Initialize the client of Gungnir and update docs

README.md

@@ -112,6 +112,7 @@ The paper references and links are all listed at the bottom of this file.
 
 | **Type**      | **Algo**                    | **IMPU** | **FORE** | **CLAS** | **CLUS** | **ANOD** | **Year - Venue**   |
 |:--------------|:----------------------------|:--------:|:--------:|:--------:|:--------:|:--------:|:-------------------|
+| LLM           | Gungnir 🚀 [^36]            |    ✅     |    ✅     |    ✅     |    ✅     |    ✅     | `Later in 2024`    |
 | Neural Net    | ImputeFormer🧑‍🔧[^34]      |    ✅     |          |          |          |          | `2024 - KDD`       |
 | Neural Net    | iTransformer🧑‍🔧[^24]      |    ✅     |          |          |          |          | `2024 - ICLR`      |
 | Neural Net    | SAITS[^1]                   |    ✅     |          |          |          |          | `2023 - ESWA`      |
@@ -385,6 +386,8 @@ PyPOTS community is open, transparent, and surely friendly. Let's work together
 [^33]: Cao, D., Wang, Y., Duan, J., Zhang, C., Zhu, X., Huang, C., Tong, Y., Xu, B., Bai, J., Tong, J., & Zhang, Q. (2020). [Spectral Temporal Graph Neural Network for Multivariate Time-series Forecasting](https://proceedings.neurips.cc/paper/2020/hash/cdf6581cb7aca4b7e19ef136c6e601a5-Abstract.html). *NeurIPS 2020*.
 [^34]: Nie, T., Qin, G., Mei, Y., & Sun, J. (2024). [ImputeFormer: Low Rankness-Induced Transformers for Generalizable Spatiotemporal Imputation](https://arxiv.org/abs/2312.01728). *KDD 2024*.
 [^35]: Bai, S., Kolter, J. Z., & Koltun, V. (2018). [An empirical evaluation of generic convolutional and recurrent networks for sequence modeling](https://arxiv.org/abs/1803.01271). *arXiv 2018*.
+[^36]: Project Gungnir, the world 1st LLM for time-series multitask modeling, will meet you soon. 🚀 Missing values and variable lengths in your datasets?
+       Hard to perform multitask learning with your time series? Not problems no longer. We'll open application for public beta test recently ;-) Follow us, and stay tuned!
 
 <details>
 <summary>🏠 Visits</summary>

README_zh.md

@@ -96,8 +96,9 @@ PyPOTS当前支持多变量POTS数据的插补，预测，分类，聚类以及
 所以这些模型的输入中不能带有缺失值，无法接受POTS数据作为输入，更加不是插补算法。
 **为了使上述模型能够适用于POTS数据，我们采用了与[SAITS论文](https://arxiv.org/pdf/2202.08516)[^1]中相同的embedding策略和训练方法（ORT+MIT）对它们进行改进**。
 
-| **类型**      | **算法**                      | **插补** | **预测** | **分类** | **聚类** | **异常检测** | **年份 - 刊物**      |
-|:--------------|:----------------------------|:------:|:------:|:------:|:------:|:--------:|:-----------------|
+| **类型**      | **算法**                      | **插补** | **预测** | **分类** | **聚类** | **异常检测** | **年份 - 刊物**        |
+|:--------------|:----------------------------|:------:|:------:|:------:|:------:|:--------:|:-------------------|
+| LLM           | Gungnir 🚀 [^36]            |    ✅     |    ✅     |    ✅     |    ✅     |    ✅     | `Later in 2024`    |
 | Neural Net    | ImputeFormer🧑‍🔧[^34]      |    ✅     |          |          |          |          | `2024 - KDD`       |
 | Neural Net    | iTransformer🧑‍🔧[^24]      |    ✅     |          |          |          |          | `2024 - ICLR`      |
 | Neural Net    | SAITS[^1]                   |    ✅     |          |          |          |          | `2023 - ESWA`      |
@@ -356,7 +357,7 @@ PyPOTS社区是一个开放、透明、友好的社区，让我们共同努力
 [^33]: Cao, D., Wang, Y., Duan, J., Zhang, C., Zhu, X., Huang, C., Tong, Y., Xu, B., Bai, J., Tong, J., & Zhang, Q. (2020). [Spectral Temporal Graph Neural Network for Multivariate Time-series Forecasting](https://proceedings.neurips.cc/paper/2020/hash/cdf6581cb7aca4b7e19ef136c6e601a5-Abstract.html). *NeurIPS 2020*.
 [^34]: Nie, T., Qin, G., Mei, Y., & Sun, J. (2024). [ImputeFormer: Low Rankness-Induced Transformers for Generalizable Spatiotemporal Imputation](https://arxiv.org/abs/2312.01728). *KDD 2024*.
 [^35]: Bai, S., Kolter, J. Z., & Koltun, V. (2018). [An empirical evaluation of generic convolutional and recurrent networks for sequence modeling](https://arxiv.org/abs/1803.01271). *arXiv 2018*.
-
+[^36]: Gungnir项目，世界上第一个时间序列多任务大模型，将很快与大家见面。🚀 数据集存在缺少值且样本长短不一？多任务建模场景困难？都不再是问题，让我们的大模型来帮你解决。我们将在近期开放公测申请 ;-) 关注我们，敬请期待!
 
 <details>
 <summary>🏠 访问量</summary>

docs/about_us.rst

@@ -22,6 +22,12 @@ Linglong Qian
 - `GitHub (LinglongQian) <https://github.com/LinglongQian>`_
 - `LinkedIn (Linglong Qian) <https://www.linkedin.com/in/linglongqian>`_
 
+Yiyuan Yang
+************
+- Joined in Jun 2024
+- `GitHub (yyysjz1997) <https://github.com/yyysjz1997>`_
+- `LinkedIn (Yiyuan Yang) <https://www.linkedin.com/in/yiyuan-yang-8154941ab/>`_
+
 
 All Contributors
 """"""""""""""""

docs/benchpots.rst

@@ -1,6 +1,14 @@
 All APIs of BenchPOTS
 =======================
 
+.. image:: https://pypots.com/figs/pypots_logos/BenchPOTS/logo_FFBG.svg
+   :height: 120
+   :align: left
+   :target: https://github.com/WenjieDu/BenchPOTS
+   :alt: BenchPOTS logo
+BenchPOTS
+---------
+
 benchpots.datasets
 ------------------
 

docs/index.rst

@@ -133,6 +133,8 @@ The paper references are all listed at the bottom of this readme file.
 +----------------+-----------------------------------------------------------+------+------+------+------+------+-----------------------+
 | Type           | Algorithm                                                 | IMPU | FORE | CLAS | CLUS | ANOD | Year - Venue          |
 +================+===========================================================+======+======+======+======+======+=======================+
+| Neural Net     | ImputeFormer      :cite:`nie2024imputeformer`             |  ✅  |      |      |      |      | ``2024 - KDD``        |
++----------------+-----------------------------------------------------------+------+------+------+------+------+-----------------------+
 | Neural Net     | iTransformer🧑‍🔧 :cite:`liu2024itransformer`             |  ✅  |      |      |      |      | ``2024 - ICLR``       |
 +----------------+-----------------------------------------------------------+------+------+------+------+------+-----------------------+
 | Neural Net     | SAITS :cite:`du2023SAITS`                                 |  ✅  |      |      |      |      | ``2023 - ESWA``       |

docs/install.rst

@@ -31,8 +31,9 @@ Required Dependencies
 * tensorboard
 * scikit-learn
 * torch >=1.10.0
-* tsdb >=0.2
-* pygrinder >=0.4
+* tsdb >=0.6
+* pygrinder >=0.6
+* benchpots >=0.2
 
 
 Optional Dependencies

docs/pygrinder.rst

@@ -1,6 +1,11 @@
 All APIs of PyGrinder
 =======================
 
+.. image:: https://pypots.com/figs/pypots_logos/PyGrinder/logo_FFBG.svg
+   :height: 120
+   :align: left
+   :target: https://github.com/WenjieDu/PyGrinder
+   :alt: PyGrinder logo
 PyGrinder
 ---------
 

docs/tsdb.rst

@@ -1,6 +1,11 @@
 All APIs of TSDB
 =======================
 
+.. image:: https://pypots.com/figs/pypots_logos/TSDB/logo_FFBG.svg
+   :height: 120
+   :align: left
+   :target: https://github.com/WenjieDu/TSDB
+   :alt: TSDB logo
 TSDB
 ----
 

pypots/__init__.py

@@ -15,6 +15,7 @@
     data,
     utils,
 )
+from .gungnir import Gungnir
 from .version import __version__
 
 __all__ = [
@@ -25,5 +26,6 @@
     "optim",
     "data",
     "utils",
+    "Gungnir",
     "__version__",
 ]

pypots/gungnir/__init__.py

@@ -0,0 +1,12 @@
+"""
+
+"""
+
+# Created by Wenjie Du <wenjay.du@gmail.com>
+# License: BSD-3-Clause
+
+from .client import Gungnir
+
+__all__ = [
+    "Gungnir",
+]

pypots/gungnir/client.py

@@ -0,0 +1,24 @@
+"""
+
+"""
+
+# Created by Wenjie Du <wenjay.du@gmail.com>
+# License: BSD-3-Clause
+
+from ..utils.logging import logger
+
+logger.info(
+    "The functionalities of client Gungnir have not been implemented yet,\n"
+    "which will be updated later 2024 once our close beta test is ready.\n"
+    "AI for real-world time series is coming. 🚀 Stay tuned please! https://time-series.ai"
+)
+
+
+class TimeSeriesAI:
+    def __init__(self):
+        pass
+
+
+class Gungnir(TimeSeriesAI):
+    def __init__(self):
+        super().__init__()