* fix BaseModel `to` method to be consistent with torch.nn.Module

* fix data_preprocessor as well

* fix docstring alignment

* fix docstring alignment

* [Enhance] Enhance revert_sync_batchnorm and convert_sync_batchnorm

* [Enhance] Enhance revert_sync_batchnorm and convert_sync_batchnorm

* Fix unit test

* Add coments

* Refine comments

* clean the code

* revert convert_sync_batchnorm

* revert convert_sync_batchnorm

* refine comment

* fix CI

* fix CI

* [Fix] Change the default value of map_location in PretrainedInit to cpu

* Fix as comment

* [Fix] Fix  cound not handle string data

* Minor refine

* Refine type hint

Refine type hint

* fix as comment

* Minor refine

* Update mmengine/model/base_model/data_preprocessor.py

Co-authored-by: Zaida Zhou <58739961+zhouzaida@users.noreply.github.com>

* [Fix] Fix is_model_wrapper

* [Fix] Fix is_model_wrapper

* init npu

* Update mmengine/optim/optimizer/amp_optimizer_wrapper.py

Co-authored-by: Zaida Zhou <58739961+zhouzaida@users.noreply.github.com>

* Update mmengine/dist/dist.py

Co-authored-by: Zaida Zhou <58739961+zhouzaida@users.noreply.github.com>

* change to is_hccl_backend

* Update mmengine/optim/optimizer/amp_optimizer_wrapper.py

Co-authored-by: Zaida Zhou <58739961+zhouzaida@users.noreply.github.com>

* add comment with AmpOptimWrapper

* Update mmengine/runner/amp.py

Co-authored-by: Zaida Zhou <58739961+zhouzaida@users.noreply.github.com>

* Update mmengine/runner/amp.py

Co-authored-by: Zaida Zhou <58739961+zhouzaida@users.noreply.github.com>

* add npu fn in base_model

* Update mmengine/optim/optimizer/amp_optimizer_wrapper.py

Co-authored-by: Zaida Zhou <58739961+zhouzaida@users.noreply.github.com>

* clean lint

* Update mmengine/optim/optimizer/amp_optimizer_wrapper.py

Co-authored-by: Zaida Zhou <58739961+zhouzaida@users.noreply.github.com>

* Update mmengine/model/base_model/base_model.py

Co-authored-by: Mashiro <57566630+HAOCHENYE@users.noreply.github.com>

* add is_npu_available

* try to fix

* Add comments

* Refine grammar

Co-authored-by: Zaida Zhou <58739961+zhouzaida@users.noreply.github.com>
Co-authored-by: Mashiro <57566630+HAOCHENYE@users.noreply.github.com>
Co-authored-by: HAOCHENYE <21724054@zju.edu.cn>

* add non_blocking feature to BaseDataPreprocessor

* Update mmengine/model/base_model/data_preprocessor.py

Co-authored-by: Zaida Zhou <58739961+zhouzaida@users.noreply.github.com>

* move new parameters to the last to avoid bc issue

* Update mmengine/model/base_model/data_preprocessor.py

Co-authored-by: Zaida Zhou <58739961+zhouzaida@users.noreply.github.com>

* Update mmengine/model/base_model/data_preprocessor.py

Co-authored-by: Zaida Zhou <58739961+zhouzaida@users.noreply.github.com>

Co-authored-by: Zaida Zhou <58739961+zhouzaida@users.noreply.github.com>

Co-authored-by: ubuntu <ubuntu@localhost.localdomain>

* First commit

* add BaseTestTimeAugModel

* Add unit test

* move loop logic to test_step

* fix ddp test

* rename model to module

* optim __init__

* Fix as comment

* Fix as comment

* make val_step should not be called

* make tta do not inherit base model

* Fix unit test

* Enhance docstring

* Fix as comment

* Fix as comment

* minor refine

* minor refine

* minor refine

* fix unit test

* minor refine

* minor refine

* minor refine

* minor refine

* minor refine

* minor refine

* fix unit test

* [Feature] Support convert BN to SyncBN by config

* make unit test compatible with cpu

* Fix as comment

* fix unit test

* change signature of convert_sync_batchnorm: rename sync_bn to implemention

* fix unit test

* fix unit test

* regist pytorch ddp and dp, add unit test

* minor refine

* Support check custom wrapper

* enhance ut

* [Fix] Fix EMAHook trigger train loop init during testing.

* fix sync buffer

* update ut

* fix sync buffer

* fix sync buffer

* [Refactor]: modify interface of Visualizer.add_datasample (#365)

* [Refactor] Refactor data flow: refine `data_preprocessor`. (#359)

* refine data_preprocessor

* remove unused BATCH_DATA alias

* Fix type hints

* rename move_data to cast_data

* [Refactor] Refactor data flow: collate data in `collate_fn` of `DataLoader`  (#323)

* acollate data in dataloader

* fix docstring

* refine comment

* fix as comment

* refactor default collate and psedo collate

* foramt test file

* fix docstring

* fix as comment

* rename elem to data_item

* minor fix

* fix as comment

* [Refactor] Refactor data flow: `data_batch` argument of `Evaluator.process is a `dict` (#360)

* refine evaluator and metric

* compatible with new default collate

* replace default collate with pseudo

* Handle data_batch in metric

* fix unit test

* fix unit test

* fix unit test

* minor refine

* make data_batch optional

make data_batch optional

* rename outputs to predictions

* fix ut

* rename predictions to outputs

* fix docstring

* fix docstring

* fix unit test

* make outputs and data_batch to kwargs

* fix unit test

* keep signature of metric

* fix ut

* rename pred_sample arguments to data_sample(Visualizer)

* fix loop and ut

* [refactor]: Refactor model dataflow (#398)

* [Refactor] Refactor data flow: refine `data_preprocessor`. (#359)

* refine data_preprocessor

* remove unused BATCH_DATA alias

* Fix type hints

* rename move_data to cast_data

* refactor model data flow

tmp_commt

tmp commit

* make val_cfg and test_cfg optional

* roll back runner

* pass test mmdet

* fix as comment

fix as comment

fix ci in DataPreprocessor

* fix ut

* fix ut

* fix rebase main

* [Fix]: Fix test val ddp (#462)

* [Fix] Fix docstring and type hint of data flow (#463)

* Fix docstring of data flow

* change signature of hook

* fix unit test

* resolve conflicts

* fix lint

* Rename data to structure

* adjust the way to import module

* adjust the way to import module

* rename Structure to Data Structures in docs api

* rename structure to structures

* support using some modules of mmengine without torch

* fix circleci config

* fix circleci config

* fix registry ut

* minor fix

* move init method from model/utils to model/weight_init.py

* move init method from model/utils to model/weight_init.py

* move sync_bn to model

* move functions depending on torch to dl_utils

* format import

* fix logging ut

* add weight init in model/__init__.py

* move get_config and get_model to mmengine/hub

* move log_processor.py to mmengine/runner

* fix ut

* Add TimeCounter in dl_utils/__init__.py

* [Refactor] Refactor the import rule

* minor refinement

* add a comment

* fix missing device ids in wrap_model

* clean the code

* use default broadcast_buffers

* refine MMSeparateDistributedDataParallel

* rename tmp variable

* refine docstring

* add type hints

* refactor docstring of ddp model

* add  arg in docstring

* minor refine

* better ddp link

* assert image shape before forward

* add unit test

* enhance error message

* allow gray image input

* fix as comment

* fix unit test

* fix unit test

* modify cuda() to to()

* rollback load_checkpoint

* refine runner

* add TODO

* [Feat] Support FSDP Training

* fix version comparison

* change param format and move `FSDP_WRAP_POLICY` to wrapper file

* add docstring and type hint,reformat code

* fix type hint

* fix typo, reformat code

* merge context

* update unit test

* add docstring

* fix bug in AmpOptimWrapper

* add docstring for backward

* add warning and docstring for accumuate gradient

* fix docstring

* fix docstring

* add params_group method

* fix as comment

* fix as comment

* make default_value of loss_scale to dynamic

* Fix docstring

* decouple should update and should no sync

* rename attribute in OptimWrapper

* fix docstring

* fix comment

* fix comment

* fix as comment

* fix as comment and add unit test

* [Fix] Fix image dtype when enable_normalize=False.

* update ut

* move to collate

* update ut

* add module list

* add module list

* fix docstring

* fix BaseDataPreprocessor

* fix BaseDataPreprocessor

* change device type to torch.device

* change device type to torch.device

* fix cpu method of base model

* Allow ImgDataPreprocessor do not normalize

* remove unnecessary type ignore

* make mean and std optional

* refine docstring

* fix BaseDataPreprocessor

* fix BaseDataPreprocessor

* change device type to torch.device

* change device type to torch.device

* fix cpu method of base model

* [Enhance] Optimize parameter updating speed in AveragedModel.

* add docstring