| 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 |
| } |
