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Linlang fbba768006 fixed a problem with multi index caused by the default value of groupkey (#1917) 
* fixed a problem with multi index caused by the default value of groupkey

* modify group_key default value

* limit pandas verion

* format with black

* fix docs error

* fix docs error

* fixed bugs caused by pandas upgrade

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* reformat with black

* limit version & add docs
2025-05-13 16:02:49 +08:00
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data_formatters
Adjust rolling api (#1594)
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libs
fixed a problem with multi index caused by the default value of groupkey (#1917)
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README.md
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requirements.txt
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tft.py
fixed a problem with multi index caused by the default value of groupkey (#1917)
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workflow_config_tft_Alpha158.yaml
Adjust rolling api (#1594)
2023-07-14 12:16:12 +08:00

README.md

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.