文件最后提交记录最后更新时间
Adjust rolling api (#1594) * Intermediate version * Fix yaml template & Successfully run rolling * Be compatible with benchmark * Get same results with previous linear model * Black formatting * Update black * Update the placeholder mechanism * Update CI * Update CI * Upgrade Black * Fix CI and simplify code * Fix CI * Move the data processing caching mechanism into utils. * Adjusting DDG-DA * Organize import2 年前
Adjust rolling api (#1594) * Intermediate version * Fix yaml template & Successfully run rolling * Be compatible with benchmark * Get same results with previous linear model * Black formatting * Update black * Update the placeholder mechanism * Update CI * Update CI * Upgrade Black * Fix CI and simplify code * Fix CI * Move the data processing caching mechanism into utils. * Adjusting DDG-DA * Organize import2 年前
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 * remove needless code * reformat with black * limit version & add docs1 年前
Fix Models (#483) * fix gat dataset * fix tft model * Update tft.py * Fix tft.py Co-authored-by: Pengrong Zhu <zhu.pengrong@foxmail.com>4 年前
Fix Models (#483) * fix gat dataset * fix tft model * Update tft.py * Fix tft.py Co-authored-by: Pengrong Zhu <zhu.pengrong@foxmail.com>4 年前
fix(security): use RestrictedUnpickler in load_instance (#2153) * fix(security): enforce RestrictedUnpickler for load_instance to prevent unsafe pickle deserialization * fix: lint error2 个月前
Adjust rolling api (#1594) * Intermediate version * Fix yaml template & Successfully run rolling * Be compatible with benchmark * Get same results with previous linear model * Black formatting * Update black * Update the placeholder mechanism * Update CI * Update CI * Upgrade Black * Fix CI and simplify code * Fix CI * Move the data processing caching mechanism into utils. * Adjusting DDG-DA * Organize import2 年前
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.