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[Feature] Resume from the latest checkpoint automatically. #61
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@@ Coverage Diff @@
## master #61 +/- ##
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- Coverage 58.50% 58.46% -0.05%
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Files 86 87 +1
Lines 3114 3154 +40
Branches 570 581 +11
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+ Hits 1822 1844 +22
- Misses 1205 1223 +18
Partials 87 87
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# Conflicts: # mmrazor/apis/mmcls/train.py # mmrazor/apis/mmdet/train.py # mmrazor/apis/mmseg/train.py # mmrazor/utils/__init__.py # tools/mmcls/train_mmcls.py # tools/mmdet/train_mmdet.py # tools/mmseg/train_mmseg.py
pppppM
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…b#61) * support auto-resume * support auto-resume * support auto-resume * support auto-resume Co-authored-by: pppppM <67539920+pppppM@users.noreply.github.com>
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…b#61) * support auto-resume * support auto-resume * support auto-resume * support auto-resume Co-authored-by: pppppM <67539920+pppppM@users.noreply.github.com>
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* [Refactor] Refactor configs according to new standard (open-mmlab#67) * modify cfg and cfg_util * modify tensorrt config * fix bug * lint * Fix 1. Delete print 2. Modify the return value from "False, None" to "None" and related code 3. Rename 2 get functions * modify apply_marks * [Feature] Refactor ocr config (open-mmlab#71) * add text detection config refactor * add text recognition refactor * add static exporting for mmocr * fix lint * set max space in child config * use Sequence[int] instead * add assert input_shape * fix static bug and add ppl ort and trt static (open-mmlab#77) * [Feature] Refine setup.py (open-mmlab#61) * add setup.py and related files * lint * Edit requirements * modify onnx version * modify according to comments * [Refactor] Refactor mmseg configs (open-mmlab#73) * refactor mmseg config * change create_input * fix lint * fix lint * fix lint * fix yapf * fix yapf * update export * remove Segmentation * remove tast assert * add onnx_config * remove hardcode * Inherit with static * Remove blank line * Add segmentation task enum * add assert task * mmocr version 0.3.0 (open-mmlab#79) * add dump_info * [Feature]: Refactor config in mmdet (open-mmlab#75) * support onnxruntime * add two stage * test two-stage ort and ppl * update fcos post_params * fix calib * test ok with maskrcnn dynamic * add empty line * add static into config filename * add input_shape to create_input in mmdet * add static to some configs * remove todo codes * remove partition config in base * refactor create_input * rename task name in mmdet * return None if input_shape is None * add size info into mmdet configs filenames * reorganize mmdet configs * add object detection task for mmdet * rename get_mmdet_params * keep naming style consistent * update post_params for fcos * fix typo in ncnn config * [Refactor] Refactor mmedit static config (open-mmlab#78) * add static cfg * update create_input * [Refactor]: Refactor mmcls configs (open-mmlab#74) * refactor mmcls2.0 * fix classify_tensorrt_dynamic.py * fix classify_tensorrt_dynmic.py * classify_tensorrt_dynamic_int8.py * fix file name * fix ncnn ppl * updata prepare_input.py * update utils.py * updata constant.py * add * fix prepare_input.py * fix prepare_input.py * add static config file * add blank lines * fix prepare_input.py(wait test) * fix input_shape(wait test) * Update prepare_input.py * fix classification_tensorrt_dynamic(wait test) * fix classification_tensorrt_dynamic_int8(wait test) * fix classification_tensorrt_static_int8(wait test) * Rename classification_tensorrt_dynamic.py to classification_tensorrt_dynamic-224x224-224x224.py * Rename classification_tensorrt_dynamic_int8.py to classification_tensorrt_dynamic_int8-224x224-224x224.py * Rename classification_tensorrt_dynamic_int8-224x224-224x224.py to classification_tensorrt_int8_dynamic_224x224-224x224.py * Rename classification_tensorrt_dynamic-224x224-224x224.py to classification_tensorrt_dynamic_224x224-224x224.py * Rename classification_tensorrt_static.py to classification_tensorrt_static_224x224.py * Rename classification_tensorrt_static_int8.py to classification_tensorrt_int8_static_224x224.py * Update prepare_input.py * Rename classification_tensorrt_dynamic_224x224-224x224.py to classification_tensorrt_dynamic-224x224-224x224.py * Rename classification_tensorrt_int8_dynamic_224x224-224x224.py to classification_tensorrt_int8-dynamic_224x224-224x224.py * Rename classification_tensorrt_int8-dynamic_224x224-224x224.py to classification_tensorrt_int8_dynamic-224x224-224x224.py * Rename classification_tensorrt_int8_static_224x224.py to classification_tensorrt_int8_static-224x224.py * Rename classification_tensorrt_static_224x224.py to classification_tensorrt_static-224x224.py * Update prepare_input.py * Update prepare_input.py * Update prepare_input.py * Update prepare_input.py * Update prepare_input.py * Update prepare_input.py * Update prepare_input.py * change logging msg Co-authored-by: maningsheng <mnsheng@yeah.net> * fix * fix else branch * fix bug for trt in mmseg * enable dump trt info * fix trt static for mmdet * remove two-stage_partition_tensorrt_static-800x1344 config * fix wrong backend in ppl config * fix partition calibration Co-authored-by: Yifan Zhou <singlezombie@163.com> Co-authored-by: AllentDan <41138331+AllentDan@users.noreply.github.com> Co-authored-by: hanrui1sensetime <83800577+hanrui1sensetime@users.noreply.github.com> Co-authored-by: RunningLeon <maningsheng@sensetime.com> Co-authored-by: VVsssssk <88368822+VVsssssk@users.noreply.github.com> Co-authored-by: maningsheng <mnsheng@yeah.net> Co-authored-by: AllentDan <AllentDan@yeah.net>
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* Remove deepcopy * Fix test
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Thanks for your contribution and we appreciate it a lot. The following instructions would make your pull request more healthy and more easily get feedback. If you do not understand some items, don't worry, just make the pull request and seek help from maintainers.
Motivation
Resume from the latest checkpoint automatically without specifying the path of the checkpoint.
Modified from mmdet pr#6727
Modification
Add a new argument auto-resume in tools/mmcls/train.py, tools/mmdet/train.py and tools/mmseg/train.py, and add a new function find_latest_checkpoint in mmrazor/utils/misc.py.
BC-breaking (Optional)
Does the modification introduce changes that break the backward compatibility of the downstream repositories?
If so, please describe how it breaks the compatibility and how the downstream projects should modify their code to keep compatibility with this PR.
Use cases (Optional)
If this PR introduces a new feature, it is better to list some use cases here and update the documentation.
Checklist
Before PR:
After PR: