Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/10185634

    * fix dist training

Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/10189613

1. Fix a bug in trainer's progress bar
2. Fix a bug that trainer does not support dataset in config file
3. Add feature: support go on training via checkpoint file
4. Add feature: support fixed filename when saving best checkpoint
5. Fix a bug that no id2label in config file after finetune of nlp models
6. Fix some other bugs
        Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/10138906

Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/10142442

Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/10103248

    * update EasyCV MSDataset

Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/9856179

Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/10061562

Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/9935664

    * adapt to msdataset for EasyCV

加入space模型在banking数据集上的微调代码
        Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/10006792

1. Fix random seed for trainer and init it at the first line of init
2. Add a regress test for fixed training
3. Change the dataset 'dureader_robust_qg' to 'DuReader_robust-QG'
4. Change some datasets from loading hf.datasets to loading msdataset.load
        Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/10029509

1. 修复 palm，gpt3，mplug 模型存在的 finetune 后保存 checkpoint 与原有 checkpoint key 字段存在区别无法使用 from_pretrained 导入的问题
2. 调整 test_finetune_mplug.py 为只保存训练结束时的 checkpoint，减少 ci 耗时
        Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/10016517

Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/10011826

、

1. Support saving the best checkpoint for inference
2. Fix a bug that _max_iters field does not exist in trainer
3. Fix a bug that function in lambda_lr field cannot be saved to file
4. Fix a bug that save_pretrained would not be called by iterating
5. Fix a bug that interval is not passed from BestCkptHook's init
        Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/9972765

Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/9970626

    * fix trainer unittest

Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/9872869

* dataset json file add args

1. add child-tuning optimizer and ut
2. fix a training bug which can cause interruption after cross-evaluation
3. move model.params from cfg to default args in build_optimizer to prevent the saving of params in save_pretrained
        Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/9891963

支持 MPLUG 模型 image-text-retrieval 任务的 pipeline 和 finetune
        Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/9919955

Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/9892528

* 修复了zip文件不同打包模式下返回路径错误问题。
* 修复了替换了数据集文件重新下载时校验失败问题。
* 修复dataset oss文件在 REUSE 模式下重复下载的问题。
* 修复了csv数据集的meta json文件中某个split的meta和file字段都为''时加载所有split失败的问题。
 * 修复了不同版本datasets路径不一致的问题。

添加 gpt3 中小模型单机单卡下的 finetune 代码
        Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/9899004

Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/9781849

    * support EasyCV

添加 mplug 模型 caption 及 vqa 任务的 finetuning 支持
        Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/9858028

新增video summarization模型的inference和finetune
        Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/9840532

msdataset add coco dataset
unify taskdataset and ms dataset
fix hf datasets

Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/9791200

    * fix trainer about iters_per_epoch

Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/9763330

Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/9644184

    * fix ditributed training and eval

Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/9691512

Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/9662406

    * bug fix for nlp backbone-head trainers

* csanmt finetune wxp

Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/9660779

    * fix unittest

1. remove comments 
2. fix a bug that ws assert failure for english input
3. add an english input test for ws
3. remove a test case which the dataset can not be visited by outer website
        Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/9657140

移除测试中 damo/nlp_palm2.0_text-generation_english-base beta 分支的使用

1. Refine the nlp finetune examples
2. Remove some useless code
        Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/9631158

1. add sbert,veco,palm,space source code
2. support sbert sequence classification, token classification finetune
3. support veco sequence classification finetune
4. support palm nlg finetune
evaluation result: https://sheet.alibaba-inc.com/#/sheet/f7fdcc7f22bd5105 sheet:Maas
5. add ut for finetunes
6. add veco's taskdataset processor
7. add a common trainer for nlp, and a specific trainer for veco
8. merge some duplicate codes of models, preprocessors, pipelines
        Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/9574105

    * add basic class of hook&metrics

* pre-commit passed

* change some comments

* pre commit passed

* 1. remove accuracy's groups 2. remove useless hooks 3. simplify priorities

* pre-commit passed

* fix a comment

* Merge branch 'master' into finetune_hooks_metrics

# Conflicts:
#	modelscope/metainfo.py

* pre-commit passed

* add basic class of hook&metrics

* pre-commit passed

* change some comments

* pre commit passed

* 1. remove accuracy's groups 2. remove useless hooks 3. simplify priorities

* pre-commit passed

* fix a comment

* Merge branch 'feat/finetune' of gitlab.alibaba-inc.com:Ali-MaaS/MaaS-lib into feat/finetune

* mv hooks related to modelscope/trainers/hooks

* mv priority back

* add torch mdoel base and test

* update hooks, trainer, import_util

* add torch epoch based trainer and dis utils

* add hooks

* fix warmup

* format code stype and fix warmup and add warmup unittest

* fix impls

* pre-commit check passed

* update hook and add EpochBasedTrainer

* add trainer unittest

* Merge branch 'feat/add_hooks' into feat/add_task

# Conflicts:
#	modelscope/models/base_torch.py
#	modelscope/trainers/hooks/hook.py
#	modelscope/trainers/trainer.py

* update unittest name

* rewrite taskdataset to trainer

* fix trainer and add unittest

* add unittest

* code: run to forward

* run through... but ugly code

* arrange some cls

* fix some errs

* revert some mistakes

* init check in

* Merge branch 'feat/add_hooks' into feat/add_task

# Conflicts:
#	modelscope/trainers/trainer.py

* test with bigger epoch and size

* add the default metrics class

* move build metrics code to a method

* merge add_task

* merge origin add_task

* add device initialization

* remove preprocessor arg for bool

* add task models

* move metric collect logic to metrics class

* pre-commit passed

* fix cr comments

* precommit passed

* add task models

* Merge remote-tracking branch 'origin/feat/add_task' into feat/backbone_head

* add comment

* change comment formats.

* fix comments

* fix ut bug

* fix comments

* add wrapper check

* fix comments

* pre commit passed

* fix cr comments

* solve a loop import problem

* fix ut bug

* fix ut errors

* change dummydataset to msdataset

* precommit passed

* merge add task

* backbone-head is build, model is not correctly loaded

* model load states matched

* result matched

* lint

* add veco/palm_v2 code

* merge master

* merge master success running

* add repr model name level

* Merge branch 'feat/veco_palm' into feat/finetune_sbert_veco

* model test for training

* add token-classification metric add formal ut

* fix running bug

* finetune and pipeline are working with backbone-head

* add nli

* add missing code

* finetune and pipeline are working with backbone-head

* Merge branch 'feat/backbone_head' of http://gitlab.alibaba-inc.com/Ali-MaaS/MaaS-lib into feat/backbone_head

* add a test repo for pr

* remove merge conflicted file

* remove merge conflicted file 1

* lint check

* import error

* none type bug fix

* forward input unpacking or dict bug

* move head into models, add build_backbone with registry, no base method

* merge master

* feat: 1. add interleave dataset method 2. support multiple dataset in trainer.build_dataset 3. support 3 sub tasks in sequence_classification task

* unfinished

* update the task model structure in NLP field

* merge master

* update by comments

* keep the default model id as current on production

* unfinished

* unfinished

* veco can run

* Merge remote-tracking branch 'origin/master' into feat/backbone_head

* add taskmodel for module management

* remove forward_input_is_dict

* unfinished

* token classification started

* update base model structure

* move space to backbone

* remove 'type' in build_from_cfg method

* test update

* bug fix

* on tesing, mess code

* Merge branch 'feat/backbone_head' into feat/refactor_nlp_730

# Conflicts:
#	modelscope/metrics/builder.py
#	modelscope/models/__init__.py
#	modelscope/models/nlp/__init__.py
#	modelscope/preprocessors/nlp.py
#	modelscope/trainers/trainer.py
#	requirements/multi-modal.txt

* add missing merge

* add sofa source code

* refactor

* add veco task dataset

* add veco task dataset

* pre-commit passed

* fix bug of log

* add some features

* merge master

* bug fix

* refine nlp models

* fix the training error

* unfinished

* refactor pipeline

* Merge branch 'feat/backbone_head' into feat/refactor_nlp_730

# Conflicts:
#	modelscope/metrics/builder.py
#	modelscope/models/nlp/__init__.py
#	modelscope/models/nlp/backbones/structbert/modeling_sbert.py
#	modelscope/models/nlp/palm_v2/palm_for_text_generation.py
#	modelscope/preprocessors/base.py
#	modelscope/preprocessors/nlp.py
#	modelscope/trainers/trainer.py

* Merge commit 'ab04ceafc5453ce7daa9aa09e37a55f703072a10' into feat/refactor_nlp_730

# Conflicts:
#	modelscope/metainfo.py
#	modelscope/metrics/builder.py
#	modelscope/models/__init__.py
#	modelscope/models/base/base_torch_model.py
#	modelscope/models/nlp/__init__.py
#	modelscope/models/nlp/backbones/space/model/intent_unified_transformer.py
#	modelscope/models/nlp/backbones/space/model/model_base.py
#	modelscope/models/nlp/palm_v2/palm_for_text_generation.py
#	modelscope/models/nlp/sbert_for_sequence_classification.py
#	modelscope/models/nlp/sequence_classification.py
#	modelscope/models/nlp/space/__init__.py
#	modelscope/models/nlp/space_for_dialog_intent_prediction.py
#	modelscope/models/nlp/space_for_dialog_modeling.py
#	modelscope/models/nlp/space_for_dialog_state_tracking.py
#	modelscope/models/nlp/task_model.py
#	modelscope/pipelines/nlp/sentiment_classification_pipeline.py
#	modelscope/preprocessors/base.py
#	modelscope/preprocessors/nlp.py
#	modelscope/trainers/trainer.py

* revert changes

* unify sentnece classification postprocess

* revert some changes, move some model files

* pipeline first case run through

* ws pipeline passed

* Merge branch 'feat/refactor_nlp_730' into feat/finetune_sbert_veco

* finetune

* revert code

* revert some code

* ws finetune started, only the accuracy is weird

* Merge branch 'feat/veco_taskdataset' into feat/finetune_sbert_veco

# Conflicts:
#	modelscope/task_datasets/veco_dataset.py
#	tests/taskdataset/test_veco_dataset.py

* veco+nli finetune started

* Merge branch 'master' into feat/finetune_sbert_veco

# Conflicts:
#	modelscope/models/nlp/sbert_for_sequence_classification.py
#	modelscope/models/nlp/sbert_for_token_classification.py
#	modelscope/models/nlp/sbert_for_zero_shot_classification.py
#	modelscope/models/nlp/space/space_for_dialog_intent_prediction.py
#	modelscope/models/nlp/space/space_for_dialog_modeling.py
#	modelscope/trainers/trainer.py

* add trainer for nlp

* trainer: dataset params passed into preprocessor

* test passed by nlptrainer

* fix some bugs

* fix some bugs

* add backbone/head subclass

* fix regression bugs

* fix bug in token-cls finetune

* support cfg modification

* fix bug

* fix bug

* update requirements

* add some comments and fix some t

* add some comments and revert a argument

* split to two test files

* revert code

* fixbug in precessor

(cherry picked from commit 7a648d096e)

* fix ut bug

* support sbert models

* unfinished

* Merge branch 'feat/finetune_sbert_veco' into sly_tmp_veco_finetune

# Conflicts:
#	tests/trainers/test_finetune_sequence_classification.py

* fixbug in veco

* fix bug

* fixbug

* correct running params

* remove useless files

* add palm finetuning with cnn_dailymail dataset

* copy space model from sofa

* Merge branch 'feat/finetune_sbert_veco' of gitlab.alibaba-inc.com:Ali-MaaS/MaaS-lib into feat/finetune_sbert_veco

* Merge branch 'master' into feat/finetune_sbert_veco

# Conflicts:
#	modelscope/metrics/__init__.py
#	modelscope/models/__init__.py
#	modelscope/models/nlp/__init__.py
#	modelscope/models/nlp/backbones/__init__.py
#	modelscope/models/nlp/backbones/structbert/modeling_sbert.py
#	modelscope/models/nlp/heads/__init__.py
#	modelscope/models/nlp/masked_language.py
#	modelscope/models/nlp/palm_v2/palm_for_text_generation.py
#	modelscope/models/nlp/sbert_for_nli.py
#	modelscope/models/nlp/sbert_for_sentence_similarity.py
#	modelscope/models/nlp/sbert_for_sentiment_classification.py
#	modelscope/models/nlp/sbert_for_sequence_classification.py
#	modelscope/models/nlp/sbert_for_token_classification.py
#	modelscope/models/nlp/sbert_for_zero_shot_classification.py
#	modelscope/models/nlp/sequence_classification.py
#	modelscope/models/nlp/space/space_for_dialog_intent_prediction.py
#	modelscope/models/nlp/space/space_for_dialog_modeling.py
#	modelscope/models/nlp/space/space_for_dialog_state_tracking.py
#	modelscope/models/nlp/structbert/adv_utils.py
#	modelscope/models/nlp/structbert/configuration_sbert.py
#	modelscope/models/nlp/task_models/task_model.py
#	modelscope/pipelines/__init__.py
#	modelscope/pipelines/nlp/__init__.py
#	modelscope/pipelines/nlp/fill_mask_pipeline.py
#	modelscope/pipelines/nlp/named_entity_recognition_pipeline.py
#	modelscope/pipelines/nlp/nli_pipeline.py
#	modelscope/pipelines/nlp/sentence_similarity_pipeline.py
#	modelscope/pipelines/nlp/sentiment_classification_pipeline.py
#	modelscope/pipelines/nlp/text_generation_pipeline.py
#	modelscope/pipelines/nlp/word_segmentation_pipeline.py
#	modelscope/pipelines/nlp/zero_shot_classification_pipeline.py
#	modelscope/preprocessors/nlp.py
#	modelscope/task_datasets/__init__.py
#	modelscope/trainers/trainer.py
#	modelscope/trainers/utils/inference.py
#	modelscope/utils/file_utils.py
#	requirements/nlp.txt
#	tests/pipelines/test_nli.py
#	tests/pipelines/test_sentence_similarity.py
#	tests/pipelines/test_sentiment_classification.py

* fix imports

* mark backbone in their own modeling

* pre-commit check passed

* pre-commit passed, remove roberta model

* fix a bug in ast import

* skip all finetune uts

* fix bugs

* pre-commit passed

* bug fixed

* bug fixed

* bug fixed

* bug fixed

* fix ut bug

* fix bug

* fix ut bug

* fix bug

* fix bug

* fixbugs

* fixbug

* revert veco

* revert veco because of core dump

* fix palm bug

* revert veco

* revert mistaken code

* add a test print

* pre-commit check

* test exception

* add test code

* for test

* fix bug and test

* remove test code

* remove useless file

* 1. fix some bugs 2. add backbone ut

* Merge branch 'master' into feat/finetune_refactor_730

# Conflicts:
#	modelscope/metainfo.py
#	modelscope/metrics/sequence_classification_metric.py
#	modelscope/models/nlp/__init__.py
#	modelscope/models/nlp/task_models/task_model.py
#	modelscope/preprocessors/__init__.py
#	modelscope/preprocessors/nlp.py
#	modelscope/trainers/trainer.py
#	modelscope/trainers/utils/inference.py
#	modelscope/utils/file_utils.py
#	tests/trainers/test_trainer_with_nlp.py

* pre-commit passed

* revert files

* increase test level

* unregister models

* fix bugs

* fix cr comments

* fix bug in backbone-head

* add sbert backbone

* fix bug

* add test for token-cls-metric

* pre-commit passed

* fix ut comments

* revert normal tokenizer to fast tokenizer

* Merge branch 'master' into feat/finetune_refactor_730

# Conflicts:
#	modelscope/models/nlp/__init__.py
#	modelscope/models/nlp/backbones/__init__.py
#	modelscope/models/nlp/backbones/structbert/__init__.py
#	modelscope/models/nlp/masked_language.py
#	modelscope/models/nlp/palm_v2/palm_for_text_generation.py
#	modelscope/models/nlp/sbert_for_sequence_classification.py
#	modelscope/models/nlp/sbert_for_token_classification.py
#	modelscope/models/nlp/sbert_for_zero_shot_classification.py
#	modelscope/pipelines/nlp/text_generation_pipeline.py
#	modelscope/preprocessors/nlp.py
#	modelscope/trainers/trainer.py
#	modelscope/trainers/utils/inference.py

* fix merge bugs

* pre commit passed

* fix bug

* fix bug

* fix bug

* fix bug from master

* add print

* fix ut bug

* fix bug

* Merge branch 'master' into feat/finetune_refactor_730

* skip task model test

Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/9590794

1. change dummy dataset to msdataset
        Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/9586561

    * change dummpy dataset to msdataset

* add pre-commit ignore

* Merge commit 'e93339ea877b93fa0c1b9ebfeee8877f78facb0e' into feat/ms_dataset_case

* Merge commit '34840fc5d8a8ee8cd1278efea913d42db522f9c8' into feat/ms_dataset_case

* remove useless ip hosts.

* Merge commit '47dda0a5f9b4b4466177d9acae097a53f8bea8f7' into feat/ms_dataset_case

* Merge commit '21de1e7db035843c6c2caccf382a6e4f7071f96b' into feat/ms_dataset_case

1. Support `ReduceLROnPlateau` lr scheduler, and add  `PlateauLrSchedulerHook` for it
2. Support custom `optimizer_hook` and `lr_scheduler_hook`
3. Remove function of save best ckpt from `EvaluationHook`, replace with `BestCkptSaverHook`
4. `evaluation_loop` return metric values directly，move metric computation to `single_gpu_test` and `multi_gpu_test`
        Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/9584322

    * [to #43627720] support ReduceLROnPlateau and fix lr scheduler

Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/9552632

* load csv dataset from modelscoop

Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/9567392

1. add trainer doc
2. support local configuration file for trainer
3. update nlp trainer test

Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/9541239

Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/9551089

    * support distributed training

Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/9491966

enable image segmentation test
        Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/9522337