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qlib/examples/benchmarks/TFT
you-n-g fc243fd29b Fix Models (#483)
* fix gat dataset

* fix tft model

* Update tft.py

* Fix tft.py

Co-authored-by: Pengrong Zhu <zhu.pengrong@foxmail.com>
2021-09-30 13:11:06 +08:00
..
2020-12-15 20:37:43 +08:00
2020-12-15 20:37:43 +08:00
2021-09-30 13:11:06 +08:00
2021-09-30 13:11:06 +08:00
2021-09-30 13:11:06 +08:00

Temporal Fusion Transformers Benchmark

Source

Reference: Lim, Bryan, et al. "Temporal fusion transformers for interpretable multi-horizon time series forecasting." arXiv preprint arXiv:1912.09363 (2019).

GitHub: https://github.com/google-research/google-research/tree/master/tft

Run the Workflow

Users can follow the workflow_by_code_tft.py to run the benchmark.

Notes

  1. Please be aware that this script can only support Python 3.6 - 3.7.
  2. If the CUDA version on your machine is not 10.0, please remember to run the following commands conda install anaconda cudatoolkit=10.0 and conda install cudnn on your machine.
  3. The model must run in GPU, or an error will be raised.
  4. New datasets should be registered in data_formatters, for detail please visit the source.