* 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>
* sampler bugfixes
* sampler bugfixes
* reorganize code
* minor fixes
* reorganize code
* minor fixes
* Use `mmcv.runner.get_dist_info` instead of `dist` package to get rank
and world size.
* Add `build_dataloader` unit tests and fix sampler's unit tests.
* Fix unit tests
* Fix unit tests
Co-authored-by: mzr1996 <mzr1996@163.com>
* remove DistSamplerSeedHook for IterBasedRunner
* Register DistSamplerSeedHook for EpochBasedRunner only
Co-authored-by: Ma Zerun <mzr1996@163.com>
Co-authored-by: Ma Zerun <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.
The get_root_logger(log_file=None, log_level=logging.INFO) function does not needs the string type cfg.log_level as input. This bug does not have negative effect.
* 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.
* add mytrain.py for test
* test before layers
* test attr in layers
* test classifier
* delete mytrain.py
* register custom_hooks in runner
* set custom_hooks_config to cfg.get(custom_hooks, None)
* Use build_runner in train api
* Support iter in eval_hook
* Add runner section
* Add test_eval_hook
* Pin mmcv version in install docs
* Replace max_iters with max_epochs
* Set by_epoch=True as default
* Remove trailing space
* Replace DeprecationWarning with UserWarning
* pre-commit
* Fix tests
* 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