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- Global:
- model: TimesNet_ad
- mode: check_dataset # check_dataset/train/evaluate/predict
- dataset_dir: "/paddle/dataset/paddlex/ts_ad/ts_anomaly_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: timestamp
- feature_cols: feature_0,feature_1
- label_col: label
- freq: 1
- input_len: 96
- epochs_iters: 20
- batch_size: 16
- learning_rate: 0.0005
- log_interval: 10
- Evaluate:
- weight_path: "output/best_model/model.pdparams"
- Export:
- weight_path: https://paddle-model-ecology.bj.bcebos.com/paddlex/official_pretrained_model/TimesNet_ad.pdparams.tar
- Predict:
- batch_size: 1
- model_dir: "output/inference"
- input: "https://paddle-model-ecology.bj.bcebos.com/paddlex/ts/demo_ts/ts_ad.csv"
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