NormNet

This is an implementation of NormNet. The skeleton of the code refers to ST-Norm.

Requirements

Python 3.7
Numpy >= 1.17.4
Pandas >= 1.0.3
Pytorch >= 1.4.0
h5py

Model Training

python main.py -mode train -normA 1 -normB 1 -normC 1 -normD 1 0

Arguments

normA: whether use the normalization block (a) introduced in the paper.
normB: whether use the normalization block (b) introduced in the paper.
normC: whether use the normalization block (c) introduced in the paper.
normD: whether use the normalization block (d) introduced in the paper.
dataset: dataset name.
version: version number.
hidden_channels: number of hidden channels.
n_pred: number of output steps.
n_his: number of input steps.
n_layers: number of hidden layers.

Model Evaluation

python main.py -mode eval -normA 1 -normB 1 -normC 1 -normD 1 0