5410		nmi: 0.1742		ari: 0.1771		f1: 0.3261		
epoch: 031		acc: 0.5191		nmi: 0.1895		ari: 0.1448		f1: 0.2996		
epoch: 032		acc: 0.5137		nmi: 0.1822		ari: 0.1548		f1: 0.3168		
epoch: 033		acc: 0.5191		nmi: 0.1751		ari: 0.1821		f1: 0.3179		
epoch: 034		acc: 0.5191		nmi: 0.1885		ari: 0.1690		f1: 0.3165		
epoch: 035		acc: 0.5082		nmi: 0.1863		ari: 0.1658		f1: 0.3281		
epoch: 036		acc: 0.4863		nmi: 0.1849		ari: 0.1306		f1: 0.3041		
epoch: 037		acc: 0.5027		nmi: 0.1860		ari: 0.1630		f1: 0.3239		
epoch: 038		acc: 0.4973		nmi: 0.1797		ari: 0.1368		f1: 0.3197		
epoch: 039		acc: 0.5027		nmi: 0.2015		ari: 0.1701		f1: 0.3402		
epoch: 040		acc: 0.5082		nmi: 0.1922		ari: 0.1761		f1: 0.3455		
epoch: 041		acc: 0.4754		nmi: 0.1794		ari: 0.1409		f1: 0.3231		
epoch: 042		acc: 0.4699		nmi: 0.1911		ari: 0.1575		f1: 0.3355		
epoch: 043		acc: 0.4536		nmi: 0.1834		ari: 0.1302		f1: 0.3265		
epoch: 044		acc: 0.4645		nmi: 0.1865		ari: 0.1415		f1: 0.3324		
epoch: 045		acc: 0.4426		nmi: 0.1840		ari: 0.1114		f1: 0.3178		
epoch: 046		acc: 0.4208		nmi: 0.1675		ari: 0.1146		f1: 0.3065		
epoch: 047		acc: 0.4481		nmi: 0.1840		ari: 0.1211		f1: 0.3340		
epoch: 048		acc: 0.4699		nmi: 0.1982		ari: 0.1521		f1: 0.3449		
epoch: 049		acc: 0.4426		nmi: 0.1940		ari: 0.1322		f1: 0.3476		
epoch: 050		acc: 0.4536		nmi: 0.2051		ari: 0.1496		f1: 0.3359		
The total number of parameters is: 1.007696M(1e6).
The max memory allocated to model is: 47.13 MB.
Time consuming: 0.54s or 0.01m
****************************************Training loop No.3****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=1703, out_features=512, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.5355		nmi: 0.2774		ari: 0.1598		f1: 0.3985		
epoch: 002		acc: 0.5082		nmi: 0.1766		ari: 0.1060		f1: 0.2314		
epoch: 003		acc: 0.6448		nmi: 0.2779		ari: 0.3167		f1: 0.3933		
epoch: 004		acc: 0.4481		nmi: 0.1882		ari: 0.0625		f1: 0.2659		
epoch: 005		acc: 0.6503		nmi: 0.2726		ari: 0.3597		f1: 0.4139		
epoch: 006		acc: 0.5792		nmi: 0.1965		ari: 0.2276		f1: 0.3226		
epoch: 007		acc: 0.5191		nmi: 0.1749		ari: 0.1115		f1: 0.2766		
epoch: 008		acc: 0.5191		nmi: 0.1721		ari: 0.1124		f1: 0.2496		
epoch: 009		acc: 0.5628		nmi: 0.1988		ari: 0.1888		f1: 0.2637		
epoch: 010		acc: 0.5738		nmi: 0.1981		ari: 0.2370		f1: 0.2753		
epoch: 011		acc: 0.6011		nmi: 0.2176		ari: 0.2753		f1: 0.3086		
epoch: 012		acc: 0.5628		nmi: 0.1834		ari: 0.1885		f1: 0.2715		
epoch: 013		acc: 0.5574		nmi: 0.2011		ari: 0.1691		f1: 0.3726		
epoch: 014		acc: 0.5355		nmi: 0.1946		ari: 0.1442		f1: 0.2670		
epoch: 015		acc: 0.5246		nmi: 0.1922		ari: 0.1246		f1: 0.2648		
epoch: 016		acc: 0.5464		nmi: 0.1961		ari: 0.1612		f1: 0.2807		
epoch: 017		acc: 0.5191		nmi: 0.1844		ari: 0.1295		f1: 0.2522		
epoch: 018		acc: 0.5301		nmi: 0.1898		ari: 0.1447		f1: 0.2440		
epoch: 019		acc: 0.5574		nmi: 0.1836		ari: 0.1906		f1: 0.2923		
epoch: 020		acc: 0.5574		nmi: 0.2100		ari: 0.1920		f1: 0.3145		
epoch: 021		acc: 0.5628		nmi: 0.2024		ari: 0.1882		f1: 0.3499		
epoch: 022		acc: 0.5683		nmi: 0.2173		ari: 0.2301		f1: 0.3447		
epoch: 023		acc: 0.5519		nmi: 0.1912		ari: 0.1908		f1: 0.2917		
epoch: 024		acc: 0.5683		nmi: 0.1918		ari: 0.2110		f1: 0.2956		
epoch: 025		acc: 0.5410		nmi: 0.1727		ari: 0.1746		f1: 0.2763		
epoch: 026		acc: 0.5301		nmi: 0.1663		ari: 0.1591		f1: 0.2914		
epoch: 027		acc: 0.5301		nmi: 0.1714		ari: 0.1572		f1: 0.2828		
epoch: 028		acc: 0.5246		nmi: 0.1707		ari: 0.1407		f1: 0.2898		
epoch: 029		acc: 0.5191		nmi: 0.1769		ari: 0.1534		f1: 0.3033		
epoch: 030		acc: 0.5027		nmi: 0.1706		ari: 0.1258		f1: 0.2862		
epoch: 031		acc: 0.5082		nmi: 0.1839		ari: 0.1426		f1: 0.3006		
epoch: 032		acc: 0.5137		nmi: 0.1777		ari: 0.1450		f1: 0.3094		
epoch: 033		acc: 0.5082		nmi: 0.1834		ari: 0.1471		f1: 0.3130		
epoch: 034		acc: 0.5082		nmi: 0.2158		ari: 0.1624		f1: 0.3174		
epoch: 035		acc: 0.4918		nmi: 0.1957		ari: 0.1541		f1: 0.2959		
epoch: 036		acc: 0.4809		nmi: 0.1573		ari: 0.1285		f1: 0.2985		
epoch: 037		acc: 0.4863		nmi: 0.1879		ari: 0.1512		f1: 0.3085		
epoch: 038		acc: 0.4863		nmi: 0.1798		ari: 0.1449		f1: 0.3199		
epoch: 039		acc: 0.4645		nmi: 0.1585		ari: 0.1282		f1: 0.3187		
epoch: 040		acc: 0.4536		nmi: 0.1746		ari: 0.1257		f1: 0.3109		
epoch: 041		acc: 0.4699		nmi: 0.1792		ari: 0.1347		f1: 0.3270		
epoch: 042		acc: 0.4809		nmi: 0.1753		ari: 0.1318		f1: 0.3446		
epoch: 043		acc: 0.4590		nmi: 0.1737		ari: 0.1199		f1: 0.3311		
epoch: 044		acc: 0.4699		nmi: 0.1819		ari: 0.1516		f1: 0.3371		
epoch: 045		acc: 0.4481		nmi: 0.1658		ari: 0.1241		f1: 0.3258		
epoch: 046		acc: 0.4426		nmi: 0.1613		ari: 0.1066		f1: 0.3204		
epoch: 047		acc: 0.4481		nmi: 0.1911		ari: 0.1240		f1: 0.3353		
epoch: 048		acc: 0.4208		nmi: 0.1583		ari: 0.1037		f1: 0.3153		
epoch: 049		acc: 0.4044		nmi: 0.1537		ari: 0.0846		f1: 0.3017		
epoch: 050		acc: 0.4262		nmi: 0.1574		ari: 0.0858		f1: 0.3151		
The total number of parameters is: 1.007696M(1e6).
The max memory allocated to model is: 47.13 MB.
Time consuming: 0.53s or 0.01m
****************************************Training loop No.4****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=1703, out_features=512, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.5355		nmi: 0.2623		ari: 0.1572		f1: 0.3822		
epoch: 002		acc: 0.5519		nmi: 0.2115		ari: 0.2026		f1: 0.2471		
epoch: 003		acc: 0.6557		nmi: 0.2792		ari: 0.3176		f1: 0.3991		
epoch: 004		acc: 0.4098		nmi: 0.2071		ari: 0.0284		f1: 0.2509		
epoch: 005		acc: 0.5847		nmi: 0.2715		ari: 0.3175		f1: 0.3864		
epoch: 006		acc: 0.5738		nmi: 0.1962		ari: 0.2275		f1: 0.3238		
epoch: 007		acc: 0.5082		nmi: 0.2024		ari: 0.1176		f1: 0.3195		
epoch: 008		acc: 0.5246		nmi: 0.1952		ari: 0.1491		f1: 0.2703		
epoch: 009		acc: 0.5738		nmi: 0.2055		ari: 0.2146		f1: 0.2952		
epoch: 010		acc: 0.5847		nmi: 0.2161		ari: 0.2429		f1: 0.3064		
epoch: 011		acc: 0.5847		nmi: 0.2070		ari: 0.2384		f1: 0.3032		
epoch: 012		acc: 0.5792		nmi: 0.2138		ari: 0.2276		f1: 0.3093		
epoch: 013		acc: 0.5410		nmi: 0.1878		ari: 0.1694		f1: 0.3309		
epoch: 014		acc: 0.5355		nmi: 0.1997		ari: 0.1577		f1: 0.2965		
epoch: 015		acc: 0.4973		nmi: 0.1629		ari: 0.0934		f1: 0.2790		
epoch: 016		acc: 0.5410		nmi: 0.1984		ari: 0.1702		f1: 0.2845		
epoch: 017		acc: 0.5628		nmi: 0.2175		ari: 0.2035		f1: 0.3716		
epoch: 018		acc: 0.5464		nmi: 0.1783		ari: 0.1686		f1: 0.2863		
epoch: 019		acc: 0.5410		nmi: 0.1991		ari: 0.1777		f1: 0.2912		
epoch: 020		acc: 0.5410		nmi: 0.1910		ari: 0.1626		f1: 0.2802		
epoch: 021		acc: 0.5355		nmi: 0.1856		ari: 0.1761		f1: 0.2846		
epoch: 022		acc: 0.5464		nmi: 0.1972		ari: 0.1761		f1: 0.3052		
epoch: 023		acc: 0.5410		nmi: 0.1946		ari: 0.1780		f1: 0.2980		
epoch: 024		acc: 0.5301		nmi: 0.1844		ari: 0.1607		f1: 0.3066		
epoch: 025		acc: 0.5519		nmi: 0.1952		ari: 0.1973		f1: 0.3133		
epoch: 026		acc: 0.5410		nmi: 0.1893		ari: 0.1819		f1: 0.3321		
epoch: 027		acc: 0.5246		nmi: 0.2022		ari: 0.1872		f1: 0.3136		
epoch: 028		acc: 0.5027		nmi: 0.1791		ari: 0.1503		f1: 0.2957		
epoch: 029		acc: 0.5027		nmi: 0.1886		ari: 0.1575		f1: 0.2965		
epoch: 030		acc: 0.5191		nmi: 0.1852		ari: 0.1749		f1: 0.3384		
epoch: 031		acc: 0.5246		nmi: 0.1961		ari: 0.1722		f1: 0.3241		
epoch: 032		acc: 0.5082		nmi: 0.2067		ari: 0.1843		f1: 0.3284		
epoch: 033		acc: 0.4973		nmi: 0.1913		ari: 0.1556		f1: 0.3314		
epoch: 034		acc: 0.4918		nmi: 0.2001		ari: 0.1620		f1: 0.3260		
epoch: 035		acc: 0.4754		nmi: 0.1964		ari: 0.1437		f1: 0.3214		
epoch: 036		acc: 0.4699		nmi: 0.1825		ari: 0.1264		f1: 0.3131		
epoch: 037		acc: 0.4481		nmi: 0.1961		ari: 0.1329		f1: 0.3082		
epoch: 038		acc: 0.4426		nmi: 0.1947		ari: 0.1197		f1: 0.3180		
epoch: 039		acc: 0.4645		nmi: 0.1861		ari: 0.1470		f1: 0.3278		
epoch: 040		acc: 0.4699		nmi: 0.1942		ari: 0.1666		f1: 0.3255		
epoch: 041		acc: 0.4590		nmi: 0.2128		ari: 0.1457		f1: 0.3400		
epoch: 042		acc: 0.4372		nmi: 0.1952		ari: 0.1193		f1: 0.3120		
epoch: 043		acc: 0.4426		nmi: 0.1949		ari: 0.1335		f1: 0.3275		
epoch: 044		acc: 0.4590		nmi: 0.1769		ari: 0.1325		f1: 0.3403		
epoch: 045		acc: 0.4153		nmi: 0.1603		ari: 0.0972		f1: 0.3171		
epoch: 046		acc: 0.4262		nmi: 0.1838		ari: 0.1272		f1: 0.3172		
epoch: 047		acc: 0.4208		nmi: 0.1696		ari: 0.1112		f1: 0.3165		
epoch: 048		acc: 0.4536		nmi: 0.2067		ari: 0.1321		f1: 0.3479		
epoch: 049		acc: 0.4590		nmi: 0.1836		ari: 0.1390		f1: 0.3501		
epoch: 050		acc: 0.4044		nmi: 0.1655		ari: 0.0989		f1: 0.3112		
The total number of parameters is: 1.007696M(1e6).
The max memory allocated to model is: 47.13 MB.
Time consuming: 0.53s or 0.01m
****************************************Training loop No.5****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=1703, out_features=512, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.5355		nmi: 0.2589		ari: 0.1723		f1: 0.3679		
epoch: 002		acc: 0.5355		nmi: 0.1884		ari: 0.1560		f1: 0.2413		
epoch: 003		acc: 0.6284		nmi: 0.2523		ari: 0.2890		f1: 0.3765		
epoch: 004		acc: 0.3825		nmi: 0.1789		ari: 0.0054		f1: 0.2312		
epoch: 005		acc: 0.4536		nmi: 0.2064		ari: 0.1569		f1: 0.3088		
epoch: 006		acc: 0.5628		nmi: 0.2124		ari: 0.2202		f1: 0.3320		
epoch: 007		acc: 0.5301		nmi: 0.2059		ari: 0.1377		f1: 0.2970		
epoch: 008		acc: 0.5410		nmi: 0.2022		ari: 0.1600		f1: 0.3255		
epoch: 009		acc: 0.5628		nmi: 0.1846		ari: 0.1833		f1: 0.2821		
epoch: 010		acc: 0.5464		nmi: 0.1618		ari: 0.1597		f1: 0.2574		
epoch: 011		acc: 0.5847		nmi: 0.1895		ari: 0.2129		f1: 0.2994		
epoch: 012		acc: 0.5574		nmi: 0.1760		ari: 0.1767		f1: 0.2694		
epoch: 013		acc: 0.5464		nmi: 0.1734		ari: 0.1583		f1: 0.2797		
epoch: 014		acc: 0.5301		nmi: 0.1684		ari: 0.1457		f1: 0.2836		
epoch: 015		acc: 0.5191		nmi: 0.1656		ari: 0.1275		f1: 0.2778		
epoch: 016		acc: 0.5191		nmi: 0.1810		ari: 0.1286		f1: 0.2635		
epoch: 017		acc: 0.5519		nmi: 0.2015		ari: 0.1879		f1: 0.3312		
epoch: 018		acc: 0.5519		nmi: 0.2121		ari: 0.1889		f1: 0.3190		
epoch: 019		acc: 0.5574		nmi: 0.2197		ari: 0.2009		f1: 0.3465		
epoch: 020		acc: 0.5355		nmi: 0.1898		ari: 0.1732		f1: 0.3130		
epoch: 021		acc: 0.5191		nmi: 0.1769		ari: 0.1292		f1: 0.2710		
epoch: 022		acc: 0.5027		nmi: 0.1787		ari: 0.1155		f1: 0.2699		
epoch: 023		acc: 0.5082		nmi: 0.1639		ari: 0.1287		f1: 0.2939		
epoch: 024		acc: 0.5027		nmi: 0.1698		ari: 0.1278		f1: 0.2844		
epoch: 025		acc: 0.5082		nmi: 0.1822		ari: 0.1294		f1: 0.2948		
epoch: 026		acc: 0.5082		nmi: 0.1711		ari: 0.1617		f1: 0.3035		
epoch: 027		acc: 0.5027		nmi: 0.1837		ari: 0.1456		f1: 0.3113		
epoch: 028		acc: 0.5027		nmi: 0.1850		ari: 0.1559		f1: 0.2939		
epoch: 029		acc: 0.4973		nmi: 0.1619		ari: 0.1419		f1: 0.3269		
epoch: 030		acc: 0.4699		nmi: 0.1664		ari: 0.1133		f1: 0.2970		
epoch: 031		acc: 0.4973		nmi: 0.1911		ari: 0.1280		f1: 0.3379		
epoch: 032		acc: 0.4973		nmi: 0.2074		ari: 0.1503		f1: 0.3417		
epoch: 033		acc: 0.4809		nmi: 0.1808		ari: 0.1200		f1: 0.3222		
epoch: 034		acc: 0.4809		nmi: 0.1742		ari: 0.1251		f1: 0.3148		
epoch: 035		acc: 0.4426		nmi: 0.1724		ari: 0.1180		f1: 0.3039		
epoch: 036		acc: 0.4699		nmi: 0.1772		ari: 0.1300		f1: 0.3395		
epoch: 037		acc: 0.4317		nmi: 0.1683		ari: 0.1081		f1: 0.3135		
epoch: 038		acc: 0.4754		nmi: 0.1779		ari: 0.1415		f1: 0.3492		
epoch: 039		acc: 0.4590		nmi: 0.1695		ari: 0.1369		f1: 0.3388		
epoch: 040		acc: 0.4481		nmi: 0.1701		ari: 0.1181		f1: 0.3369		
epoch: 041		acc: 0.4372		nmi: 0.1585		ari: 0.1005		f1: 0.3292		
epoch: 042		acc: 0.4372		nmi: 0.1735		ari: 0.1145		f1: 0.3297		
epoch: 043		acc: 0.4536		nmi: 0.1767		ari: 0.1226		f1: 0.3470		
epoch: 044		acc: 0.4372		nmi: 0.1767		ari: 0.1193		f1: 0.3376		
epoch: 045		acc: 0.4426		nmi: 0.1689		ari: 0.1134		f1: 0.3326		
epoch: 046		acc: 0.4262		nmi: 0.1731		ari: 0.1107		f1: 0.3296		
epoch: 047		acc: 0.4317		nmi: 0.1588		ari: 0.1019		f1: 0.3298		
epoch: 048		acc: 0.4153		nmi: 0.1602		ari: 0.0974		f1: 0.3133		
epoch: 049		acc: 0.4481		nmi: 0.1697		ari: 0.1176		f1: 0.3447		
epoch: 050		acc: 0.4426		nmi: 0.1900		ari: 0.1286		f1: 0.3336		
The total number of parameters is: 1.007696M(1e6).
The max memory allocated to model is: 47.13 MB.
Time consuming: 0.53s or 0.01m
****************************************Training loop No.6****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=1703, out_features=512, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.5410		nmi: 0.2587		ari: 0.1733		f1: 0.3849		
epoch: 002		acc: 0.4809		nmi: 0.2032		ari: 0.0425		f1: 0.2713		
epoch: 003		acc: 0.6339		nmi: 0.2826		ari: 0.3201		f1: 0.3847		
epoch: 004		acc: 0.3989		nmi: 0.1851		ari: -0.0269		f1: 0.2372		
epoch: 005		acc: 0.5738		nmi: 0.2207		ari: 0.2724		f1: 0.3536		
epoch: 006		acc: 0.5628		nmi: 0.1885		ari: 0.2197		f1: 0.3272		
epoch: 007		acc: 0.5246		nmi: 0.1781		ari: 0.1230		f1: 0.2865		
epoch: 008		acc: 0.5464		nmi: 0.1811		ari: 0.1404		f1: 0.2955		
epoch: 009		acc: 0.5628		nmi: 0.1986		ari: 0.1835		f1: 0.2962		
epoch: 010		acc: 0.5574		nmi: 0.1701		ari: 0.1863		f1: 0.2704		
epoch: 011		acc: 0.5628		nmi: 0.1901		ari: 0.1991		f1: 0.2719		
epoch: 012		acc: 0.5792		nmi: 0.2009		ari: 0.2243		f1: 0.2882		
epoch: 013		acc: 0.5738		nmi: 0.2169		ari: 0.2156		f1: 0.2971		
epoch: 014		acc: 0.5683		nmi: 0.2200		ari: 0.2086		f1: 0.3718		
epoch: 015		acc: 0.5738		nmi: 0.2089		ari: 0.2138		f1: 0.3075		
epoch: 016		acc: 0.5519		nmi: 0.1959		ari: 0.1718		f1: 0.2734		
epoch: 017		acc: 0.5464		nmi: 0.1981		ari: 0.1778		f1: 0.2626		
epoch: 018		acc: 0.5464		nmi: 0.1898		ari: 0.1710		f1: 0.2722		
epoch: 019		acc: 0.5574		nmi: 0.2093		ari: 0.2047		f1: 0.2833		
epoch: 020		acc: 0.5628		nmi: 0.2089		ari: 0.1982		f1: 0.2872		
epoch: 021		acc: 0.5519		nmi: 0.1958		ari: 0.1770		f1: 0.2721		
epoch: 022		acc: 0.5628		nmi: 0.1960		ari: 0.1935		f1: 0.3174		
epoch: 023		acc: 0.5574		nmi: 0.1845		ari: 0.1873		f1: 0.2912		
epoch: 024		acc: 0.5628		nmi: 0.2002		ari: 0.2094		f1: 0.3288		
epoch: 025		acc: 0.5683		nmi: 0.2069		ari: 0.2095		f1: 0.3696		
epoch: 026		acc: 0.5574		nmi: 0.1990		ari: 0.1909		f1: 0.2759		
epoch: 027		acc: 0.5519		nmi: 0.1812		ari: 0.1990		f1: 0.3055		
epoch: 028		acc: 0.5519		nmi: 0.1834		ari: 0.2154		f1: 0.3070		
epoch: 029		acc: 0.5410		nmi: 0.1967		ari: 0.1720		f1: 0.3298		
epoch: 030		acc: 0.5191		nmi: 0.1828		ari: 0.1530		f1: 0.3340		
epoch: 031		acc: 0.5246		nmi: 0.1930		ari: 0.1455		f1: 0.3170		
epoch: 032		acc: 0.4973		nmi: 0.1524		ari: 0.1195		f1: 0.2824		
epoch: 033		acc: 0.5191		nmi: 0.1809		ari: 0.1630		f1: 0.3488		
epoch: 034		acc: 0.5137		nmi: 0.1810		ari: 0.1584		f1: 0.3099		
epoch: 035		acc: 0.5082		nmi: 0.1835		ari: 0.1545		f1: 0.3531		
epoch: 036		acc: 0.4809		nmi: 0.1803		ari: 0.1385		f1: 0.3271		
epoch: 037		acc: 0.4754		nmi: 0.1730		ari: 0.1346		f1: 0.3173		
epoch: 038		acc: 0.4699		nmi: 0.1644		ari: 0.1257		f1: 0.3144		
epoch: 039		acc: 0.4809		nmi: 0.1732		ari: 0.1439		f1: 0.3347		
epoch: 040		acc: 0.4918		nmi: 0.1809		ari: 0.1594		f1: 0.3503		
epoch: 041		acc: 0.4481		nmi: 0.1696		ari: 0.1173		f1: 0.3120		
epoch: 042		acc: 0.4645		nmi: 0.1670		ari: 0.1164		f1: 0.3352		
epoch: 043		acc: 0.4536		nmi: 0.1777		ari: 0.1224		f1: 0.3291		
epoch: 044		acc: 0.4645		nmi: 0.1749		ari: 0.1254		f1: 0.3393		
epoch: 045		acc: 0.4590		nmi: 0.1760		ari: 0.1150		f1: 0.3361		
epoch: 046		acc: 0.4699		nmi: 0.1818		ari: 0.1417		f1: 0.3457		
epoch: 047		acc: 0.4536		nmi: 0.1827		ari: 0.1236		f1: 0.3406		
epoch: 048		acc: 0.4699		nmi: 0.1840		ari: 0.1295		f1: 0.3605		
epoch: 049		acc: 0.4481		nmi: 0.1818		ari: 0.1285		f1: 0.3316		
epoch: 050		acc: 0.4590		nmi: 0.1837		ari: 0.1245		f1: 0.3576		
The total number of parameters is: 1.007696M(1e6).
The max memory allocated to model is: 47.13 MB.
Time consuming: 0.52s or 0.01m
****************************************Training loop No.7****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=1703, out_features=512, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.5246		nmi: 0.2388		ari: 0.1390		f1: 0.3718		
epoch: 002		acc: 0.5082		nmi: 0.1734		ari: 0.1085		f1: 0.2310		
epoch: 003		acc: 0.6393		nmi: 0.2658		ari: 0.3113		f1: 0.3870		
epoch: 004		acc: 0.4317		nmi: 0.2128		ari: 0.0724		f1: 0.2599		
epoch: 005		acc: 0.5956		nmi: 0.2501		ari: 0.3242		f1: 0.3934		
epoch: 006		acc: 0.5628		nmi: 0.2095		ari: 0.2055		f1: 0.3151		
epoch: 007		acc: 0.5246		nmi: 0.2192		ari: 0.1271		f1: 0.3076		
epoch: 008		acc: 0.5464		nmi: 0.1861		ari: 0.1475		f1: 0.3085		
epoch: 009		acc: 0.5574		nmi: 0.1930		ari: 0.1905		f1: 0.2813		
epoch: 010		acc: 0.5847		nmi: 0.1978		ari: 0.2368		f1: 0.3043		
epoch: 011		acc: 0.5792		nmi: 0.1952		ari: 0.2379		f1: 0.2887		
epoch: 012		acc: 0.5683		nmi: 0.1900		ari: 0.2492		f1: 0.3095		
epoch: 013		acc: 0.5792		nmi: 0.2031		ari: 0.2163		f1: 0.3296		
epoch: 014		acc: 0.5355		nmi: 0.1848		ari: 0.1753		f1: 0.2749		
epoch: 015		acc: 0.5464		nmi: 0.1868		ari: 0.1707		f1: 0.2970		
epoch: 016		acc: 0.5574		nmi: 0.1919		ari: 0.1845		f1: 0.2851		
epoch: 017		acc: 0.5355		nmi: 0.2019		ari: 0.1670		f1: 0.2900		
epoch: 018		acc: 0.5519		nmi: 0.1892		ari: 0.1765		f1: 0.2906		
epoch: 019		acc: 0.5410		nmi: 0.1900		ari: 0.1730		f1: 0.3320		
epoch: 020		acc: 0.5464		nmi: 0.1852		ari: 0.1735		f1: 0.2994		
epoch: 021		acc: 0.5355		nmi: 0.1766		ari: 0.1771		f1: 0.2762		
epoch: 022		acc: 0.5355		nmi: 0.1748		ari: 0.1704		f1: 0.2943		
epoch: 023		acc: 0.5574		nmi: 0.1900		ari: 0.2189		f1: 0.3058		
epoch: 024		acc: 0.5355		nmi: 0.1836		ari: 0.1824		f1: 0.2967		
epoch: 025		acc: 0.5191		nmi: 0.1828		ari: 0.1530		f1: 0.2949		
epoch: 026		acc: 0.5301		nmi: 0.1827		ari: 0.1438		f1: 0.3081		
epoch: 027		acc: 0.5301		nmi: 0.1866		ari: 0.1732		f1: 0.3018		
epoch: 028		acc: 0.5301		nmi: 0.1980		ari: 0.1650		f1: 0.3067		
epoch: 029		acc: 0.5301		nmi: 0.1876		ari: 0.1685		f1: 0.3259		
epoch: 030		acc: 0.5301		nmi: 0.1854		ari: 0.1893		f1: 0.3264		
epoch: 031		acc: 0.5301		nmi: 0.2067		ari: 0.1926		f1: 0.3298		
epoch: 032		acc: 0.5082		nmi: 0.1928		ari: 0.1775		f1: 0.3380		
epoch: 033		acc: 0.5027		nmi: 0.1862		ari: 0.1609		f1: 0.3345		
epoch: 034		acc: 0.4809		nmi: 0.1820		ari: 0.1552		f1: 0.3260		
epoch: 035		acc: 0.4590		nmi: 0.1652		ari: 0.1279		f1: 0.3098		
epoch: 036		acc: 0.4481		nmi: 0.1799		ari: 0.1161		f1: 0.3165		
epoch: 037		acc: 0.4481		nmi: 0.1514		ari: 0.1075		f1: 0.3159		
epoch: 038		acc: 0.4754		nmi: 0.1743		ari: 0.1483		f1: 0.3397		
epoch: 039		acc: 0.4481		nmi: 0.1822		ari: 0.1223		f1: 0.3158		
epoch: 040		acc: 0.4536		nmi: 0.1689		ari: 0.1201		f1: 0.3354		
epoch: 041		acc: 0.4426		nmi: 0.1811		ari: 0.1225		f1: 0.3353		
epoch: 042		acc: 0.4208		nmi: 0.1670		ari: 0.0988		f1: 0.3147		
epoch: 043		acc: 0.4153		nmi: 0.1663		ari: 0.0832		f1: 0.3147		
epoch: 044		acc: 0.4481		nmi: 0.2061		ari: 0.1334		f1: 0.3405		
epoch: 045		acc: 0.4372		nmi: 0.1735		ari: 0.1075		f1: 0.3376		
epoch: 046		acc: 0.4426		nmi: 0.1897		ari: 0.1213		f1: 0.3265		
epoch: 047		acc: 0.4153		nmi: 0.1650		ari: 0.0913		f1: 0.3205		
epoch: 048		acc: 0.4426		nmi: 0.1844		ari: 0.1112		f1: 0.3322		
epoch: 049		acc: 0.4426		nmi: 0.1896		ari: 0.1190		f1: 0.3299		
epoch: 050		acc: 0.4426		nmi: 0.1752		ari: 0.1111		f1: 0.3368		
The total number of parameters is: 1.007696M(1e6).
The max memory allocated to model is: 47.13 MB.
Time consuming: 0.52s or 0.01m
****************************************Training loop No.8****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=1703, out_features=512, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.5519		nmi: 0.2681		ari: 0.1797		f1: 0.3814		
epoch: 002		acc: 0.5246		nmi: 0.1942		ari: 0.1267		f1: 0.2379		
epoch: 003		acc: 0.6448		nmi: 0.2852		ari: 0.3373		f1: 0.3889		
epoch: 004		acc: 0.4044		nmi: 0.1961		ari: 0.0316		f1: 0.2440		
epoch: 005		acc: 0.6066		nmi: 0.2508		ari: 0.3216		f1: 0.4009		
epoch: 006		acc: 0.5683		nmi: 0.2173		ari: 0.2287		f1: 0.3330		
epoch: 007		acc: 0.5027		nmi: 0.1816		ari: 0.0931		f1: 0.2756		
epoch: 008		acc: 0.5410		nmi: 0.1964		ari: 0.1426		f1: 0.2582		
epoch: 009		acc: 0.5683		nmi: 0.1919		ari: 0.2083		f1: 0.2646		
epoch: 010		acc: 0.5847		nmi: 0.2271		ari: 0.2552		f1: 0.2744		
epoch: 011		acc: 0.5847		nmi: 0.1977		ari: 0.2397		f1: 0.3044		
epoch: 012		acc: 0.5738		nmi: 0.2175		ari: 0.2104		f1: 0.2866		
epoch: 013		acc: 0.5574		nmi: 0.1978		ari: 0.1878		f1: 0.2628		
epoch: 014		acc: 0.5519		nmi: 0.1955		ari: 0.1775		f1: 0.2608		
epoch: 015		acc: 0.5519		nmi: 0.1994		ari: 0.1846		f1: 0.2881		
epoch: 016		acc: 0.5410		nmi: 0.1944		ari: 0.1664		f1: 0.2600		
epoch: 017		acc: 0.5519		nmi: 0.1780		ari: 0.1851		f1: 0.2786		
epoch: 018		acc: 0.5464		nmi: 0.2015		ari: 0.1684		f1: 0.3251		
epoch: 019		acc: 0.5519		nmi: 0.2041		ari: 0.1728		f1: 0.3400		
epoch: 020		acc: 0.5574		nmi: 0.1966		ari: 0.2044		f1: 0.2966		
epoch: 021		acc: 0.5464		nmi: 0.1963		ari: 0.1878		f1: 0.3267		
epoch: 022		acc: 0.5792		nmi: 0.2311		ari: 0.2226		f1: 0.3648		
epoch: 023		acc: 0.5410		nmi: 0.1951		ari: 0.1562		f1: 0.2847		
epoch: 024		acc: 0.5464		nmi: 0.1982		ari: 0.1763		f1: 0.2780		
epoch: 025		acc: 0.5574		nmi: 0.2024		ari: 0.1902		f1: 0.3647		
epoch: 026		acc: 0.5355		nmi: 0.1930		ari: 0.1769		f1: 0.3124		
epoch: 027		acc: 0.5519		nmi: 0.2017		ari: 0.2135		f1: 0.2918		
epoch: 028		acc: 0.5410		nmi: 0.2062		ari: 0.1808		f1: 0.2708		
epoch: 029		acc: 0.5628		nmi: 0.1912		ari: 0.2020		f1: 0.3197		
epoch: 030		acc: 0.5410		nmi: 0.1893		ari: 0.1804		f1: 0.3044		
epoch: 031		acc: 0.5410		nmi: 0.1930		ari: 0.2018		f1: 0.3107		
epoch: 032		acc: 0.5246		nmi: 0.2022		ari: 0.1758		f1: 0.3363		
epoch: 033		acc: 0.5082		nmi: 0.1823		ari: 0.1364		f1: 0.2916		
epoch: 034		acc: 0.5027		nmi: 0.1895		ari: 0.1609		f1: 0.2954		
epoch: 035		acc: 0.5137		nmi: 0.1999		ari: 0.1753		f1: 0.3122		
epoch: 036		acc: 0.5191		nmi: 0.1940		ari: 0.1715		f1: 0.3209		
epoch: 037		acc: 0.5246		nmi: 0.1982		ari: 0.1806		f1: 0.3350		
epoch: 038		acc: 0.5027		nmi: 0.1824		ari: 0.1542		f1: 0.3154		
epoch: 039		acc: 0.5082		nmi: 0.2119		ari: 0.1908		f1: 0.3431		
epoch: 040		acc: 0.4809		nmi: 0.1922		ari: 0.1543		f1: 0.3256		
epoch: 041		acc: 0.4918		nmi: 0.1943		ari: 0.1575		f1: 0.3296		
epoch: 042		acc: 0.4754		nmi: 0.2059		ari: 0.1620		f1: 0.3400		
epoch: 043		acc: 0.4863		nmi: 0.1959		ari: 0.1705		f1: 0.3481		
epoch: 044		acc: 0.4918		nmi: 0.2068		ari: 0.1815		f1: 0.3562		
epoch: 045		acc: 0.4809		nmi: 0.1897		ari: 0.1591		f1: 0.3575		
epoch: 046		acc: 0.4590		nmi: 0.1949		ari: 0.1488		f1: 0.3203		
epoch: 047		acc: 0.4536		nmi: 0.1857		ari: 0.1268		f1: 0.3382		
epoch: 048		acc: 0.4809		nmi: 0.2172		ari: 0.1704		f1: 0.3727		
epoch: 049		acc: 0.4809		nmi: 0.1871		ari: 0.1561		f1: 0.3457		
epoch: 050		acc: 0.4699		nmi: 0.2058		ari: 0.1627		f1: 0.3540		
The total number of parameters is: 1.007696M(1e6).
The max memory allocated to model is: 47.13 MB.
Time consuming: 0.52s or 0.01m
****************************************Training loop No.9****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=1703, out_features=512, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.5355		nmi: 0.2479		ari: 0.1675		f1: 0.3672		
epoch: 002		acc: 0.5246		nmi: 0.1909		ari: 0.1528		f1: 0.2739		
epoch: 003		acc: 0.6503		nmi: 0.2755		ari: 0.3190		f1: 0.3916		
epoch: 004		acc: 0.3825		nmi: 0.1745		ari: -0.0227		f1: 0.2297		
epoch: 005		acc: 0.5574		nmi: 0.2224		ari: 0.2429		f1: 0.3755		
epoch: 006		acc: 0.5847		nmi: 0.2040		ari: 0.2440		f1: 0.3202		
epoch: 007		acc: 0.5410		nmi: 0.1776		ari: 0.1395		f1: 0.2837		
epoch: 008		acc: 0.5519		nmi: 0.1950		ari: 0.1621		f1: 0.2795		
epoch: 009		acc: 0.5738		nmi: 0.1869		ari: 0.1892		f1: 0.2867		
epoch: 010		acc: 0.5792		nmi: 0.1927		ari: 0.2166		f1: 0.2924		
epoch: 011		acc: 0.5683		nmi: 0.1998		ari: 0.1949		f1: 0.2761		
epoch: 012		acc: 0.5738		nmi: 0.1992		ari: 0.2032		f1: 0.2848		
epoch: 013		acc: 0.5683		nmi: 0.1898		ari: 0.1977		f1: 0.2720		
epoch: 014		acc: 0.5464		nmi: 0.1930		ari: 0.1688		f1: 0.2489		
epoch: 015		acc: 0.5519		nmi: 0.1883		ari: 0.1667		f1: 0.2614		
epoch: 016		acc: 0.5628		nmi: 0.2023		ari: 0.1963		f1: 0.2938		
epoch: 017		acc: 0.5574		nmi: 0.1983		ari: 0.1771		f1: 0.2809		
epoch: 018		acc: 0.5519		nmi: 0.1882		ari: 0.1734		f1: 0.2731		
epoch: 019		acc: 0.5464		nmi: 0.1929		ari: 0.1736		f1: 0.2791		
epoch: 020		acc: 0.5574		nmi: 0.2019		ari: 0.1937		f1: 0.2911		
epoch: 021		acc: 0.5464		nmi: 0.1646		ari: 0.1498		f1: 0.2682		
epoch: 022		acc: 0.5628		nmi: 0.1841		ari: 0.1925		f1: 0.3032		
epoch: 023		acc: 0.5628		nmi: 0.1973		ari: 0.2025		f1: 0.3158		
epoch: 024		acc: 0.5574		nmi: 0.1861		ari: 0.1917		f1: 0.3056		
epoch: 025		acc: 0.5410		nmi: 0.1771		ari: 0.1538		f1: 0.3045		
epoch: 026		acc: 0.5301		nmi: 0.1773		ari: 0.1582		f1: 0.2997		
epoch: 027		acc: 0.5137		nmi: 0.1702		ari: 0.1257		f1: 0.2796		
epoch: 028		acc: 0.5137		nmi: 0.1713		ari: 0.1377		f1: 0.2911		
epoch: 029		acc: 0.5191		nmi: 0.1828		ari: 0.1438		f1: 0.3056		
epoch: 030		acc: 0.5082		nmi: 0.1680		ari: 0.1368		f1: 0.3066		
epoch: 031		acc: 0.5082		nmi: 0.1765		ari: 0.1312		f1: 0.3097		
epoch: 032		acc: 0.4973		nmi: 0.1772		ari: 0.1498		f1: 0.3088		
epoch: 033		acc: 0.4918		nmi: 0.1750		ari: 0.1414		f1: 0.3051		
epoch: 034		acc: 0.4973		nmi: 0.1727		ari: 0.1559		f1: 0.3170		
epoch: 035		acc: 0.5191		nmi: 0.2259		ari: 0.1969		f1: 0.3401		
epoch: 036		acc: 0.4863		nmi: 0.1755		ari: 0.1515		f1: 0.3217		
epoch: 037		acc: 0.4918		nmi: 0.1907		ari: 0.1648		f1: 0.3290		
epoch: 038		acc: 0.4809		nmi: 0.1970		ari: 0.1585		f1: 0.3221		
epoch: 039		acc: 0.4973		nmi: 0.2077		ari: 0.1674		f1: 0.3426		
epoch: 040		acc: 0.4754		nmi: 0.1769		ari: 0.1370		f1: 0.3386		
epoch: 041		acc: 0.4590		nmi: 0.1845		ari: 0.1269		f1: 0.3226		
epoch: 042		acc: 0.4262		nmi: 0.1622		ari: 0.1075		f1: 0.3048		
epoch: 043		acc: 0.4481		nmi: 0.1925		ari: 0.1255		f1: 0.3399		
epoch: 044		acc: 0.4481		nmi: 0.1754		ari: 0.1216		f1: 0.3411		
epoch: 045		acc: 0.4645		nmi: 0.1644		ari: 0.1290		f1: 0.3448		
epoch: 046		acc: 0.4918		nmi: 0.2112		ari: 0.1645		f1: 0.3695		
epoch: 047		acc: 0.4754		nmi: 0.2000		ari: 0.1468		f1: 0.3515		
epoch: 048		acc: 0.4372		nmi: 0.1649		ari: 0.1055		f1: 0.3303		
epoch: 049		acc: 0.4426		nmi: 0.1664		ari: 0.1124		f1: 0.3252		
epoch: 050		acc: 0.4262		nmi: 0.1637		ari: 0.0950		f1: 0.3186		
The total number of parameters is: 1.007696M(1e6).
The max memory allocated to model is: 47.13 MB.
Time consuming: 0.53s or 0.01m
****************************************Training loop No.10****************************************
SYNC(
  (tigae): TIGAE(
    (linear1): Linear(in_features=1703, out_features=512, bias=True)
    (gcn1): GCN(
      (activate): ReLU()
    )
    (gcn2): GCN()
  )
)
epoch: 001		acc: 0.5519		nmi: 0.2712		ari: 0.1708		f1: 0.3873		
epoch: 002		acc: 0.5027		nmi: 0.1529		ari: 0.1017		f1: 0.2277		
epoch: 003		acc: 0.6448		nmi: 0.2836		ari: 0.3293		f1: 0.3907		
epoch: 004		acc: 0.3716		nmi: 0.1723		ari: -0.0490		f1: 0.2047		
epoch: 005		acc: 0.5956		nmi: 0.2398		ari: 0.3080		f1: 0.3761		
epoch: 006		acc: 0.5847		nmi: 0.2013		ari: 0.2495		f1: 0.3182		
epoch: 007		acc: 0.5246		nmi: 0.1867		ari: 0.1248		f1: 0.3010		
epoch: 008		acc: 0.5246		nmi: 0.1780		ari: 0.1209		f1: 0.2652		
epoch: 009		acc: 0.5683		nmi: 0.1948		ari: 0.1901		f1: 0.2905		
epoch: 010		acc: 0.5847		nmi: 0.1949		ari: 0.2310		f1: 0.2930		
epoch: 011		acc: 0.5902		nmi: 0.2078		ari: 0.2369		f1: 0.2853		
epoch: 012		acc: 0.5792		nmi: 0.1986		ari: 0.2161		f1: 0.2773		
epoch: 013		acc: 0.5683		nmi: 0.2002		ari: 0.1966		f1: 0.3048		
epoch: 014		acc: 0.5410		nmi: 0.1942		ari: 0.1643		f1: 0.2959		
epoch: 015		acc: 0.5301		nmi: 0.1854		ari: 0.1493		f1: 0.3110		
epoch: 016		acc: 0.5355		nmi: 0.1950		ari: 0.1584		f1: 0.2919		
epoch: 017		acc: 0.5355		nmi: 0.1814		ari: 0.1476		f1: 0.2770		
epoch: 018		acc: 0.5191		nmi: 0.1812		ari: 0.1309		f1: 0.2733		
epoch: 019		acc: 0.5301		nmi: 0.1861		ari: 0.1533		f1: 0.2822		
epoch: 020		acc: 0.5246		nmi: 0.1798		ari: 0.1453		f1: 0.2660		
epoch: 021		acc: 0.5246		nmi: 0.1705		ari: 0.1461		f1: 0.2703		
epoch: 022		acc: 0.5246		nmi: 0.1856		ari: 0.1573		f1: 0.2904		
epoch: 023		acc: 0.5082		nmi: 0.1757		ari: 0.1323		f1: 0.2667		
epoch: 024		acc: 0.5355		nmi: 0.2044		ari: 0.1739		f1: 0.2952		
epoch: 025		acc: 0.5301		nmi: 0.1956		ari: 0.1663		f1: 0.2828		
epoch: 026		acc: 0.5246		nmi: 0.1941		ari: 0.1716		f1: 0.3318		
epoch: 027		acc: 0.5027		nmi: 0.1607		ari: 0.1362		f1: 0.2988		
epoch: 028		acc: 0.4918		nmi: 0.1639		ari: 0.1137		f1: 0.2957		
epoch: 029		acc: 0.4754		nmi: 0.1609		ari: 0.0946		f1: 0.2902		
epoch: 030		acc: 0.4754		nmi: 0.1698		ari: 0.1100		f1: 0.3151		
epoch: 031		acc: 0.4699		nmi: 0.1687		ari: 0.1104		f1: 0.2988		
epoch: 032		acc: 0.4754		nmi: 0.1706		ari: 0.1280		f1: 0.3203		
epoch: 033		acc: 0.4754		nmi: 0.1767		ari: 0.1372		f1: 0.3164		
epoch: 034		acc: 0.4809		nmi: 0.1846		ari: 0.1479		f1: 0.3271		
epoch: 035		acc: 0.4699		nmi: 0.1837		ari: 0.1523		f1: 0.3228		
epoch: 036		acc: 0.4699		nmi: 0.1969		ari: 0.1466		f1: 0.3422		
epoch: 037		acc: 0.4372		nmi: 0.1717		ari: 0.1171		f1: 0.3183		
epoch: 038		acc: 0.4645		nmi: 0.1636		ari: 0.1352		f1: 0.3364		
epoch: 039		acc: 0.4317		nmi: 0.1863		ari: 0.1116		f1: 0.3180		
epoch: 040		acc: 0.4372		nmi: 0.1721		ari: 0.1129		f1: 0.3315		
epoch: 041		acc: 0.4536		nmi: 0.1787		ari: 0.1143		f1: 0.3418		
epoch: 042		acc: 0.4317		nmi: 0.1868		ari: 0.1161		f1: 0.3115		
epoch: 043		acc: 0.4208		nmi: 0.1717		ari: 0.0992		f1: 0.3081		
epoch: 044		acc: 0.4481		nmi: 0.1909		ari: 0.1174		f1: 0.3417		
epoch: 045		acc: 0.4372		nmi: 0.1630		ari: 0.1134		f1: 0.3209		
epoch: 046		acc: 0.4481		nmi: 0.1935		ari: 0.1360		f1: 0.3330		
epoch: 047		acc: 0.4863		nmi: 0.1850		ari: 0.1718		f1: 0.3613		
epoch: 048		acc: 0.4645		nmi: 0.2000		ari: 0.1491		f1: 0.3578		
epoch: 049		acc: 0.4645		nmi: 0.1990		ari: 0.1591		f1: 0.3547		
epoch: 050		acc: 0.4645		nmi: 0.1741		ari: 0.1299		f1: 0.3517		
The total number of parameters is: 1.007696M(1e6).
The max memory allocated to model is: 47.13 MB.
Time consuming: 0.53s or 0.01m
Namespace(is_pretrain=False, plot_clustering_tsne=False, plot_embedding_heatmap=False, adj_norm=False, adj_loop=True, adj_symmetric=True, desc='default', model_name='SYNC', dataset_name='texas', root=None, k=None, t=None, loops=10, feature_type='tensor', label_type='npy', adj_type='tensor', seed=325, epsilon=0.0, device='cuda', clusters=5, nodes=183, lr=0.005, max_epoch=50, pretrain_lr=0.001, pretrain_epoch=30, input_dim=1703, log_save_path='./logs/SYNC/texas/', dataset_path='../data/', clustering_tsne_save_path='./img/clustering/SYNC/texas/', embedding_heatmap_save_path='./img/heatmap/SYNC/texas/', pretrain_save_path='./pretrain/pretrain_tigae/SYNC/texas/', hidden_dim=256, embedding_dim=16, linear_dim=512, beta=0)
Total loops: 10
****************************************Mean value:****************************************
acc: 0.6437±0.0080		nmi: 0.2761±0.0100		ari: 0.3265±0.0191		f1: 0.3949±0.0153
Training over! Punch out!