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0c64d3fca5
master
7 Commits (0c64d3fca5a5fa2ccb87d3d66985ccc86377d0fe)
7 Commits (0c64d3fca5a5fa2ccb87d3d66985ccc86377d0fe)
| Author | SHA1 | Message | Date |
|---|---|---|---|
 yuze.zyz
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707cbef013 |
[to #42322933]Fix bug in daily UT
Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/10491891 |
3 years ago |
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yuze.zyz
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acba1786b0 |
[to #42322933] Fix bug in UT daily
1. Fix bugs in daily test
2. Fix a bug that the updating of lr is before the first time of updating of optimizer
TODO this will still cause warnings when GA is above 1
3. Remove the judgement of mode in text-classification's preprocessor to fit the base trainer(Bug)
Update some regression bins to fit the preprocessor
4. Update the regression tool to let outer code modify atol and rtol
5. Add the default metric for text-classification task
6. Remove the useless ckpt conversion method in bert to avoid the requirement of tf when loading modeling_bert
Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/10430764
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3 years ago |
|
yuze.zyz
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01e768503c |
[to #42322933] Fix random seed for trainer
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
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3 years ago |
|
yuze.zyz
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88d0804dcd |
[to #42322933] Add S4: child-tuning
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
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3 years ago |
 zhangzhicheng.zzc
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b94bb74f66 | [to #42322933]Add model.save_pretrained method and allow finetune results used by pipeline | 3 years ago |
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zhangzhicheng.zzc
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9d0b38b4e4 | [to #42322933] lazy load on trainer | 3 years ago |
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yuze.zyz
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21fa71baf0 |
[to #42322933] add/refactor nlp models source code and finetune
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
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3 years ago |