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nohup: ignoring input
Using GPU
Args in experiment:
[1mBasic Config[0m
Task Name: short_term_forecast Is Training: 1
Model ID: poly_Daily Model: DLinear
[1mData Loader[0m
Data: poly Root Path: ./dataset/poly
Data Path: ETTh1.csv Features: M
Target: OT Freq: h
Checkpoints: ./checkpoints/
[1mForecasting Task[0m
Seq Len: 5 Label Len: 1
Pred Len: 1 Seasonal Patterns: Daily
Inverse: 0
[1mModel Parameters[0m
Top k: 5 Num Kernels: 6
Enc In: 1 Dec In: 1
C Out: 1 d model: 128
n heads: 8 e layers: 2
d layers: 1 d FF: 256
Moving Avg: 25 Factor: 3
Distil: 1 Dropout: 0.1
Embed: timeF Activation: gelu
[1mRun Parameters[0m
Num Workers: 10 Itr: 1
Train Epochs: 10 Batch Size: 128
Patience: 3 Learning Rate: 0.001
Des: Exp Loss: SMAPE
Lradj: type1 Use Amp: 0
[1mGPU[0m
Use GPU: 1 GPU: 0
Use Multi GPU: 0 Devices: 0,1,2,3
[1mDe-stationary Projector Params[0m
P Hidden Dims: 128, 128 P Hidden Layers: 2
Use GPU: cuda:0
>>>>>>>start training : short_term_forecast_poly_Daily_DLinear_poly_ftM_sl5_ll1_pl1_dm128_nh8_el2_dl1_df256_expand2_dc4_fc3_ebtimeF_dtTrue_Exp_0>>>>>>>>>>>>>>>>>>>>>>>>>>
train 295803
val 269
iters: 100, epoch: 1 | loss: 166.3993378
speed: 0.0151s/iter; left time: 348.3320s
iters: 200, epoch: 1 | loss: 142.9304352
speed: 0.0044s/iter; left time: 100.2291s
iters: 300, epoch: 1 | loss: 65.7178497
speed: 0.0051s/iter; left time: 117.0936s
iters: 400, epoch: 1 | loss: 27.2089806
speed: 0.0052s/iter; left time: 119.1403s
iters: 500, epoch: 1 | loss: 21.0797997
speed: 0.0042s/iter; left time: 94.0313s
iters: 600, epoch: 1 | loss: 18.8247471
speed: 0.0042s/iter; left time: 94.0643s
iters: 700, epoch: 1 | loss: 18.4157066
speed: 0.0049s/iter; left time: 110.4736s
iters: 800, epoch: 1 | loss: 12.0082741
speed: 0.0051s/iter; left time: 114.1029s
iters: 900, epoch: 1 | loss: 11.1090813
speed: 0.0052s/iter; left time: 115.0072s
iters: 1000, epoch: 1 | loss: 10.0641203
speed: 0.0051s/iter; left time: 112.2802s
iters: 1100, epoch: 1 | loss: 14.2032089
speed: 0.0051s/iter; left time: 111.8884s
iters: 1200, epoch: 1 | loss: 13.9361706
speed: 0.0055s/iter; left time: 120.8870s
iters: 1300, epoch: 1 | loss: 12.6248198
speed: 0.0065s/iter; left time: 141.3818s
iters: 1400, epoch: 1 | loss: 15.8037004
speed: 0.0064s/iter; left time: 139.2051s
iters: 1500, epoch: 1 | loss: 16.8491154
speed: 0.0066s/iter; left time: 143.2940s
iters: 1600, epoch: 1 | loss: 14.0719633
speed: 0.0066s/iter; left time: 141.0757s
iters: 1700, epoch: 1 | loss: 11.6868582
speed: 0.0071s/iter; left time: 152.1906s
iters: 1800, epoch: 1 | loss: 15.2078600
speed: 0.0069s/iter; left time: 147.3533s
iters: 1900, epoch: 1 | loss: 16.9177284
speed: 0.0066s/iter; left time: 139.5601s
iters: 2000, epoch: 1 | loss: 21.1839218
speed: 0.0064s/iter; left time: 134.4525s
iters: 2100, epoch: 1 | loss: 10.1267729
speed: 0.0059s/iter; left time: 124.4043s
iters: 2200, epoch: 1 | loss: 19.7111320
speed: 0.0061s/iter; left time: 128.5721s
iters: 2300, epoch: 1 | loss: 13.3639898
speed: 0.0065s/iter; left time: 134.3828s
Epoch: 1 cost time: 13.978420495986938
Epoch: 1, Steps: 2311 | Train Loss: 34.0265995 Vali Loss: 101.7529179 Test Loss: 101.7529179
Validation loss decreased (inf --> 101.752918). Saving model ...
Updating learning rate to 0.001
iters: 100, epoch: 2 | loss: 11.1141844
speed: 0.0094s/iter; left time: 194.5321s
iters: 200, epoch: 2 | loss: 16.7411232
speed: 0.0063s/iter; left time: 130.2066s
iters: 300, epoch: 2 | loss: 17.8961926
speed: 0.0062s/iter; left time: 126.0855s
iters: 400, epoch: 2 | loss: 12.0125732
speed: 0.0052s/iter; left time: 106.0290s
iters: 500, epoch: 2 | loss: 15.0229378
speed: 0.0045s/iter; left time: 92.2099s
iters: 600, epoch: 2 | loss: 14.3085594
speed: 0.0046s/iter; left time: 93.0362s
iters: 700, epoch: 2 | loss: 17.1466732
speed: 0.0050s/iter; left time: 100.3969s
iters: 800, epoch: 2 | loss: 13.5355930
speed: 0.0047s/iter; left time: 94.4735s
iters: 900, epoch: 2 | loss: 14.8811426
speed: 0.0048s/iter; left time: 95.3104s
iters: 1000, epoch: 2 | loss: 12.9529867
speed: 0.0045s/iter; left time: 89.4610s
iters: 1100, epoch: 2 | loss: 12.9094820
speed: 0.0056s/iter; left time: 109.9822s
iters: 1200, epoch: 2 | loss: 12.7477808
speed: 0.0053s/iter; left time: 104.4057s
iters: 1300, epoch: 2 | loss: 17.2639427
speed: 0.0054s/iter; left time: 105.1723s
iters: 1400, epoch: 2 | loss: 14.8688908
speed: 0.0043s/iter; left time: 84.1513s
iters: 1500, epoch: 2 | loss: 11.6341562
speed: 0.0047s/iter; left time: 89.8017s
iters: 1600, epoch: 2 | loss: 9.2916813
speed: 0.0045s/iter; left time: 86.7063s
iters: 1700, epoch: 2 | loss: 16.7399368
speed: 0.0047s/iter; left time: 89.9656s
iters: 1800, epoch: 2 | loss: 10.8475046
speed: 0.0049s/iter; left time: 93.1294s
iters: 1900, epoch: 2 | loss: 11.6888628
speed: 0.0043s/iter; left time: 81.4124s
iters: 2000, epoch: 2 | loss: 15.8128824
speed: 0.0044s/iter; left time: 81.8128s
iters: 2100, epoch: 2 | loss: 13.0616302
speed: 0.0048s/iter; left time: 89.4716s
iters: 2200, epoch: 2 | loss: 14.4002781
speed: 0.0045s/iter; left time: 82.9291s
iters: 2300, epoch: 2 | loss: 13.4701118
speed: 0.0049s/iter; left time: 91.3308s
Epoch: 2 cost time: 11.716513395309448
Epoch: 2, Steps: 2311 | Train Loss: 13.8462037 Vali Loss: 104.0753566 Test Loss: 104.0753566
EarlyStopping counter: 1 out of 3
Updating learning rate to 0.0005
iters: 100, epoch: 3 | loss: 9.2631454
speed: 0.0084s/iter; left time: 154.3418s
iters: 200, epoch: 3 | loss: 13.7429829
speed: 0.0055s/iter; left time: 100.1992s
iters: 300, epoch: 3 | loss: 15.4613152
speed: 0.0052s/iter; left time: 94.8683s
iters: 400, epoch: 3 | loss: 13.2606077
speed: 0.0043s/iter; left time: 77.1520s
iters: 500, epoch: 3 | loss: 13.1992130
speed: 0.0044s/iter; left time: 78.6357s
iters: 600, epoch: 3 | loss: 14.1518326
speed: 0.0053s/iter; left time: 94.8907s
iters: 700, epoch: 3 | loss: 10.3953047
speed: 0.0052s/iter; left time: 92.2236s
iters: 800, epoch: 3 | loss: 11.1425676
speed: 0.0052s/iter; left time: 92.0962s
iters: 900, epoch: 3 | loss: 15.1989994
speed: 0.0056s/iter; left time: 98.1239s
iters: 1000, epoch: 3 | loss: 11.1210909
speed: 0.0045s/iter; left time: 78.3274s
iters: 1100, epoch: 3 | loss: 10.2565603
speed: 0.0046s/iter; left time: 80.3108s
iters: 1200, epoch: 3 | loss: 19.4495506
speed: 0.0043s/iter; left time: 74.9417s
iters: 1300, epoch: 3 | loss: 11.0335197
speed: 0.0051s/iter; left time: 87.2018s
iters: 1400, epoch: 3 | loss: 12.0176430
speed: 0.0055s/iter; left time: 93.3177s
iters: 1500, epoch: 3 | loss: 12.3233557
speed: 0.0044s/iter; left time: 74.7145s
iters: 1600, epoch: 3 | loss: 10.7192001
speed: 0.0050s/iter; left time: 83.7341s
iters: 1700, epoch: 3 | loss: 15.2406216
speed: 0.0051s/iter; left time: 85.9917s
iters: 1800, epoch: 3 | loss: 18.0517616
speed: 0.0059s/iter; left time: 98.0582s
iters: 1900, epoch: 3 | loss: 11.3984852
speed: 0.0068s/iter; left time: 113.0660s
iters: 2000, epoch: 3 | loss: 8.6379766
speed: 0.0071s/iter; left time: 117.3565s
iters: 2100, epoch: 3 | loss: 11.9196386
speed: 0.0071s/iter; left time: 116.0042s
iters: 2200, epoch: 3 | loss: 10.9545345
speed: 0.0058s/iter; left time: 94.2481s
iters: 2300, epoch: 3 | loss: 11.3433733
speed: 0.0071s/iter; left time: 114.8656s
Epoch: 3 cost time: 12.743304252624512
Epoch: 3, Steps: 2311 | Train Loss: 12.4432598 Vali Loss: 104.1657868 Test Loss: 104.1657868
EarlyStopping counter: 2 out of 3
Updating learning rate to 0.00025
iters: 100, epoch: 4 | loss: 10.3617258
speed: 0.0090s/iter; left time: 145.0791s
iters: 200, epoch: 4 | loss: 14.9338398
speed: 0.0056s/iter; left time: 89.5500s
iters: 300, epoch: 4 | loss: 11.8122749
speed: 0.0059s/iter; left time: 93.5930s
iters: 400, epoch: 4 | loss: 11.9195223
speed: 0.0055s/iter; left time: 87.4695s
iters: 500, epoch: 4 | loss: 11.0255833
speed: 0.0059s/iter; left time: 93.0334s
iters: 600, epoch: 4 | loss: 12.3556824
speed: 0.0057s/iter; left time: 88.0989s
iters: 700, epoch: 4 | loss: 9.1875401
speed: 0.0062s/iter; left time: 96.1992s
iters: 800, epoch: 4 | loss: 10.3522472
speed: 0.0060s/iter; left time: 92.3203s
iters: 900, epoch: 4 | loss: 14.2472534
speed: 0.0057s/iter; left time: 87.4218s
iters: 1000, epoch: 4 | loss: 16.8327026
speed: 0.0056s/iter; left time: 84.7399s
iters: 1100, epoch: 4 | loss: 11.3127127
speed: 0.0059s/iter; left time: 89.1948s
iters: 1200, epoch: 4 | loss: 14.2182646
speed: 0.0059s/iter; left time: 88.4019s
iters: 1300, epoch: 4 | loss: 12.7013426
speed: 0.0060s/iter; left time: 89.0013s
iters: 1400, epoch: 4 | loss: 17.1014061
speed: 0.0061s/iter; left time: 89.8557s
iters: 1500, epoch: 4 | loss: 13.6586819
speed: 0.0058s/iter; left time: 84.6825s
iters: 1600, epoch: 4 | loss: 14.7113533
speed: 0.0062s/iter; left time: 90.4426s
iters: 1700, epoch: 4 | loss: 9.5716581
speed: 0.0056s/iter; left time: 80.8428s
iters: 1800, epoch: 4 | loss: 12.1948175
speed: 0.0060s/iter; left time: 85.9679s
iters: 1900, epoch: 4 | loss: 11.7021694
speed: 0.0065s/iter; left time: 93.2858s
iters: 2000, epoch: 4 | loss: 13.9676514
speed: 0.0062s/iter; left time: 87.9734s
iters: 2100, epoch: 4 | loss: 12.2562428
speed: 0.0058s/iter; left time: 81.9602s
iters: 2200, epoch: 4 | loss: 11.7385206
speed: 0.0060s/iter; left time: 83.5228s
iters: 2300, epoch: 4 | loss: 13.9203434
speed: 0.0059s/iter; left time: 82.0698s
Epoch: 4 cost time: 13.895033597946167
Epoch: 4, Steps: 2311 | Train Loss: 11.7786089 Vali Loss: 104.1056367 Test Loss: 104.1056367
EarlyStopping counter: 3 out of 3
Early stopping
>>>>>>>testing : short_term_forecast_poly_Daily_DLinear_poly_ftM_sl5_ll1_pl1_dm128_nh8_el2_dl1_df256_expand2_dc4_fc3_ebtimeF_dtTrue_Exp_0<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<
Politics_test 129
0
test shape: (129, 1, 1)
DLinear
Sports_test 56
0
test shape: (56, 1, 1)
DLinear
Crypto_test 55
0
test shape: (55, 1, 1)
DLinear
Election_test 69
0
test shape: (69, 1, 1)
DLinear
Other_test 93
0
test shape: (93, 1, 1)
DLinear
test 417
0
test shape: (417, 1, 1)
DLinear
Using GPU
Args in experiment:
[1mBasic Config[0m Task Name: short_term_forecast Is Training: 1 Model ID: poly_Daily Model: TimesNet [1mData Loader[0m Data: poly Root Path: ./dataset/poly Data Path: ETTh1.csv Features: M Target: OT Freq: h Checkpoints: ./checkpoints/ [1mForecasting Task[0m Seq Len: 5 Label Len: 1 Pred Len: 1 Seasonal Patterns: Daily Inverse: 0 [1mModel Parameters[0m Top k: 5 Num Kernels: 6 Enc In: 1 Dec In: 1 C Out: 1 d model: 128 n heads: 8 e layers: 2 d layers: 1 d FF: 256 Moving Avg: 25 Factor: 3 Distil: 1 Dropout: 0.1 Embed: timeF Activation: gelu [1mRun Parameters[0m Num Workers: 10 Itr: 1 Train Epochs: 10 Batch Size: 128 Patience: 3 Learning Rate: 0.001 Des: Exp Loss: SMAPE Lradj: type1 Use Amp: 0 [1mGPU[0m Use GPU: 1 GPU: 0 Use Multi GPU: 0 Devices: 0,1,2,3 [1mDe-stationary Projector Params[0m P Hidden Dims: 128, 128 P Hidden Layers: 2 Use GPU: cuda:0>>>>>>>start training : short_term_forecast_poly_Daily_TimesNet_poly_ftM_sl5_ll1_pl1_dm128_nh8_el2_dl1_df256_expand2_dc4_fc3_ebtimeF_dtTrue_Exp_0>>>>>>>>>>>>>>>>>>>>>>>>>>train 295803val 269Traceback (most recent call last): File "run.py", line 203, in <module> exp.train(setting) File "/data/taofeng2/Time-Series-Library/exp/exp_short_term_forecasting.py", line 108, in train outputs = self.model(batch_x, None, dec_inp, None) File "/data/taofeng2/rec/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1553, in _wrapped_call_impl return self._call_impl(*args, **kwargs) File "/data/taofeng2/rec/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1562, in _call_impl return forward_call(*args, **kwargs) File "/data/taofeng2/Time-Series-Library/models/TimesNet.py", line 203, in forward dec_out = self.forecast(x_enc, x_mark_enc, x_dec, x_mark_dec) File "/data/taofeng2/Time-Series-Library/models/TimesNet.py", line 117, in forecast enc_out = self.layer_norm(self.model[i](enc_out))
File "/data/taofeng2/rec/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1553, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "/data/taofeng2/rec/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1562, in _call_impl
return forward_call(*args, **kwargs)
File "/data/taofeng2/Time-Series-Library/models/TimesNet.py", line 38, in forward
period_list, period_weight = FFT_for_Period(x, self.k)
File "/data/taofeng2/Time-Series-Library/models/TimesNet.py", line 15, in FFT_for_Period
_, top_list = torch.topk(frequency_list, k)
RuntimeError: selected index k out of range
Using GPU
Args in experiment:
[1mBasic Config[0m Task Name: short_term_forecast Is Training: 1 Model ID: poly_Daily Model: ETSformer [1mData Loader[0m Data: poly Root Path: ./dataset/poly Data Path: ETTh1.csv Features: M Target: OT Freq: h Checkpoints: ./checkpoints/ [1mForecasting Task[0m Seq Len: 5 Label Len: 1 Pred Len: 1 Seasonal Patterns: Daily Inverse: 0 [1mModel Parameters[0m Top k: 5 Num Kernels: 6 Enc In: 1 Dec In: 1 C Out: 1 d model: 128 n heads: 8 e layers: 2 d layers: 1 d FF: 256 Moving Avg: 25 Factor: 3 Distil: 1 Dropout: 0.1 Embed: timeF Activation: gelu [1mRun Parameters[0m Num Workers: 10 Itr: 1 Train Epochs: 10 Batch Size: 128 Patience: 3 Learning Rate: 0.001 Des: Exp Loss: SMAPE Lradj: type1 Use Amp: 0 [1mGPU[0m Use GPU: 1 GPU: 0 Use Multi GPU: 0 Devices: 0,1,2,3 [1mDe-stationary Projector Params[0m P Hidden Dims: 128, 128 P Hidden Layers: 2 Use GPU: cuda:0Traceback (most recent call last): File "run.py", line 180, in <module> exp = Exp(args) # set experiments File "/data/taofeng2/Time-Series-Library/exp/exp_short_term_forecasting.py", line 39, in __init__ super(Exp_Short_Term_Forecast, self).__init__(args) File "/data/taofeng2/Time-Series-Library/exp/exp_basic.py", line 49, in __init__ self.model = self._build_model().to(self.device) File "/data/taofeng2/Time-Series-Library/exp/exp_short_term_forecasting.py", line 47, in _build_model model = self.model_dict[self.args.model].Model(self.args).float()
File "/data/taofeng2/Time-Series-Library/models/ETSformer.py", line 22, in __init__
assert configs.e_layers == configs.d_layers, "Encoder and decoder layers must be equal"
AssertionError: Encoder and decoder layers must be equal
Using GPU
Args in experiment:
[1mBasic Config[0m Task Name: short_term_forecast Is Training: 1 Model ID: poly_Daily Model: Autoformer [1mData Loader[0m Data: poly Root Path: ./dataset/poly Data Path: ETTh1.csv Features: M Target: OT Freq: h Checkpoints: ./checkpoints/ [1mForecasting Task[0m Seq Len: 5 Label Len: 1 Pred Len: 1 Seasonal Patterns: Daily Inverse: 0 [1mModel Parameters[0m Top k: 5 Num Kernels: 6 Enc In: 1 Dec In: 1 C Out: 1 d model: 128 n heads: 8 e layers: 2 d layers: 1 d FF: 256 Moving Avg: 25 Factor: 3 Distil: 1 Dropout: 0.1 Embed: timeF Activation: gelu [1mRun Parameters[0m Num Workers: 10 Itr: 1 Train Epochs: 10 Batch Size: 128 Patience: 3 Learning Rate: 0.001 Des: Exp Loss: SMAPE Lradj: type1 Use Amp: 0 [1mGPU[0m Use GPU: 1 GPU: 0 Use Multi GPU: 0 Devices: 0,1,2,3 [1mDe-stationary Projector Params[0m P Hidden Dims: 128, 128 P Hidden Layers: 2 Use GPU: cuda:0>>>>>>>start training : short_term_forecast_poly_Daily_Autoformer_poly_ftM_sl5_ll1_pl1_dm128_nh8_el2_dl1_df256_expand2_dc4_fc3_ebtimeF_dtTrue_Exp_0>>>>>>>>>>>>>>>>>>>>>>>>>>train 295803val 269 iters: 100, epoch: 1 | loss: 125.1093140 speed: 0.0817s/iter; left time: 1879.1837s iters: 200, epoch: 1 | loss: 119.9883194 speed: 0.0519s/iter; left time: 1187.9621s iters: 300, epoch: 1 | loss: 120.4995880 speed: 0.0524s/iter; left time: 1194.9475s iters: 400, epoch: 1 | loss: 100.0465622 speed: 0.0560s/iter; left time: 1272.2691s iters: 500, epoch: 1 | loss: 116.4824753 speed: 0.0536s/iter; left time: 1213.0602s iters: 600, epoch: 1 | loss: 85.4972382 speed: 0.0522s/iter; left time: 1174.4087s iters: 700, epoch: 1 | loss: 88.1885834 speed: 0.0522s/iter; left time: 1169.2559s iters: 800, epoch: 1 | loss: 82.2276077 speed: 0.0542s/iter; left time: 1209.2240s iters: 900, epoch: 1 | loss: 106.9474945 speed: 0.0539s/iter; left time: 1196.2974s iters: 1000, epoch: 1 | loss: 85.0476990 speed: 0.0533s/iter; left time: 1177.9007s iters: 1100, epoch: 1 | loss: 87.7373810 speed: 0.0535s/iter; left time: 1178.2929s iters: 1200, epoch: 1 | loss: 84.0766220 speed: 0.0553s/iter; left time: 1211.8615s iters: 1300, epoch: 1 | loss: 85.4758148 speed: 0.0557s/iter; left time: 1215.1944s iters: 1400, epoch: 1 | loss: 78.2181702 speed: 0.0528s/iter; left time: 1147.3401s iters: 1500, epoch: 1 | loss: 60.2390709 speed: 0.0525s/iter; left time: 1133.7439s iters: 1600, epoch: 1 | loss: 89.1311646 speed: 0.0525s/iter; left time: 1129.6546s iters: 1700, epoch: 1 | loss: 71.2259750 speed: 0.0544s/iter; left time: 1165.5368s iters: 1800, epoch: 1 | loss: 82.6697159 speed: 0.0534s/iter; left time: 1138.3032s iters: 1900, epoch: 1 | loss: 74.9959106 speed: 0.0536s/iter; left time: 1137.6840s iters: 2000, epoch: 1 | loss: 62.5461235 speed: 0.0544s/iter; left time: 1149.0427s iters: 2100, epoch: 1 | loss: 70.7119598 speed: 0.0541s/iter; left time: 1136.8583s iters: 2200, epoch: 1 | loss: 73.7651138 speed: 0.0557s/iter; left time: 1164.0662s iters: 2300, epoch: 1 | loss: 66.4088516 speed: 0.0569s/iter; left time: 1183.5827sEpoch: 1 cost time: 127.12707090377808Epoch: 1, Steps: 2311 | Train Loss: 87.2712972 Vali Loss: 97.2253280 Test Loss: 97.2253280Validation loss decreased (inf --> 97.225328). Saving model ...Updating learning rate to 0.001 iters: 100, epoch: 2 | loss: 61.3923912 speed: 0.0636s/iter; left time: 1317.1222s iters: 200, epoch: 2 | loss: 65.1753159 speed: 0.0522s/iter; left time: 1075.5479s iters: 300, epoch: 2 | loss: 67.3857117 speed: 0.0523s/iter; left time: 1071.1485s iters: 400, epoch: 2 | loss: 65.1161575 speed: 0.0524s/iter; left time: 1069.5358s iters: 500, epoch: 2 | loss: 67.7170486 speed: 0.0476s/iter; left time: 966.8471s iters: 600, epoch: 2 | loss: 49.4349747 speed: 0.0486s/iter; left time: 982.3895s iters: 700, epoch: 2 | loss: 49.2569199 speed: 0.0540s/iter; left time: 1085.9273s iters: 800, epoch: 2 | loss: 52.6935806 speed: 0.0541s/iter; left time: 1081.7599s iters: 900, epoch: 2 | loss: 42.6565361 speed: 0.0539s/iter; left time: 1072.0634s iters: 1000, epoch: 2 | loss: 42.3841629 speed: 0.0538s/iter; left time: 1064.7251s iters: 1100, epoch: 2 | loss: 38.3114891 speed: 0.0552s/iter; left time: 1088.2016s iters: 1200, epoch: 2 | loss: 33.6605415 speed: 0.0556s/iter; left time: 1090.5894s iters: 1300, epoch: 2 | loss: 45.3808479 speed: 0.0531s/iter; left time: 1035.7985s iters: 1400, epoch: 2 | loss: 57.4418716 speed: 0.0519s/iter; left time: 1007.2046s iters: 1500, epoch: 2 | loss: 34.7861824 speed: 0.0525s/iter; left time: 1012.5823s iters: 1600, epoch: 2 | loss: 44.8839378 speed: 0.0530s/iter; left time: 1018.4727s iters: 1700, epoch: 2 | loss: 37.3716125 speed: 0.0525s/iter; left time: 1003.3147s iters: 1800, epoch: 2 | loss: 43.5099640 speed: 0.0516s/iter; left time: 980.7705s iters: 1900, epoch: 2 | loss: 29.0294819 speed: 0.0514s/iter; left time: 971.9725s iters: 2000, epoch: 2 | loss: 31.7118816 speed: 0.0521s/iter; left time: 979.0828s iters: 2100, epoch: 2 | loss: 30.0087452 speed: 0.0517s/iter; left time: 966.9519s iters: 2200, epoch: 2 | loss: 29.2079182 speed: 0.0515s/iter; left time: 957.1559s iters: 2300, epoch: 2 | loss: 25.0816441 speed: 0.0518s/iter; left time: 958.1917sEpoch: 2 cost time: 121.51659893989563Epoch: 2, Steps: 2311 | Train Loss: 43.9573370 Vali Loss: 102.6979827 Test Loss: 102.6979827EarlyStopping counter: 1 out of 3Updating learning rate to 0.0005 iters: 100, epoch: 3 | loss: 21.2371597 speed: 0.0615s/iter; left time: 1131.0782s iters: 200, epoch: 3 | loss: 25.6254253 speed: 0.0520s/iter; left time: 951.8379s iters: 300, epoch: 3 | loss: 26.1523972 speed: 0.0519s/iter; left time: 943.6313s iters: 400, epoch: 3 | loss: 26.9119415 speed: 0.0520s/iter; left time: 941.1800s iters: 500, epoch: 3 | loss: 19.9309731 speed: 0.0519s/iter; left time: 934.3014s iters: 600, epoch: 3 | loss: 21.9623642 speed: 0.0517s/iter; left time: 924.0741s iters: 700, epoch: 3 | loss: 22.2535343 speed: 0.0522s/iter; left time: 927.8553s iters: 800, epoch: 3 | loss: 21.7021313 speed: 0.0520s/iter; left time: 920.1141s iters: 900, epoch: 3 | loss: 29.0058079 speed: 0.0524s/iter; left time: 921.7826s iters: 1000, epoch: 3 | loss: 22.5263767 speed: 0.0527s/iter; left time: 922.4195s iters: 1100, epoch: 3 | loss: 21.3485889 speed: 0.0487s/iter; left time: 847.2666s iters: 1200, epoch: 3 | loss: 28.2024269 speed: 0.0522s/iter; left time: 902.3692s iters: 1300, epoch: 3 | loss: 21.6908150 speed: 0.0521s/iter; left time: 895.9471s iters: 1400, epoch: 3 | loss: 24.5477161 speed: 0.0522s/iter; left time: 892.3110s iters: 1500, epoch: 3 | loss: 26.5273266 speed: 0.0521s/iter; left time: 884.2791s iters: 1600, epoch: 3 | loss: 24.3354797 speed: 0.0519s/iter; left time: 876.5215s iters: 1700, epoch: 3 | loss: 18.4123936 speed: 0.0518s/iter; left time: 870.2681s iters: 1800, epoch: 3 | loss: 25.8204365 speed: 0.0522s/iter; left time: 871.9368s iters: 1900, epoch: 3 | loss: 23.8119259 speed: 0.0516s/iter; left time: 855.1912s iters: 2000, epoch: 3 | loss: 20.4097233 speed: 0.0518s/iter; left time: 853.3957s iters: 2100, epoch: 3 | loss: 24.2828884 speed: 0.0523s/iter; left time: 857.5460s iters: 2200, epoch: 3 | loss: 22.7519112 speed: 0.0527s/iter; left time: 859.2399s iters: 2300, epoch: 3 | loss: 18.1778259 speed: 0.0535s/iter; left time: 866.4758sEpoch: 3 cost time: 120.52296924591064Epoch: 3, Steps: 2311 | Train Loss: 21.9228031 Vali Loss: 98.9596668 Test Loss: 98.9596668EarlyStopping counter: 2 out of 3Updating learning rate to 0.00025 iters: 100, epoch: 4 | loss: 18.0018024 speed: 0.0613s/iter; left time: 984.7920s iters: 200, epoch: 4 | loss: 19.0251102 speed: 0.0521s/iter; left time: 831.8499s iters: 300, epoch: 4 | loss: 23.1028042 speed: 0.0523s/iter; left time: 831.1161s iters: 400, epoch: 4 | loss: 20.9184685 speed: 0.0522s/iter; left time: 823.5250s iters: 500, epoch: 4 | loss: 11.0799093 speed: 0.0519s/iter; left time: 814.4509s iters: 600, epoch: 4 | loss: 18.0772190 speed: 0.0522s/iter; left time: 812.4761s iters: 700, epoch: 4 | loss: 25.0085659 speed: 0.0519s/iter; left time: 803.1572s iters: 800, epoch: 4 | loss: 19.4635715 speed: 0.0523s/iter; left time: 803.7490s iters: 900, epoch: 4 | loss: 15.6261635 speed: 0.0522s/iter; left time: 796.8244s iters: 1000, epoch: 4 | loss: 19.1861935 speed: 0.0527s/iter; left time: 799.2424s iters: 1100, epoch: 4 | loss: 17.4227142 speed: 0.0511s/iter; left time: 770.6021s iters: 1200, epoch: 4 | loss: 17.0906410 speed: 0.0521s/iter; left time: 780.8483s iters: 1300, epoch: 4 | loss: 22.2389450 speed: 0.0518s/iter; left time: 771.1419s iters: 1400, epoch: 4 | loss: 21.4989586 speed: 0.0531s/iter; left time: 785.0399s iters: 1500, epoch: 4 | loss: 24.4634037 speed: 0.0525s/iter; left time: 770.6515s iters: 1600, epoch: 4 | loss: 14.3931332 speed: 0.0522s/iter; left time: 760.2537s iters: 1700, epoch: 4 | loss: 18.2236023 speed: 0.0523s/iter; left time: 757.5477s iters: 1800, epoch: 4 | loss: 15.9513836 speed: 0.0518s/iter; left time: 744.3429s iters: 1900, epoch: 4 | loss: 14.6144123 speed: 0.0524s/iter; left time: 748.7924s iters: 2000, epoch: 4 | loss: 17.3529682 speed: 0.0526s/iter; left time: 746.2371s iters: 2100, epoch: 4 | loss: 11.5572128 speed: 0.0518s/iter; left time: 728.5932s iters: 2200, epoch: 4 | loss: 20.6630287 speed: 0.0519s/iter; left time: 725.0715s iters: 2300, epoch: 4 | loss: 15.0299158 speed: 0.0519s/iter; left time: 720.3636sEpoch: 4 cost time: 120.83198928833008Epoch: 4, Steps: 2311 | Train Loss: 17.8590446 Vali Loss: 99.6541544 Test Loss: 99.6541544EarlyStopping counter: 3 out of 3Early stopping>>>>>>>testing : short_term_forecast_poly_Daily_Autoformer_poly_ftM_sl5_ll1_pl1_dm128_nh8_el2_dl1_df256_expand2_dc4_fc3_ebtimeF_dtTrue_Exp_0<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<Politics_test 1290test shape: (129, 1, 1)AutoformerSports_test 560test shape: (56, 1, 1)AutoformerCrypto_test 550test shape: (55, 1, 1)AutoformerElection_test 690test shape: (69, 1, 1)AutoformerOther_test 930test shape: (93, 1, 1)Autoformertest 4170test shape: (417, 1, 1)AutoformerUsing GPUArgs in experiment:[1mBasic Config[0m Task Name: short_term_forecast Is Training: 1 Model ID: poly_Daily Model: Informer [1mData Loader[0m Data: poly Root Path: ./dataset/poly Data Path: ETTh1.csv Features: M Target: OT Freq: h Checkpoints: ./checkpoints/ [1mForecasting Task[0m Seq Len: 5 Label Len: 1 Pred Len: 1 Seasonal Patterns: Daily Inverse: 0 [1mModel Parameters[0m Top k: 5 Num Kernels: 6 Enc In: 1 Dec In: 1 C Out: 1 d model: 128 n heads: 8 e layers: 2 d layers: 1 d FF: 256 Moving Avg: 25 Factor: 3 Distil: 1 Dropout: 0.1 Embed: timeF Activation: gelu [1mRun Parameters[0m Num Workers: 10 Itr: 1 Train Epochs: 10 Batch Size: 128 Patience: 3 Learning Rate: 0.001 Des: Exp Loss: SMAPE Lradj: type1 Use Amp: 0 [1mGPU[0m Use GPU: 1 GPU: 0 Use Multi GPU: 0 Devices: 0,1,2,3 [1mDe-stationary Projector Params[0m P Hidden Dims: 128, 128 P Hidden Layers: 2 Use GPU: cuda:0>>>>>>>start training : short_term_forecast_poly_Daily_Informer_poly_ftM_sl5_ll1_pl1_dm128_nh8_el2_dl1_df256_expand2_dc4_fc3_ebtimeF_dtTrue_Exp_0>>>>>>>>>>>>>>>>>>>>>>>>>>train 295803val 269 iters: 100, epoch: 1 | loss: 18.4633255 speed: 0.0636s/iter; left time: 1463.5806s iters: 200, epoch: 1 | loss: 18.6141644 speed: 0.0425s/iter; left time: 972.9542s iters: 300, epoch: 1 | loss: 16.2997761 speed: 0.0427s/iter; left time: 973.8946s iters: 400, epoch: 1 | loss: 17.3613701 speed: 0.0425s/iter; left time: 965.9605s iters: 500, epoch: 1 | loss: 20.3218861 speed: 0.0425s/iter; left time: 961.7123s iters: 600, epoch: 1 | loss: 18.3885727 speed: 0.0446s/iter; left time: 1004.2115s iters: 700, epoch: 1 | loss: 14.3645077 speed: 0.0449s/iter; left time: 1005.8090s iters: 800, epoch: 1 | loss: 16.3529015 speed: 0.0446s/iter; left time: 994.2204s iters: 900, epoch: 1 | loss: 19.2060375 speed: 0.0445s/iter; left time: 987.4204s iters: 1000, epoch: 1 | loss: 16.6374512 speed: 0.0452s/iter; left time: 999.8708s iters: 1100, epoch: 1 | loss: 15.2332935 speed: 0.0448s/iter; left time: 985.5892s iters: 1200, epoch: 1 | loss: 12.6538916 speed: 0.0444s/iter; left time: 973.5792s iters: 1300, epoch: 1 | loss: 13.2856150 speed: 0.0450s/iter; left time: 981.6979s iters: 1400, epoch: 1 | loss: 14.9170208 speed: 0.0451s/iter; left time: 978.9705s iters: 1500, epoch: 1 | loss: 13.7197580 speed: 0.0452s/iter; left time: 976.4711s iters: 1600, epoch: 1 | loss: 15.3093014 speed: 0.0453s/iter; left time: 975.0410s iters: 1700, epoch: 1 | loss: 14.0163336 speed: 0.0467s/iter; left time: 999.7417s iters: 1800, epoch: 1 | loss: 20.7117882 speed: 0.0549s/iter; left time: 1169.0129s iters: 1900, epoch: 1 | loss: 17.5478783 speed: 0.0461s/iter; left time: 977.3043s iters: 2000, epoch: 1 | loss: 17.1245537 speed: 0.0455s/iter; left time: 961.0005s iters: 2100, epoch: 1 | loss: 10.6634064 speed: 0.0426s/iter; left time: 896.0313s iters: 2200, epoch: 1 | loss: 16.5588665 speed: 0.0429s/iter; left time: 896.5249s iters: 2300, epoch: 1 | loss: 11.9621868 speed: 0.0426s/iter; left time: 886.4605sEpoch: 1 cost time: 105.22166132926941Epoch: 1, Steps: 2311 | Train Loss: 16.1697510 Vali Loss: 100.6653375 Test Loss: 100.6653375Validation loss decreased (inf --> 100.665337). Saving model ...Updating learning rate to 0.001 iters: 100, epoch: 2 | loss: 13.1238909 speed: 0.0516s/iter; left time: 1068.0875s iters: 200, epoch: 2 | loss: 20.1728382 speed: 0.0423s/iter; left time: 872.0876s iters: 300, epoch: 2 | loss: 17.8780251 speed: 0.0427s/iter; left time: 875.0298s iters: 400, epoch: 2 | loss: 14.7511721 speed: 0.0463s/iter; left time: 943.5732s iters: 500, epoch: 2 | loss: 12.0427904 speed: 0.0446s/iter; left time: 904.8627s iters: 600, epoch: 2 | loss: 13.5631447 speed: 0.0449s/iter; left time: 906.3342s iters: 700, epoch: 2 | loss: 13.5782328 speed: 0.0449s/iter; left time: 902.8507s iters: 800, epoch: 2 | loss: 20.8360691 speed: 0.0450s/iter; left time: 900.0690s iters: 900, epoch: 2 | loss: 22.0370770 speed: 0.0451s/iter; left time: 898.0539s iters: 1000, epoch: 2 | loss: 16.5801201 speed: 0.0453s/iter; left time: 896.9155s iters: 1100, epoch: 2 | loss: 14.5161734 speed: 0.0448s/iter; left time: 882.4622s iters: 1200, epoch: 2 | loss: 14.2732534 speed: 0.0447s/iter; left time: 876.4462s iters: 1300, epoch: 2 | loss: 11.9960461 speed: 0.0446s/iter; left time: 870.6034s iters: 1400, epoch: 2 | loss: 15.1337070 speed: 0.0447s/iter; left time: 866.5460s iters: 1500, epoch: 2 | loss: 9.0656061 speed: 0.0447s/iter; left time: 863.2922s iters: 1600, epoch: 2 | loss: 13.3213301 speed: 0.0449s/iter; left time: 861.3891s iters: 1700, epoch: 2 | loss: 14.5119638 speed: 0.0452s/iter; left time: 864.2129s iters: 1800, epoch: 2 | loss: 10.7177267 speed: 0.0450s/iter; left time: 855.8081s iters: 1900, epoch: 2 | loss: 17.8395786 speed: 0.0435s/iter; left time: 822.7455s iters: 2000, epoch: 2 | loss: 14.8244381 speed: 0.0441s/iter; left time: 829.8490s iters: 2100, epoch: 2 | loss: 18.4039059 speed: 0.0424s/iter; left time: 793.5548s iters: 2200, epoch: 2 | loss: 13.6118736 speed: 0.0425s/iter; left time: 790.1691s iters: 2300, epoch: 2 | loss: 11.4545870 speed: 0.0427s/iter; left time: 790.3481sEpoch: 2 cost time: 102.58697414398193Epoch: 2, Steps: 2311 | Train Loss: 15.4020720 Vali Loss: 100.3961058 Test Loss: 100.3961058Validation loss decreased (100.665337 --> 100.396106). Saving model ...Updating learning rate to 0.0005 iters: 100, epoch: 3 | loss: 11.5091486 speed: 0.0511s/iter; left time: 940.4287s iters: 200, epoch: 3 | loss: 17.9458122 speed: 0.0426s/iter; left time: 778.6839s iters: 300, epoch: 3 | loss: 14.1994238 speed: 0.0438s/iter; left time: 795.7742s iters: 400, epoch: 3 | loss: 12.7651749 speed: 0.0443s/iter; left time: 802.2211s iters: 500, epoch: 3 | loss: 17.0586910 speed: 0.0424s/iter; left time: 762.3583s iters: 600, epoch: 3 | loss: 13.4506731 speed: 0.0425s/iter; left time: 759.5705s iters: 700, epoch: 3 | loss: 15.9784584 speed: 0.0428s/iter; left time: 760.8213s iters: 800, epoch: 3 | loss: 14.2870235 speed: 0.0437s/iter; left time: 773.5784s iters: 900, epoch: 3 | loss: 12.5884647 speed: 0.0434s/iter; left time: 763.9027s iters: 1000, epoch: 3 | loss: 12.9502296 speed: 0.0431s/iter; left time: 753.2222s iters: 1100, epoch: 3 | loss: 13.4879770 speed: 0.0430s/iter; left time: 748.3827s iters: 1200, epoch: 3 | loss: 13.5512428 speed: 0.0429s/iter; left time: 742.3157s iters: 1300, epoch: 3 | loss: 14.2446995 speed: 0.0425s/iter; left time: 731.3537s iters: 1400, epoch: 3 | loss: 12.8596277 speed: 0.0424s/iter; left time: 724.4615s iters: 1500, epoch: 3 | loss: 15.4766855 speed: 0.0422s/iter; left time: 716.1462s iters: 1600, epoch: 3 | loss: 15.9771128 speed: 0.0423s/iter; left time: 715.2346s iters: 1700, epoch: 3 | loss: 12.8717899 speed: 0.0421s/iter; left time: 706.4150s iters: 1800, epoch: 3 | loss: 14.9743271 speed: 0.0422s/iter; left time: 704.6534s iters: 1900, epoch: 3 | loss: 11.9715862 speed: 0.0423s/iter; left time: 701.9540s iters: 2000, epoch: 3 | loss: 14.0643806 speed: 0.0428s/iter; left time: 705.1025s iters: 2100, epoch: 3 | loss: 12.7980490 speed: 0.0423s/iter; left time: 692.4459s iters: 2200, epoch: 3 | loss: 10.2281256 speed: 0.0424s/iter; left time: 690.0895s iters: 2300, epoch: 3 | loss: 12.0620594 speed: 0.0423s/iter; left time: 684.8138sEpoch: 3 cost time: 99.08935761451721Epoch: 3, Steps: 2311 | Train Loss: 13.6597602 Vali Loss: 101.7785843 Test Loss: 101.7785843EarlyStopping counter: 1 out of 3Updating learning rate to 0.00025 iters: 100, epoch: 4 | loss: 12.2986031 speed: 0.0517s/iter; left time: 831.6404s iters: 200, epoch: 4 | loss: 13.6242809 speed: 0.0427s/iter; left time: 681.8278s iters: 300, epoch: 4 | loss: 16.0387383 speed: 0.0422s/iter; left time: 669.5553s iters: 400, epoch: 4 | loss: 14.6737423 speed: 0.0423s/iter; left time: 666.8543s iters: 500, epoch: 4 | loss: 13.9088306 speed: 0.0427s/iter; left time: 669.1568s iters: 600, epoch: 4 | loss: 14.2297001 speed: 0.0424s/iter; left time: 660.9013s iters: 700, epoch: 4 | loss: 15.9587755 speed: 0.0441s/iter; left time: 682.0672s iters: 800, epoch: 4 | loss: 10.5772629 speed: 0.0446s/iter; left time: 685.4166s iters: 900, epoch: 4 | loss: 13.7204466 speed: 0.0446s/iter; left time: 681.5976s iters: 1000, epoch: 4 | loss: 13.2972298 speed: 0.0456s/iter; left time: 692.5898s iters: 1100, epoch: 4 | loss: 11.9296160 speed: 0.0440s/iter; left time: 663.5456s iters: 1200, epoch: 4 | loss: 10.6008577 speed: 0.0436s/iter; left time: 653.6986s iters: 1300, epoch: 4 | loss: 13.9893007 speed: 0.0431s/iter; left time: 641.3495s iters: 1400, epoch: 4 | loss: 13.6078968 speed: 0.0431s/iter; left time: 637.3480s iters: 1500, epoch: 4 | loss: 14.7155819 speed: 0.0428s/iter; left time: 628.1566s iters: 1600, epoch: 4 | loss: 12.3526201 speed: 0.0422s/iter; left time: 614.5359s iters: 1700, epoch: 4 | loss: 15.0242414 speed: 0.0422s/iter; left time: 611.1779s iters: 1800, epoch: 4 | loss: 11.4305649 speed: 0.0422s/iter; left time: 606.3483s iters: 1900, epoch: 4 | loss: 12.1565456 speed: 0.0423s/iter; left time: 604.4711s iters: 2000, epoch: 4 | loss: 14.7527428 speed: 0.0426s/iter; left time: 603.4732s iters: 2100, epoch: 4 | loss: 12.4254017 speed: 0.0432s/iter; left time: 607.5699s iters: 2200, epoch: 4 | loss: 10.6814489 speed: 0.0425s/iter; left time: 594.4002s iters: 2300, epoch: 4 | loss: 14.7907343 speed: 0.0434s/iter; left time: 602.1179sEpoch: 4 cost time: 99.98644852638245Epoch: 4, Steps: 2311 | Train Loss: 13.3942514 Vali Loss: 101.0912924 Test Loss: 101.0912924EarlyStopping counter: 2 out of 3Updating learning rate to 0.000125 iters: 100, epoch: 5 | loss: 13.3308678 speed: 0.0532s/iter; left time: 732.0343s iters: 200, epoch: 5 | loss: 12.2457314 speed: 0.0454s/iter; left time: 620.2042s iters: 300, epoch: 5 | loss: 16.6337662 speed: 0.0450s/iter; left time: 610.2456s iters: 400, epoch: 5 | loss: 13.1633835 speed: 0.0435s/iter; left time: 585.8901s iters: 500, epoch: 5 | loss: 12.3083649 speed: 0.0432s/iter; left time: 576.9998s iters: 600, epoch: 5 | loss: 13.8466206 speed: 0.0434s/iter; left time: 575.7987s iters: 700, epoch: 5 | loss: 9.2352076 speed: 0.0437s/iter; left time: 575.7554s iters: 800, epoch: 5 | loss: 15.7612267 speed: 0.0435s/iter; left time: 569.0226s iters: 900, epoch: 5 | loss: 10.5522366 speed: 0.0439s/iter; left time: 569.2786s iters: 1000, epoch: 5 | loss: 12.1655550 speed: 0.0433s/iter; left time: 557.5137s iters: 1100, epoch: 5 | loss: 12.2718935 speed: 0.0436s/iter; left time: 556.1994s iters: 1200, epoch: 5 | loss: 13.9424686 speed: 0.0427s/iter; left time: 540.8828s iters: 1300, epoch: 5 | loss: 13.7018471 speed: 0.0421s/iter; left time: 529.4038s iters: 1400, epoch: 5 | loss: 14.8656826 speed: 0.0426s/iter; left time: 530.6968s iters: 1500, epoch: 5 | loss: 11.1673717 speed: 0.0424s/iter; left time: 524.8073s iters: 1600, epoch: 5 | loss: 12.5054331 speed: 0.0419s/iter; left time: 513.8862s iters: 1700, epoch: 5 | loss: 18.9798508 speed: 0.0432s/iter; left time: 526.1677s iters: 1800, epoch: 5 | loss: 11.4785357 speed: 0.0466s/iter; left time: 562.4803s iters: 1900, epoch: 5 | loss: 9.7765656 speed: 0.0445s/iter; left time: 532.6982s iters: 2000, epoch: 5 | loss: 11.5274982 speed: 0.0446s/iter; left time: 528.9419s iters: 2100, epoch: 5 | loss: 10.8811531 speed: 0.0443s/iter; left time: 521.0156s iters: 2200, epoch: 5 | loss: 11.5428467 speed: 0.0450s/iter; left time: 524.7494s iters: 2300, epoch: 5 | loss: 12.3268862 speed: 0.0450s/iter; left time: 520.5609sEpoch: 5 cost time: 101.652188539505Epoch: 5, Steps: 2311 | Train Loss: 12.9931090 Vali Loss: 102.2651240 Test Loss: 102.2651240EarlyStopping counter: 3 out of 3Early stopping>>>>>>>testing : short_term_forecast_poly_Daily_Informer_poly_ftM_sl5_ll1_pl1_dm128_nh8_el2_dl1_df256_expand2_dc4_fc3_ebtimeF_dtTrue_Exp_0<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<Politics_test 1290test shape: (129, 1, 1)InformerSports_test 560test shape: (56, 1, 1)InformerCrypto_test 550test shape: (55, 1, 1)InformerElection_test 690test shape: (69, 1, 1)InformerOther_test 930test shape: (93, 1, 1)Informertest 4170test shape: (417, 1, 1)InformerUsing GPUArgs in experiment:[1mBasic Config[0m Task Name: short_term_forecast Is Training: 1 Model ID: poly_Daily Model: Reformer [1mData Loader[0m Data: poly Root Path: ./dataset/poly Data Path: ETTh1.csv Features: M Target: OT Freq: h Checkpoints: ./checkpoints/ [1mForecasting Task[0m Seq Len: 5 Label Len: 1 Pred Len: 1 Seasonal Patterns: Daily Inverse: 0 [1mModel Parameters[0m Top k: 5 Num Kernels: 6 Enc In: 1 Dec In: 1 C Out: 1 d model: 128 n heads: 8 e layers: 2 d layers: 1 d FF: 256 Moving Avg: 25 Factor: 3 Distil: 1 Dropout: 0.1 Embed: timeF Activation: gelu [1mRun Parameters[0m Num Workers: 10 Itr: 1 Train Epochs: 10 Batch Size: 128 Patience: 3 Learning Rate: 0.001 Des: Exp Loss: SMAPE Lradj: type1 Use Amp: 0 [1mGPU[0m Use GPU: 1 GPU: 0 Use Multi GPU: 0 Devices: 0,1,2,3 [1mDe-stationary Projector Params[0m P Hidden Dims: 128, 128 P Hidden Layers: 2 Use GPU: cuda:0>>>>>>>start training : short_term_forecast_poly_Daily_Reformer_poly_ftM_sl5_ll1_pl1_dm128_nh8_el2_dl1_df256_expand2_dc4_fc3_ebtimeF_dtTrue_Exp_0>>>>>>>>>>>>>>>>>>>>>>>>>>train 295803val 269 iters: 100, epoch: 1 | loss: 13.0938053 speed: 0.0490s/iter; left time: 1126.7311s iters: 200, epoch: 1 | loss: 15.2827663 speed: 0.0329s/iter; left time: 752.6535s iters: 300, epoch: 1 | loss: 14.7007103 speed: 0.0336s/iter; left time: 767.2641s iters: 400, epoch: 1 | loss: 18.5184879 speed: 0.0335s/iter; left time: 761.4445s iters: 500, epoch: 1 | loss: 20.6989002 speed: 0.0333s/iter; left time: 752.5492s iters: 600, epoch: 1 | loss: 10.8244925 speed: 0.0332s/iter; left time: 747.4235s iters: 700, epoch: 1 | loss: 14.2390881 speed: 0.0344s/iter; left time: 770.7905s iters: 800, epoch: 1 | loss: 18.8083763 speed: 0.0337s/iter; left time: 751.9970s iters: 900, epoch: 1 | loss: 16.8756447 speed: 0.0329s/iter; left time: 731.3578s iters: 1000, epoch: 1 | loss: 17.6418076 speed: 0.0344s/iter; left time: 759.9624s iters: 1100, epoch: 1 | loss: 14.4830141 speed: 0.0344s/iter; left time: 756.9512s iters: 1200, epoch: 1 | loss: 10.8848639 speed: 0.0333s/iter; left time: 730.1792s iters: 1300, epoch: 1 | loss: 10.6840534 speed: 0.0335s/iter; left time: 731.1137s iters: 1400, epoch: 1 | loss: 11.0293818 speed: 0.0336s/iter; left time: 729.6414s iters: 1500, epoch: 1 | loss: 16.0277195 speed: 0.0343s/iter; left time: 741.7794s iters: 1600, epoch: 1 | loss: 17.1872330 speed: 0.0333s/iter; left time: 715.5861s iters: 1700, epoch: 1 | loss: 13.1975203 speed: 0.0335s/iter; left time: 717.1604s iters: 1800, epoch: 1 | loss: 12.5348682 speed: 0.0333s/iter; left time: 710.1910s iters: 1900, epoch: 1 | loss: 12.9809971 speed: 0.0334s/iter; left time: 708.6607s iters: 2000, epoch: 1 | loss: 16.2764931 speed: 0.0330s/iter; left time: 696.1383s iters: 2100, epoch: 1 | loss: 10.9245796 speed: 0.0325s/iter; left time: 682.1171s iters: 2200, epoch: 1 | loss: 16.2822971 speed: 0.0327s/iter; left time: 683.2302s iters: 2300, epoch: 1 | loss: 11.5812016 speed: 0.0327s/iter; left time: 680.3051sEpoch: 1 cost time: 78.6737813949585Epoch: 1, Steps: 2311 | Train Loss: 14.2079166 Vali Loss: 99.7781234 Test Loss: 99.7781234Validation loss decreased (inf --> 99.778123). Saving model ...Updating learning rate to 0.001 iters: 100, epoch: 2 | loss: 12.7582073 speed: 0.0424s/iter; left time: 878.1352s iters: 200, epoch: 2 | loss: 12.7426033 speed: 0.0361s/iter; left time: 743.5629s iters: 300, epoch: 2 | loss: 13.9916630 speed: 0.0340s/iter; left time: 696.8634s iters: 400, epoch: 2 | loss: 14.5632896 speed: 0.0343s/iter; left time: 699.8757s iters: 500, epoch: 2 | loss: 11.3187494 speed: 0.0353s/iter; left time: 716.2310s iters: 600, epoch: 2 | loss: 15.0807352 speed: 0.0343s/iter; left time: 693.6616s iters: 700, epoch: 2 | loss: 15.4637814 speed: 0.0337s/iter; left time: 677.8212s iters: 800, epoch: 2 | loss: 13.6297464 speed: 0.0341s/iter; left time: 681.5798s iters: 900, epoch: 2 | loss: 11.4614668 speed: 0.0339s/iter; left time: 674.7651s iters: 1000, epoch: 2 | loss: 12.3964357 speed: 0.0340s/iter; left time: 672.6581s iters: 1100, epoch: 2 | loss: 16.2975006 speed: 0.0326s/iter; left time: 642.3626s iters: 1200, epoch: 2 | loss: 15.5103655 speed: 0.0330s/iter; left time: 647.0615s iters: 1300, epoch: 2 | loss: 8.6653471 speed: 0.0336s/iter; left time: 656.1528s iters: 1400, epoch: 2 | loss: 11.5170870 speed: 0.0332s/iter; left time: 644.8372s iters: 1500, epoch: 2 | loss: 18.3927097 speed: 0.0341s/iter; left time: 658.7317s iters: 1600, epoch: 2 | loss: 11.2226019 speed: 0.0336s/iter; left time: 645.7614s iters: 1700, epoch: 2 | loss: 16.7179165 speed: 0.0334s/iter; left time: 638.5544s iters: 1800, epoch: 2 | loss: 13.6152878 speed: 0.0338s/iter; left time: 641.3864s iters: 1900, epoch: 2 | loss: 15.7888355 speed: 0.0331s/iter; left time: 625.1765s iters: 2000, epoch: 2 | loss: 8.4861393 speed: 0.0339s/iter; left time: 637.1009s iters: 2100, epoch: 2 | loss: 9.1293392 speed: 0.0330s/iter; left time: 616.4914s iters: 2200, epoch: 2 | loss: 10.7194405 speed: 0.0326s/iter; left time: 605.7921s iters: 2300, epoch: 2 | loss: 13.5013428 speed: 0.0330s/iter; left time: 611.0293sEpoch: 2 cost time: 78.48243737220764Epoch: 2, Steps: 2311 | Train Loss: 13.4540042 Vali Loss: 103.1032754 Test Loss: 103.1032754EarlyStopping counter: 1 out of 3Updating learning rate to 0.0005 iters: 100, epoch: 3 | loss: 8.7505894 speed: 0.0416s/iter; left time: 764.8289s iters: 200, epoch: 3 | loss: 16.2966042 speed: 0.0335s/iter; left time: 613.3147s iters: 300, epoch: 3 | loss: 13.1304350 speed: 0.0343s/iter; left time: 623.3230s iters: 400, epoch: 3 | loss: 10.0901203 speed: 0.0343s/iter; left time: 621.1440s iters: 500, epoch: 3 | loss: 14.0613499 speed: 0.0335s/iter; left time: 603.3487s iters: 600, epoch: 3 | loss: 14.9908180 speed: 0.0345s/iter; left time: 617.1607s iters: 700, epoch: 3 | loss: 15.9622726 speed: 0.0345s/iter; left time: 614.1300s iters: 800, epoch: 3 | loss: 10.4527206 speed: 0.0349s/iter; left time: 617.9401s iters: 900, epoch: 3 | loss: 13.5178328 speed: 0.0351s/iter; left time: 617.7693s iters: 1000, epoch: 3 | loss: 16.0394764 speed: 0.0351s/iter; left time: 613.4625s iters: 1100, epoch: 3 | loss: 11.2444696 speed: 0.0347s/iter; left time: 603.5343s iters: 1200, epoch: 3 | loss: 18.3262157 speed: 0.0340s/iter; left time: 587.2271s iters: 1300, epoch: 3 | loss: 15.2621632 speed: 0.0343s/iter; left time: 589.0081s iters: 1400, epoch: 3 | loss: 10.9593201 speed: 0.0337s/iter; left time: 576.7009s iters: 1500, epoch: 3 | loss: 11.9178505 speed: 0.0340s/iter; left time: 578.0316s iters: 1600, epoch: 3 | loss: 13.3236094 speed: 0.0341s/iter; left time: 576.0734s iters: 1700, epoch: 3 | loss: 11.9597034 speed: 0.0340s/iter; left time: 569.9988s iters: 1800, epoch: 3 | loss: 14.4585695 speed: 0.0341s/iter; left time: 569.0872s iters: 1900, epoch: 3 | loss: 11.1829357 speed: 0.0345s/iter; left time: 572.2489s iters: 2000, epoch: 3 | loss: 10.1677876 speed: 0.0335s/iter; left time: 552.8517s iters: 2100, epoch: 3 | loss: 13.7870026 speed: 0.0342s/iter; left time: 561.1851s iters: 2200, epoch: 3 | loss: 12.1221762 speed: 0.0343s/iter; left time: 559.3241s iters: 2300, epoch: 3 | loss: 15.8239422 speed: 0.0339s/iter; left time: 549.3557sEpoch: 3 cost time: 79.47149276733398Epoch: 3, Steps: 2311 | Train Loss: 12.9249844 Vali Loss: 102.8106960 Test Loss: 102.8106960EarlyStopping counter: 2 out of 3Updating learning rate to 0.00025 iters: 100, epoch: 4 | loss: 14.3106441 speed: 0.0417s/iter; left time: 670.7145s iters: 200, epoch: 4 | loss: 11.0477028 speed: 0.0346s/iter; left time: 553.1858s iters: 300, epoch: 4 | loss: 13.0026131 speed: 0.0327s/iter; left time: 518.8125s iters: 400, epoch: 4 | loss: 12.0062904 speed: 0.0317s/iter; left time: 499.4935s iters: 500, epoch: 4 | loss: 11.5933075 speed: 0.0343s/iter; left time: 537.8736s iters: 600, epoch: 4 | loss: 13.4011488 speed: 0.0344s/iter; left time: 536.3223s iters: 700, epoch: 4 | loss: 16.5099373 speed: 0.0343s/iter; left time: 530.3679s iters: 800, epoch: 4 | loss: 9.7886133 speed: 0.0341s/iter; left time: 524.8950s iters: 900, epoch: 4 | loss: 13.0298634 speed: 0.0340s/iter; left time: 520.1355s iters: 1000, epoch: 4 | loss: 17.2791309 speed: 0.0341s/iter; left time: 517.4290s iters: 1100, epoch: 4 | loss: 12.6219540 speed: 0.0332s/iter; left time: 500.5746s iters: 1200, epoch: 4 | loss: 11.7571306 speed: 0.0334s/iter; left time: 500.4405s iters: 1300, epoch: 4 | loss: 12.2164078 speed: 0.0335s/iter; left time: 498.0036s iters: 1400, epoch: 4 | loss: 13.2915449 speed: 0.0336s/iter; left time: 496.6147s iters: 1500, epoch: 4 | loss: 14.7077398 speed: 0.0338s/iter; left time: 496.8160s iters: 1600, epoch: 4 | loss: 9.7155552 speed: 0.0326s/iter; left time: 474.5674s iters: 1700, epoch: 4 | loss: 14.3058004 speed: 0.0335s/iter; left time: 485.0914s iters: 1800, epoch: 4 | loss: 11.7236633 speed: 0.0342s/iter; left time: 491.1135s iters: 1900, epoch: 4 | loss: 9.3147182 speed: 0.0344s/iter; left time: 490.9678s iters: 2000, epoch: 4 | loss: 10.3452396 speed: 0.0343s/iter; left time: 485.8885s iters: 2100, epoch: 4 | loss: 12.1823196 speed: 0.0339s/iter; left time: 476.8713s iters: 2200, epoch: 4 | loss: 14.4862919 speed: 0.0337s/iter; left time: 471.2754s iters: 2300, epoch: 4 | loss: 13.3286495 speed: 0.0336s/iter; left time: 465.6098sEpoch: 4 cost time: 78.32981204986572Epoch: 4, Steps: 2311 | Train Loss: 12.4508031 Vali Loss: 101.5631628 Test Loss: 101.5631628EarlyStopping counter: 3 out of 3Early stopping>>>>>>>testing : short_term_forecast_poly_Daily_Reformer_poly_ftM_sl5_ll1_pl1_dm128_nh8_el2_dl1_df256_expand2_dc4_fc3_ebtimeF_dtTrue_Exp_0<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<Politics_test 1290test shape: (129, 1, 1)ReformerSports_test 560test shape: (56, 1, 1)ReformerCrypto_test 550test shape: (55, 1, 1)ReformerElection_test 690test shape: (69, 1, 1)ReformerOther_test 930test shape: (93, 1, 1)Reformertest 4170test shape: (417, 1, 1)Reformer |