Questions about the target_shape of the enso dataset

[LivingRoomcode]

The label of enso is Nino3.4 SST anomaly index, and the data dimension is (year,month). But why targe shape in cfg is a four-dimensional array of (12,24, 48,1), shouldn't it be two-dimensional

[gaozhihan]

Thank you for your question. Earthformer does not directly predict the Niño3.4 index, but rather forecasts future sea surface temperature (SST) anomalies across a certain region used to calculate the index, which has two spatial dimensions.

[LivingRoomcode]

Ok, I understand. But why are in_len and out_len respectively 12,14 in fig configuration, but 12 and 26 in data preprocessing?

[gaozhihan]

The dataset we used has a maximum support of out_len=26 (two years). For the experiments in our paper, we only explored a setting with out_len=14 (one year).

[LivingRoomcode]

Why I use the command:
MASTER_ADDR=localhost MASTER_PORT=10001 python ./scripts/cuboid_transformer/enso/train_cuboid_enso.py --gpus 1 --cfg ./scripts/cuboid_transformer/enso/earthformer_enso_v1.yaml --ckpt_name last.ckpt --save tmp_enso
Trying to run the training enso dataset results in code that automatically kills?

[gaozhihan]

This error does not appear to be related to our code. You may want to run sudo dmesg to view system log messages and help identify what happened.