TimesNet_cls.yaml 864 B

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  1. Global:
  2. model: TimesNet_cls
  3. mode: check_dataset # check_dataset/train/evaluate/predict
  4. dataset_dir: "/paddle/dataset/paddlex/ts_cls/ts_classify_examples"
  5. device: gpu:0
  6. output: "output"
  7. CheckDataset:
  8. convert:
  9. enable: False
  10. src_dataset_type: null
  11. split:
  12. enable: False
  13. train_percent: null
  14. val_percent: null
  15. Train:
  16. time_col: time
  17. target_cols: dim_0,dim_1,dim_2
  18. group_id: group_id
  19. static_cov_cols: label
  20. freq: 1
  21. epochs_iters: 40
  22. batch_size: 16
  23. learning_rate: 0.0001
  24. log_interval: 10
  25. Evaluate:
  26. weight_path: "output/best_model/model.pdparams"
  27. Export:
  28. weight_path: https://paddle-model-ecology.bj.bcebos.com/paddlex/official_pretrained_model/TimesNet_cls.pdparams.tar
  29. Predict:
  30. batch_size: 1
  31. model_dir: "output/inference"
  32. input: "https://paddle-model-ecology.bj.bcebos.com/paddlex/ts/demo_ts/ts_cls.csv"