* add en-zh en-es es-en base translation models
 * add en-zh en-es es-en base translation models
        Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/10895782

    * 新增英中/英西/西英-base机器翻译模型

* 新增英中/英西/西英-base机器翻译模型

Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/10713843

    * [to #42322933] solve memory error for translation finetune

Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/10708723

Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/10712244

Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/10680402

修复了 mplug evaluation 使用了错误的 metrics 的问题，将部分中文处理代码独立到 utils 中，为 mplug 添加 trainer
        Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/10612875

修复ocr预处理逻辑不一致问题
        Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/10581697

1.修复token classification preprocessor finetune结果错误问题
2.修复word segmentation output 无用属性
3. 修复nlp preprocessor传use_fast错误
4. 修复torch model exporter bug
5. 修复文档撰写过程中发现trainer相关bug
        Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/10573269

Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/10572842

1. Fix bug in model exporting
2. Skip some long trainings in test level 2
3. Refine some comments
4. Fix a bug that mode is not correct when saving checkpoints
        Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/10564716

1. Add F1 score to sequence classification metric
2. Fix a bug that the evaluate method in trainer does not support a pure pytorch_model.bin
3. Fix a bug in evaluation of veco trainer 
4. Add some tips if lr_scheduler in the trainer needs a higher version torch
5. Add some comments
        Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/10532230

Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/10539423

Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/10525413

Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/10539917

    * add basic remap column wrapper

1. 将 single_gpu_test 与 multi_gpu_test 中的 model.forward 部分分离为 EpochBasedTrainer 中的 evaluation_step，为部分 evaluation 阶段不调用 forward 的模型提供更好的灵活性
2. 重构代码将文本生成模型 Model 层的输入输出统一为 Tensor，Tensor 到 str 的 decode 过程移动到 pipeline 中完成
3. pipeline 后处理添加对中文和中文标点与英文混杂时空格的处理，使 decode 后中英文混杂输出正确
4. 添加 TextGenerationTrainer 修复了部分模型 evaluation 过程 forward 输出单个 token 计算 metrics 的问题
5. 修复了 rouge 无法接收空字符串的问题
        Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/10473768

新增ofa的finetune能力
        Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/10540701

之前的finetune代码当dataset最后长度不足制定batch size时会出错，现已修正
        Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/10524066

1. Change structbert dev revision to master revision
2. Fix bug:  Sample code failed because the updating of model configuration
3. Fix bug: Continue training regression failed
        Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/10519992

Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/10318299

Features:
1. Refactor the directory structure of nlp models. All model files are placed into either the model folder or the task_model folder
2. Refactor all the comments to google style
3. Add detail comments to important tasks and nlp models, to list the description of the model, and its preprocessor&trainer
4. Model Exporting now supports a direct all to TorchModelExporter(no need to derive from it)
5. Refactor model save_pretrained method to support direct running(independent from trainer)
6. Remove the judgement of Model in the pipeline base class, to support outer register models running in our pipelines
7. Nlp trainer now has a NLPTrainingArguments class , user can pass arguments into the dataclass, and use it as a normal cfg_modify_fn, to simplify the operation of modify cfg.
8. Merge the BACKBONES and the MODELS, so user can get a backbone with the Model.from_pretrained call
9. Model.from_pretrained now support a task argument, so user can use a backbone and load it with a specific task class.
10. Support Preprocessor.from_pretrained method
11. Add standard return classes to important nlp tasks, so some of the pipelines and the models are independent now, the return values of the models will always be tensors, and the pipelines will take care of the conversion to numpy and the following stuffs.
12. Split the file of the nlp preprocessors, to make the dir structure more clear.

Bugs Fixing:
1. Fix a bug that lr_scheduler can be called earlier than the optimizer's step
2. Fix a bug that the direct call of Pipelines (not from pipeline(xxx)) throws error
3. Fix a bug that the trainer will not call the correct TaskDataset class
4. Fix a bug that the internal loading of dataset will throws error in the trainer class
        Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/10490585

Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/10509580

# Conflicts:
#	tests/trainers/test_ofa_trainer.py

Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/10465138

Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/10507910

    * [to #42322933] remove revision usage for face detection

增加对text-ranking任务中文模型的单元测试，以方便得到官方模型打标。
        Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/10492754