## Motivation
Address an issue where mix training is not enabled when optimizer_config
is present in the config on Ascend NPU
## Modification
Previously, mix training was not enabled when optimizer_config was
present in the configuration on Ascend NPU. This commit addresses the
issue by ensuring that mix training is enabled under these
circumstances.
## Use cases
It has been validated on the
knet_s3_upernet_swin-l_8x2_640x640_adamw_80k_ade20k.py config.
## Checklist
1. Pre-commit or other linting tools are used to fix the potential lint
issues.
2. The modification is covered by complete unit tests. If not, please
add more unit test to ensure the correctness.
3. If the modification has potential influence on downstream projects,
this PR should be tested with downstream projects, like MMDet or
MMDet3D.
4. The documentation has been modified accordingly, like docstring or
example tutorials.
## Motivation
We will support full precision training on the next generation Ascend
NPU, so there is no need to enable mixed precision by default.
## Modification
Determine whether the current chip supports full precision training, and
automatically enable mixed precision.
## BC-breaking (Optional)
Not affected.
## Use cases (Optional)
We have verified the correctness on the Ascend NPU.
* [Fix] Fix mmseg.api.inference inference_segmentor
Motivation
Fix inference_segmentor not working with multiple images path or images. List[str/ndarray]
Modification
- process images if instance is list
* fix typo
* Update mmseg/apis/inference.py
Co-authored-by: Hakjin Lee <nijkah@gmail.com>
Co-authored-by: Hakjin Lee <nijkah@gmail.com>
* [Enhance] New-style CPU training and inference.
* assert mmcv version
* SyncBN to BN in training and testing
* SyncBN to BN in training and testing
* upload untracked files to this branch
* delete gpu_ids
* fix bugs
* assert args.gpu_id in train.py
* use cfg.gpu_ids = [args.gpu_id]
* use cfg.gpu_ids = [args.gpu_id]
* fix typo
* fix typo
* fix typos
* Support progressive test with fewer memory cost.
* Temp code
* Using processor to refactor evaluation workflow.
* refactor eval hook.
* Fix process bar.
* Fix middle save argument.
* Modify some variable name of dataset evaluate api.
* Modify some viriable name of eval hook.
* Fix some priority bugs of eval hook.
* Depreciated efficient_test.
* Fix training progress blocked by eval hook.
* Depreciated old test api.
* Fix test api error.
* Modify outer api.
* Build a sampler test api.
* TODO: Refactor format_results.
* Modify variable names.
* Fix num_classes bug.
* Fix sampler index bug.
* Fix grammaly bug.
* Support batch sampler.
* More readable test api.
* Remove some command arg and fix eval hook bug.
* Support format-only arg.
* Modify format_results of datasets.
* Modify tool which use test apis.
* support cityscapes eval
* fixed cityscapes
* 1. Add comments for batch_sampler;
2. Keep eval hook api same and add deprecated warning;
3. Add doc string for dataset.pre_eval;
* Add efficient_test doc string.
* Modify test tool to compat old version.
* Modify eval hook to compat with old version.
* Modify test api to compat old version api.
* Sampler explanation.
* update warning
* Modify deploy_test.py
* compatible with old output, add efficient test back
* clear logic of exclusive
* Warning about efficient_test.
* Modify format_results save folder.
* Fix bugs of format_results.
* Modify deploy_test.py.
* Update doc
* Fix deploy test bugs.
* Fix custom dataset unit tests.
* Fix dataset unit tests.
* Fix eval hook unit tests.
* Fix some imcompatible.
* Add pre_eval argument for eval hooks.
* Update eval hook doc string.
* Make pre_eval false in default.
* Add unit tests for dataset format_results.
* Fix some comments and bc-breaking bug.
* Fix pre_eval set cfg field.
* Remove redundant codes.
Co-authored-by: Jiarui XU <xvjiarui0826@gmail.com>
* add inference test
* fix E501 line too long (81 > 79 characters
* fix wrong config path
* fix num of augmentations (2) != num of image meta (1)
* Update test_inference.py
Co-authored-by: Jerry Jiarui XU <xvjiarui0826@gmail.com>
