model_kwargs.py

autoformer_kwargs = lambda lookback,lookahead:{
    'enc_in': 6,
    'dec_in': 2,
    'c_out': 1,
    'pred_len': lookahead,
    'seq_len': lookback,
    'd_model': 32*4,
    'data_idx': [0,3,4,5,6,7],
    'time_idx': [1,2]
}

informer_kwargs = lambda lookback,lookahead:{
    'enc_in': 6,
    'dec_in': 2,
    'c_out': 1,
    'pred_len': lookahead,
    'd_model': 32*4,
    'data_idx': [0,3,4,5,6,7],
    'time_idx': [1,2]
}

timesnet_kwargs = lambda lookback,lookahead:{
    'enc_in': 6,
    'dec_in': 2,
    'c_out': 1,
    'pred_len': lookahead,
    'seq_len': lookback,
    'd_model': 32*4,
    'data_idx': [0,3,4,5,6,7],
    'time_idx': [1,2]
}

transformer_kwargs = lambda lookback,lookahead:{
    'enc_in': 6,
    'dec_in': 2,
    'c_out': 1,
    'pred_len': lookahead,
    'd_model': 32*4,
    'data_idx': [0,3,4,5,6,7],
    'time_idx': [1,2]
}

lstm_kwargs = lambda lookback,lookahead:{
    'input_size': 8,
    'hidden_size': 8*4,
    'num_layers': 2,
    'lookback': lookback
}

lstnet_kwargs = lambda lookback,lookahead:{
    'num_features':8,
    'conv1_out_channels':8*4,
    'conv1_kernel_height':3*4,
    'recc1_out_channels':32*4
}

patchtst_kwargs = lambda lookback,lookahead:{
    'enc_in': 6,
    'dec_in': 2,
    'c_out': 1,
    'pred_len': lookahead,
    'seq_len': lookback,
    'd_model': 32*4,
    'data_idx': [0,3,4,5,6,7],
    'time_idx': [1,2]
}

timesfm_kwargs = lambda lookback, lookahead:{
    'lookback': lookback,
    'lookahead': lookahead,
    'context_len': 512
}