Comments (4)
zezhishao
commented on June 19, 2024
The specific method is to fuse the representation generated by TSFormer with the Encoder of DCRNN, and the others are the same as Graph WaveNet.
from step.
zezhishao
commented on June 19, 2024
Now I don't have the code too, I will reproduce it later.
from step.
zezhishao
commented on June 19, 2024
See branch dev/dcrnn.
This is the result of the first 50 epochs on the METR-LA dataset:
2023-07-29 05:33:08,260 - easytorch-training - INFO - Result <train>: [train_time: 312.44 (s), lr: 1.00e-04, train_MAE: 2.7313, train_RMSE: 5.4791, train_MAPE: 0.0720]
2023-07-29 05:33:08,261 - easytorch-training - INFO - Start validation.
2023-07-29 05:34:07,963 - easytorch-training - INFO - Result <val>: [val_time: 59.70 (s), val_MAE: 2.7455, val_RMSE: 5.2874, val_MAPE: 0.0748]
2023-07-29 05:34:09,407 - easytorch-training - INFO - Checkpoint checkpoints/STEP_100/506878ab44e96728aec144de7098d6cb/STEP_best_val_MAE.pt saved
2023-07-29 05:36:09,617 - easytorch-training - INFO - Evaluate best model on test data for horizon 1, Test MAE: 2.1745, Test RMSE: 3.7863, Test MAPE: 0.0521
2023-07-29 05:36:09,621 - easytorch-training - INFO - Evaluate best model on test data for horizon 2, Test MAE: 2.4548, Test RMSE: 4.5666, Test MAPE: 0.0612
2023-07-29 05:36:09,625 - easytorch-training - INFO - Evaluate best model on test data for horizon 3, Test MAE: 2.6419, Test RMSE: 5.0937, Test MAPE: 0.0681
2023-07-29 05:36:09,628 - easytorch-training - INFO - Evaluate best model on test data for horizon 4, Test MAE: 2.7905, Test RMSE: 5.5172, Test MAPE: 0.0742
2023-07-29 05:36:09,632 - easytorch-training - INFO - Evaluate best model on test data for horizon 5, Test MAE: 2.9136, Test RMSE: 5.8632, Test MAPE: 0.0794
2023-07-29 05:36:09,637 - easytorch-training - INFO - Evaluate best model on test data for horizon 6, Test MAE: 3.0203, Test RMSE: 6.1615, Test MAPE: 0.0839
2023-07-29 05:36:09,641 - easytorch-training - INFO - Evaluate best model on test data for horizon 7, Test MAE: 3.1131, Test RMSE: 6.4187, Test MAPE: 0.0879
2023-07-29 05:36:09,644 - easytorch-training - INFO - Evaluate best model on test data for horizon 8, Test MAE: 3.1937, Test RMSE: 6.6351, Test MAPE: 0.0914
2023-07-29 05:36:09,648 - easytorch-training - INFO - Evaluate best model on test data for horizon 9, Test MAE: 3.2655, Test RMSE: 6.8282, Test MAPE: 0.0946
2023-07-29 05:36:09,652 - easytorch-training - INFO - Evaluate best model on test data for horizon 10, Test MAE: 3.3307, Test RMSE: 7.0007, Test MAPE: 0.0974
2023-07-29 05:36:09,655 - easytorch-training - INFO - Evaluate best model on test data for horizon 11, Test MAE: 3.3905, Test RMSE: 7.1538, Test MAPE: 0.1000
2023-07-29 05:36:09,658 - easytorch-training - INFO - Evaluate best model on test data for horizon 12, Test MAE: 3.4496, Test RMSE: 7.3009, Test MAPE: 0.1025
2023-07-29 05:36:09,762 - easytorch-training - INFO - Result <test>: [test_time: 120.35 (s), test_MAE: 2.9782, test_RMSE: 6.1186, test_MAPE: 0.0827]
2023-07-29 05:36:10,938 - easytorch-training - INFO - Checkpoint checkpoints/STEP_100/506878ab44e96728aec144de7098d6cb/STEP_034.pt saved
from step.
Jimmy-7664
commented on June 19, 2024
Thank you for your prompt reply, my questions have been answered. Wish you all the best :)
from step.
Related Issues (20)
- 关于pre-training结果的复现 HOT 7
- 关于adj_mx.pkl这个数据集的问题 HOT 1
- 数据集替换 HOT 1
- Error HOT 6
- torch.cuda.OutOfMemoryError
- 作者你好，请问这个可以用单步预测里面吗，类似mtgnn 里exchage那种的
- 复现出现张量维度不匹配 HOT 3
- 作者您好，向您请教一下discrete_graph_learning.py中实现Equation(2)的细节
- launch_training() got an unexpected keyword argument 'devices'
- 请问如何用TSformer预训练模型，是否有readme文件介绍步骤 HOT 2
- 用自己的数据集来 预训练 模型时，如何配置 HOT 2
- 配置“CFG.RE_SCALE=False” HOT 3
- 单变量是否可以用这个预训练模型 HOT 2
- 数据集只有两列，请问是否可以用tsformer预训练模型 HOT 4
- About Figure 1 in the Paper HOT 4
- Setting of input and output length of compared model
- TSFormer预训练模型是否可以处理时间序列多通道数据？ HOT 3
- 关于discrere_graph_learning.py 中的train_length HOT 1
- 多卡训练失败问题 HOT 3
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from step.