* implement training and evaluation on IPU
* fp16 SOTA
* Tput reaches 5600
* 123
* add poptorch dataloder
* change ipu_replicas to ipu-replicas
* add noqa to config long line(website)
* remove ipu dataloder test code
* del one blank line in test_builder
* refine the dataloder initialization
* fix a typo
* refine args for dataloder
* remove an annoted line
* process one more conflict
* adjust code structure in mmcv.ipu
* adjust ipu code structure in mmcv
* IPUDataloader to IPUDataLoader
* align with mmcv
* adjust according to mmcv
* mmcv code structre fixed
Co-authored-by: hudi <dihu@graphcore.ai>
* Support to use `indices` to specify which samples to evaluate.
* Add KFoldDataset wrapper
* Rename 'K' to 'num_splits' accroding to sklearn
* Add `kfold-cross-valid.py`
* Add unit tests
* Add help doc and docstring
* add cam-grad tool
* refactor cam-grad tool
* add docs
* update docs
* Update docs and support Transformer
* remove pictures and use link
* replace example img and finish EN docs
* improve docs
* improve code
* Fix MobileNet V3 configs
* Refactor to support more powerful feature extraction.
* Add unit tests
* Fix unit test
* fix distortion of visualization exapmles in docs
* fix distortion
* fix distortion
* fix distortion
* merge master
* merge fix conficts
* Imporve the tool
* Support use both attribute name and index to get layer
* add default get_target-layers
* add default get_target-layers
* update docs
* update docs
* add additional printt info when not using target-layers
* Imporve docs
* Fix enumerate list.
Co-authored-by: mzr1996 <mzr1996@163.com>
* add pth converter
* minor update on config files, add metafile and readme
* add missing readme and minor fixes
* minor fixes
* Update config names and checkpoint download link
* Update model_zoo.md
Co-authored-by: mzr1996 <mzr1996@163.com>
* [Fix] Analyze logs with single training iteration
* [Fix] Make `plot_curve` with 'accuracy' metric
* [Fix] Assert length of training log records of each epoch is larger than 1
Co-authored-by: Ma Zerun <mzr1996@163.com>
Co-authored-by: Ma Zerun <mzr1996@163.com>
* add vis lr
* add doc
* Update doc and rm load_json_log in analysis
* Update docs
* add unit tests and update docstring
* fix unit-tests
* Use DummyIterBasedRunner and DummyEpochBasedRunner to simulate training
process.
* rm function val and add judge
* update docs
* improve english expression
* Update docs/tools/visualization.md
Co-authored-by: Ma Zerun <mzr1996@163.com>
* fix typo and ImageNet datasize
* fix typo
* update example
Co-authored-by: mzr1996 <mzr1996@163.com>
* Add `title` option in `show_result_pyplot`.
* Add test_torchserver.py
* Add docs about test torchserve
* Update docs and result output.
* Update chinese docs.
* Add RepVGG code.
* Add se_module as plugin.
* Add the repvggA0 primitive config
* Change repvggA0.py to fit mmcls
* Add RepVGG configs
* Add repvgg_to_mmcls
* Add tools/deployment/convert_repvggblock_param_to_deploy.py
* Change configs/repvgg/README.md
* Streamlining the number of configuration files.
* Fix lints
* Delete plugins
* Delete code about plugin.
* Modify the code for using se module.
* Modify config to fit repvgg with se.
* Change se_cfg to allow loading of pre-training parameters.
* Reduce the complexity of the configuration file.
* Finsh unitest for repvgg.
* Fix bug about se in repvgg_to_mmcls.
* Rename convert_repvggblock_param_to_deploy.py to reparameterize_repvgg.py, and delete setting about device.
* test commit
* test commit
* test commit command
* Modify repvgg.py to make the code more readable.
* Add value=0 in F.pad()
* Add se_cfg to arch_settings.
* Fix bug.
* modeify some attr name and Update unit tests
* rename stage_0 to stem and branch_identity to branch_norm
* update unit tests
* add m.eval in unit tests
* [Enhance] Enhence SE layer to support custom squeeze channels. (#417)
* add enhenced SE
* Update
* rm basechannel
* fix docstring
* Update se_layer.py
fix docstring
* [Docs] Add algorithm readme and update meta yml (#418)
* Add README.md for models without checkpoints.
* Update model-index.yml
* Update metafile.yml of seresnet
* [Enhance] Add `hparams` argument in `AutoAugment` and `RandAugment` and some other improvement. (#398)
* Add hparams argument in `AutoAugment` and `RandAugment`.
And `pad_val` supports sequence instead of tuple only.
* Add unit tests for `AutoAugment` and `hparams` in `RandAugment`.
* Use smaller test image to speed up uni tests.
* Use hparams to simplify RandAugment config in swin-transformer.
* Rename augment config name from `pipeline` to `pipelines`.
* Add some commnet ad docstring.
* [Feature] Support classwise weight in losses (#388)
* Add classwise weight in losses:CE,BCE,softBCE
* Update unit test
* rm some extra code
* rm some extra code
* fix broadcast
* fix broadcast
* update unit tests
* use new_tensor
* fix lint
* [Enhance] Better result visualization (#419)
* Imporve result visualization to support wait time and change the backend
to matplotlib.
* Add unit test for visualization
* Add adaptive dpi function
* Rename `imshow_cls_result` to `imshow_infos`.
* Support str in `imshow_infos`
* Improve docstring.
* Bump version to v0.15.0 (#426)
* [CI] Add PyTorch 1.9 and Python 3.9 build workflow, and remove some CI. (#422)
* Add PyTorch 1.9 build workflow, and remove some CI.
* Add Python 3.9 CI
* Show Python 3.9 support.
* [Enhance] Rename the option `--options` in some tools to `--cfg-options`. (#425)
* [Docs] Fix sphinx version (#429)
* [Docs] Add `CITATION.cff` (#428)
* Add CITATION.cff
* Fix typo in setup.py
* Change author in setup.py
* modeify some attr name and Update unit tests
* rename stage_0 to stem and branch_identity to branch_norm
* update unit tests
* add m.eval in unit tests
* Update unit tests
* refactor
* refactor
* Alignment inference accuracy
* Update configs, readme and metafile
* Update readme
* return tuple and fix metafile
* fix unit test
* rm regnet and classifiers changes
* update auto_aug
* update metafile & readme
* use delattr
* rename cfgs
* Update checkpoint url
* Update readme
* Rename config files.
* Update readme and metafile
* add comment
* Update mmcls/models/backbones/repvgg.py
Co-authored-by: Ma Zerun <mzr1996@163.com>
* Update docstring
* Improve docstring.
* Update unittest_testblock
Co-authored-by: Ezra-Yu <1105212286@qq.com>
Co-authored-by: Ma Zerun <mzr1996@163.com>
* Refactor tools folder structure.
* Modify tools/test.py and add eval_metric.py to analysis test output.
* Add new tools `analyze_logs.py` and `print_config.py`.
* Add comment for analysis_tools functions.
* support dynamic shape export to onnx
* update the code and reset the simple_test() of image.py
* fix dynamic_axes name is not a valid input/output name
* add model inference on single image
* rm --eval
* revise doc
* add inference tool and demo
* fix linting
* rename inference_image to inference_model
* infer pred_label and pred_score
* fix linting
* add docstr for inference
* add remove_keys
* add doc for inference
* dump results rather than outputs
* add class_names
* add related infer scripts
* add demo image and the first part of colab tutorial
* conduct evaluation in dataset
* return lst in simple_test
* compuate topk accuracy with numpy
* return outputs in test api
* merge inference and evaluation tool
* fix typo
* rm gt_labels in test conifg
* get gt_labels during evaluation
* sperate the ipython notebook to another PR
* return tensor for onnx_export
* detach var in simple_test
* rm inference script
* rm inference script
* construct data dict to replace LoadImage
* print first predicted result if args.out is None
* modify test_pipeline in inference
* refactor class_names of imagenet
* set class_to_idx as a property in base dataset
* output pred_class during inference
* remove unused docstr
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