Comments (2)
ahariri13
commented on July 30, 2024
@kailunn I kind of have the same problem :) I have a different kind of dataset, but the same approach works. For now I believe the number of channels should be changed depending on how many variables you're trying to predict (in this case 1 only, i.e the speed). For sure you should also change the loss function in base_model.
For me, it is still unclear how the model_inference process is working, in addition to the difference between "merge" mode and "sep" mode in trainer.py. For instance i am not sure what line 72 in trainer.py does (As i mentioned in one issue 2 days ago). If you get to know the answers for these please let me know :)
Cheers
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VeritasYin
commented on July 30, 2024
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Related Issues (20)
- input data HOT 1
- PeMS(L) dataset HOT 1
- Settings for n_his and Kt
- About first_approx() HOT 4
- About bseline model
- 为什么 windows10运行程序中的main.py 总是报错UnboundLocalError:赋值前引用的局部变量W，希望指点。 HOT 5
- Predict diference data HOT 1
- the sensor id of V_228 HOT 1
- adjacency matrix computation and its heatmap HOT 4
- how to make train dataset HOT 1
- what purpose of this model HOT 1
- How to convert Trajectory datasets into adjacency matrix? HOT 1
- Problem with weight forwarding HOT 1
- Way of resuming training with checkpoint
- Hello, can you send me the PEMS07(L) dataset? HOT 1
- TypeError: Fetch argument None has invalid type <class 'NoneType'>
- [Visualization] How can I visualize the predicted result?
- Metrics HOT 1
- Station Info missing for larger dataset
- pickle data was truncated
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