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- Global:
- model: Nonstationary
- mode: check_dataset # check_dataset/train/evaluate/predict
- dataset_dir: "/paddle/dataset/paddlex/ts_fc/ts_dataset_examples"
- device: gpu:0
- output: "output"
- CheckDataset:
- convert:
- enable: False
- src_dataset_type: null
- split:
- enable: False
- train_percent: null
- val_percent: null
- Train:
- time_col: date
- target_cols: OT
- freq: 1h
- input_len: 96
- predict_len: 96
- epochs_iters: 40
- batch_size: 16
- learning_rate: 0.0001
- patience: 10
- Evaluate:
- weight_path: "output/best_accuracy.pdparams.tar"
- Predict:
- model_dir: "output/best_accuracy.pdparams.tar"
- input_path: "/paddle/dataset/paddlex/ts_fc/ts_dataset_examples/test.csv"
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