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64 lines
1.4 KiB
64 lines
1.4 KiB
export CUDA_VISIBLE_DEVICES=0
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forward_layers=3
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stride=1
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batch_size=4
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lr=0.0005
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lradj="type1"
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python -u imputation.py \
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--task_name "imputation" \
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--dataset_name "ECL" \
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--data "custom" \
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--root_path "./datasets/electricity/" \
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--data_path "electricity.csv" \
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--mask_rate 0.125 \
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--forward_layers 2 \
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--stride $stride \
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--batch_size $batch_size \
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--learning_rate 0.00025 \
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--lradj "cosine" \
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python -u imputation.py \
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--task_name "imputation" \
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--dataset_name "ECL" \
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--data "custom" \
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--root_path "./datasets/electricity/" \
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--data_path "electricity.csv" \
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--mask_rate 0.25 \
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--forward_layers $forward_layers \
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--stride $stride \
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--batch_size $batch_size \
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--learning_rate $lr \
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--lradj $lradj \
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python -u imputation.py \
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--task_name "imputation" \
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--dataset_name "ECL" \
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--data "custom" \
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--root_path "./datasets/electricity/" \
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--data_path "electricity.csv" \
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--mask_rate 0.375 \
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--forward_layers $forward_layers \
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--stride $stride \
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--batch_size $batch_size \
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--learning_rate $lr \
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--lradj $lradj \
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python -u imputation.py \
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--task_name "imputation" \
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--dataset_name "ECL" \
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--data "custom" \
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--root_path "./datasets/electricity/" \
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--data_path "electricity.csv" \
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--mask_rate 0.50 \
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--forward_layers $forward_layers \
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--stride $stride \
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--batch_size $batch_size \
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--learning_rate $lr \
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--lradj "type2" \
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