[⭐] BasicTS baselines upgrade schedule

[yisongfu]

Description of the new feature / enhancement | 您所需的新功能或能力

Baselines to be upgraded from v0.5.8 to v1.0

• BigST
• ChronosBolt
• CrossGNN
• DGCRN
• DeepAR
• FEDformer
• GTS
• HimNet
• Koopa
• MOIRAI
• ModernTCN
• S4
• STAEformer
• STDMAE
• STDN
• STEP
• STGCN
• STGODE
• STPGNN
• STWave
• StemGNN
• Sumba
• TimeMoE
• UMixer
• WaveNet

Contribution Guidelines

Welcome to become a contributor and help make this project better! When upgrading the aforementioned models, please adhere to the following specifications:

1. Code Standards

   • Variable Naming Conventions: If a variable's meaning is unclear, it should be renamed to be more descriptive.
     • Fields and Local Variables: Use all lowercase letters, connected by _.
     • Constants and Global Variables: Use all uppercase letters, connected by _.
     • Class Names: Use CamelCase (capitalize the first letter of each word) and should not use _.
   • Function and Class Comments: Add comments for each class and major function to ensure readability. Refer to the implemented baselines for examples.
   • Function Parameter Type Annotations: Annotate the parameter types and return type for each function. For example:

     def func(a: int, b: float, c: torch.Tensor) -> torch.Tensor:

   • Pass local checks using isort and pylint. Usage:

     pip install pylint
     pip install isort
     
     isort src/basicts
     pylint src/basicts

2. Code Style Standards

   • Model configuration classes should be dataclasses inheriting from BasicTSModelConfig. Try to keep field names consistent with other baselines (e.g., use hidden_size instead of d_model). Refer to the configurations of already implemented baselines.
   • Strive to improve code efficiency by removing unnecessary modules and inefficient implementations.
   • Prefer using components from the BasicTS module library to replace original components where possible (common examples include Transformer, RevIN, Embedding, etc.).

3. Please first open a pull request to beta branch to submit your updates.

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贡献指南

欢迎成为贡献者，一起使这个项目变得更好！在升级上述模型时，请遵守下面的规范：

1. 代码规范

   • 变量命名规范：若变量语义不明确，应该重命名为语义明确的名字。
     • 字段与临时变量：全部小写，用_连接。
     • 常量与全局变量：全部大写，用_连接。
     • 类名：首字母大写，不应该使用_。
   • 函数与类的注释：为每个类和主要的函数添加注释以保证可读性，可参考已实现的baseline。
   • 函数参数类型注解：为每个函数的参数注释类型并标明返回值类型，例如：

      def func(a: int, b: float, c: torch.Tensor) -> torch.Tensor:

   • 在本地通过isor、pylint检查。使用方法：

      pip install pylint
      pip install isort
      
      isort src/basicts
      pylint src/basicts

2. 代码风格规范

   • 模型配置类应该为继承BasicTSModelConfig的数据类，并尽量保持字段命名与其他baseline一致（例如：使用hidden_size 而不是 d_model）。可以参考已实现的baseline配置。
   • 尽可能提高代码效率，移除不必要的模块和低效实现。
   • 尽可能使用BasicTS module模块中的组件替换原有组件（例如常用的包括Transformer、RevIN、Embedding等）。

3. 请向beta分支发起PR来提交您的更改。

Scenario when this would be used? | 使用场景

NA

Supporting information | 附加信息

No response