* [Fix] Fix the problem that the instance cannot reuse when overwriting the file client.
* Remove _overridden_backends and _overridden_prefixes, and pop the old instance when overwriting the file client.
* add unittest
* fix prefix error
* modify clear_backend to overridden_backend
* Delete redundant comments.
* Fix the bug met in using nasfpn
Fix the bug met in using nasfpn which is mentioned at https://github.com/open-mmlab/mmdetection/issues/5987.
Avoid the strong restrictions of _resize function in BaseMergeCell:
1. When Downsampling the feature map, the feature map's shape must be divisible by the target size. We pad zero around feature map before max_pool2d opt to make it always divisible. (line 102 ~ 107)
2. Considering the different downsampling scale of H and W, shape[-2] and shape[-1] are involed in the definition of kernel_size. (line 110)
* Update merge_cells.py
check flake8 & isort
* Update merge_cells.py
* Update merge_cells.py
yapf
* Update mmcv/ops/merge_cells.py
X_pad rename to padding_x
Co-authored-by: Mashiro <57566630+HAOCHENYE@users.noreply.github.com>
* Update merge_cells.py
format the code style after renameing the X_pad to padding_x
* Update test_merge_cells.py
Mainly test the downsampling resize in BaseMergeCell. The smaller target size is set to (14, 7), the classical feature map's size in the last few stages of the backbone, which will product different downsampling scales in different dims.
* Update test_merge_cells.py
add "# Copyright (c) OpenMMLab. All rights reserved."
* Update merge_cells.py
format the variable name
* Update test_merge_cells.py
Testing divisible and indivisible situations simultaneously
* Update mmcv/ops/merge_cells.py
fix the bug when h is indivisible and w is divisible, the pad_w will be padded unreasonable.
Co-authored-by: Zaida Zhou <58739961+zhouzaida@users.noreply.github.com>
* Update mmcv/ops/merge_cells.py
fix the bug when w is indivisible and h is divisible, the pad_h will be padded unreasonable.
Co-authored-by: Zaida Zhou <58739961+zhouzaida@users.noreply.github.com>
* fix undefined error
* Update merge_cells.py
make pad_h, pad_w more readable
* Update test_merge_cells.py
use @pytest.mark.parametrize instead of 'for' methor
* Update merge_cells.py
* Update test_merge_cells.py
isort
* Update merge_cells.py
isort
Co-authored-by: Mashiro <57566630+HAOCHENYE@users.noreply.github.com>
Co-authored-by: Zaida Zhou <58739961+zhouzaida@users.noreply.github.com>
* config dump fix
dump should not depend on how config was loaded only where it is dumped
changed checks for type to the given filename instead of the source filename
* defined test_fromdict and fixed dump function
it might be more convoluted than it needs to be but the formatting depends on the extension of the argument or the extension of the self.filename
* config dump defaults to returning pretty_text, test_fromdict renamed to test_dump_from_dict
* some reformatting in docstrings
* refine unittest
* fix unit test as comment
* Refine docstring
* minor refinement
* import mmcv
* fix lint
Co-authored-by: HAOCHENYE <21724054@zju.edu.cn>
Co-authored-by: Zaida Zhou <58739961+zhouzaida@users.noreply.github.com>
* add rotated_feature_align cpu implementation
* add rotated_feature_align onnxruntime implementation
* Update code for advices from grimoire
Remove useless comment from mmcv/ops/csrc/pytorch/cpu/rotated_feature_align.cpp
Replace ambiguous function name atomicAdd in mmcv/ops/csrc/pytorch/cpu/rotated_feature_align.cpp
Simplify unit test with parameter in tests/test_ops/test_rotated_feature_align.py
Use fma in interpolate in mmcv/ops/csrc/onnxruntime/cpu/rotated_feature_align.cpp mmcv/ops/csrc/pytorch/cpu/rotated_feature_align.cpp
* Inline the function to reduce the overhead of the function call
Use fma in interpolate
* enhance get_torchvision_models
* simplify logic
* Dump ckpt in torchvision lower than 0.13.0 to a json file
* add json
* refactor load urls logic
* fix unit test
* change url key to lower letters
* check torchvision version rather than check torch version in unittest
* Fix CI and refine test logic of torchvision version
* add comment
* support compare pre-release version
* support loaad modeel like torchvision
* refine comment.
* fix unit test and comment
* fxi unit test bug
* support get model by lower weights
* Make sure padding size is not negative
If Resize maintains aspect ratio, could be the case that image shape is bigger than resize value.
* Test pad shape smaller than image shape
* Fix lint
* Remove whitespaces
* update support for linearly learning rate decay
* Fix LinearAnnealingLrUpdaterHook, update LinearAnnealingMomentumUpdaterHook, add unit test
add docstring
add docstring
update linear lr momentum schedule test
fix ci
Fix CI
* add lr and momentum hook to runner and hooks package
add lr and momentum hook to runner and hooks package
* replace multi_optimziers with multi_optimizers
Co-authored-by: HAOCHENYE <21724054@zju.edu.cn>
Co-authored-by: Mashiro <57566630+HAOCHENYE@users.noreply.github.com>
* Add .owners.yml to mark daily issue shift
* Update .owners.yml
fix end of file
* Add __copy__() to Config
* fix format in config.py
* fix format in test_copy
* fix format in config.py
* Update config.py
* Update tests/test_utils/test_config.py
Co-authored-by: Zaida Zhou <58739961+zhouzaida@users.noreply.github.com>
Co-authored-by: Zaida Zhou <58739961+zhouzaida@users.noreply.github.com>
* fix interface for RoIAlignRotated
* Add a unit test for RoIAlignRotated
* Make a unit test for RoIAlignRotated concise
* fix interface for RoIAlignRotated
* Refactor ext_module.nms_rotated
* Lint cpp files
* Support deepcopy for Config
* Iterate the `__dict__` of Config directly.
* Use __new__ to avoid unnecessary initialization.
* Improve according to comments
* Fix batched_nms to support nms_rotated
* Update test code for batched_nms with nms_rotated
* Edit indexing the score in nms
* Use -1 indexing for batched_nms
* fix the scatter when input is cpu
* Update _functions.py
Add spaces to comply with the code specification
* add unittests
* add a blank line
* fix unittet
Co-authored-by: zhouzaida <zhouzaida@163.com>
* Add file client to image io
* Fix petrel_client imwrite error
* Add examples to the docstring and delete the file check of imread
* modify docstring v1.3.19->v1.4.1
* Deprecate auto_mkdir parameter and complete test_io.py
* Fix error caused by deleting the mock package in test_io.py
* Add annotation to imencode
* modify imread input assert and delete the judgement of file client 'put' method
* Delete try except in imwrite.
* Add a error file extension unit test.
* skip nms
* judge at beginning
* add test
* remove else
* add more details in docstr including version not
* fix unitest
* fix doc
* fix doc
* fix typo
* resove conversation
* fix link
* detect detect_anomalous_params
* fix default value
* merge two case
* fix none case
* add unitest
* fix typo
* change level to error
* fix type
* add more details in docstr
* [Fix] fix deform conv by add argument
* [Fix] replace useless func with np.repeat and add necessary comment
* [Fix] reduce batch_size and remove useless lines and modify some var name
* [Fix] change position of comments
* [Fix] add im2col_step in the docstring and add two test cases
* [Fix] fix docstring and add comments for test cases
* [Fix] fix docstring
* [Fix] add note, fix issue link and other details
* [Fix] fix docstring details
* [Fix] fix links in docstring
* [Fix] fix docstring details
* [Features] Load optical flow data from bytes
* docstring
* revise base on comments
* compression test data
* compression test data
* docstring
* minors
* restrict the warning message
* and an important keyword in warning description
* a more elegant way of condition
* link format code too long
* fix the stupid spelling mistake
* Use issubclass to restrict warning message.
* maybe this version is more elegant.
* conv + bias + norm warning pytest
* 'created' a warning, hahaha
* isort and yapf format revision
* isort and yapf format revision
* flake8 fail issue
* I have to right this way in order to solve the conflicts between yapf and flake8, sigh...
* fixed test bug
* Add ruby windows installer source.
* Simplified the code and remove ruby source from CONTRIBUTING.md
* use _BatchNorm to simplify the code
* bug fix and add instanceNorm case into warning
* change the warning message to make it more clear
* fix unit test
* DCN cpu version
* add modulated dcn cpu version
* move deform_conv_shape_check to deform conv utils
* add inline to deform_conv_shape_check
* add tests
* run linter
* add newline at file end
* run pre-commit against modulated deform conv cpp
* update saconv test
* run clang-format
* remove cuda device inline
* refactor dcn cuda/cpu functions
* remove DCN util
* remove DCN util hpp from all included files
* Addressing PR comment by refactoring modulated-DCN
* fix lint in cpp files
* add windows CI
* clean versions
* only allow pt1.7 on windows
* fix windows install issue
* add win cpu
* fix win command
* clean unnecessary command
* resolve turbojpeg & tempfile on win
* replace os.readlink with os.path.realpath
* fix windows ci
* close file before removing it
* fix windows ci
* fix symlink on windows
* fix windows ci
* fix windows ci
* fix windows ci
* fix windows ci
* fix windows ci
* fix windows ci
* fix windows ci
* fix windows ci
* fix windows ci
* modify according to comment
Co-authored-by: zhouzaida <zhouzaida@163.com>
* add modulated_deform_conv in onnxruntime support
* Add docs descriptions
* Add gpu test in test_onnx.py
* code format
* remove new usage and move if outside for loop
* use memset when bias is nullptr
* Add gradient cumulative optimizer
fixes#190
* Update optimizer.py
* Update optimizer.py
* fix loss scale improperly in last equivalent_iter
* Add `GradientCumulativeOptimizerHook` in `__init__.py`.
* Add docstring of `GradientCumulativeOptimizerHook`.
* Add type check, BN warning and resume warning. And fix typo, lint the
code.
* Add unit test
* Update docstring example.
* Change GradientCumulativeOptimizerHook `__init__` arguments.
* Add GradientCumulativeOptimzierHook unit tests with IterBasedRunner.
* Add GradientCumulativeFp16OptimizerHook.
* Add unit tests of GradientCumulativeFp16OptimizerHook
* Use '!=' instead of '>' to determine resume
Co-authored-by: Zhiyuan Chen <this@zyc.ai>
* Support deprecation checking in Config
* add unittest for config deprecation
* support reference link in deprecation info
* add doc
* Update config.md
* [Fix] Fix the bug that training log and evaluating log are mixed
* [Fix] Fix the bug that training log and evaluating log are mixed
* fix comment
* fix import error
* refactor
* refactor
* refactor
* clear log_buffer before evaluation
* fix error
* add unittest
* improve digit_version & use it for version_checking
* more testing for digit_version
* setuptools >= 50 is needed
* fix CI
* add debuging log
* >= to ==
* fix lint
* remove
* add failure case
* replace
* fix
* consider TORCH_VERSION == 'parrots'
* add unittest
* digit_version do not deal with the case if 'parrots' in version name.
* add flat cosine lr updater
* add test
* add doc
* update doc
* reformat
* update unittest
* update test flat cos
* remove momentum hook test
* update test
* change assert to ValueError
* fix unittest
* add by_epoch=True unittest
* change to start_percent
* change to start_percent in test
* add torch.roll to onnx
* remove skip test
* add support to torch<170
* add dim=0 for torch==1.9.0
* update fixture function name, add comment in roll symbolic
* Add `is_tracing` to wrap `torch.jit.is_tracing` in different versions.
* Remame `is_tracing` to `is_jit_tracing`
* Ignore `is_jit_tracing` tests in CI.
* porting mmcv for hip
* add nvcc
* fix format
* fix format
* fix bug for carafe
* fix test_utils because rocm_torch not allow set torch.backends.cudnn.benchmark to false
* add LOOSEVERSION
* fix format
* fix format of version
* fix code format
* test for yaml
* fix bug for citest
* fix bug for how to get torch._version_ at setup.py
* Missing check for dir in the 'else' clause
Fixing issue when recursively scanning directories with filenames starting with '.' Without this fix, the `if not entry.name.startswith('.') and entry.is_file()` logic falls through to the `else` clause which in the current code base will error out as it encounters '.' files (e.g. .DS_Store)
* Updated code per comments
* fixing indentation
* fix indenterror and add comment
* remove .DS_Store and add .file
Co-authored-by: zhouzaida <zhouzaida@163.com>
* support print using hooks before running.
* Support to print hook trigger stages.
* Print stage-wise hook infos. And make `stages` as class attribute of
`Hook`
* Add util function `is_method_overriden` and use it in
`Hook.get_trigger_stages`.
* Add unit tests.
* Move `is_method_overriden` to `mmcv/utils/misc.py`
* Improve hook info text.
* Add base_class argument type assertion, and fix some typos.
* Remove `get_trigger_stages` to `get_triggered_stages`
* Use f-string.
* Support image reading while ignoring EXIF orientation info
Add unit test for ignore_orientation flags in imread()
* add documentation for imread
* Add test cases
* Refine default hooks and custom hooks priority rank.
* Add unit tests for custom hooks with string priority.
* Use priority `ABOVE_NORMAL` and `BELOW_NORMAL` instead of `HIGHER` and
`LOWER`.
And add unit tests for custom hook with the same priority as
default hooks.
* Support variables in base files for configs
Signed-off-by: lizz <lizz@sensetime.com>
* Test json and yaml as well
Signed-off-by: lizz <lizz@sensetime.com>
* Add test for recusive base
Signed-off-by: lizz <lizz@sensetime.com>
* Test misleading values
Signed-off-by: lizz <lizz@sensetime.com>
* Improve comments
Signed-off-by: lizz <lizz@sensetime.com>
* Add doc
Signed-off-by: lizz <lizz@sensetime.com>
* Improve doc
Signed-off-by: lizz <lizz@sensetime.com>
* More tests
Signed-off-by: lizz <lizz@sensetime.com>
* Harder test case
Signed-off-by: lizz <lizz@sensetime.com>
* use BASE_KEY instead of base
Signed-off-by: lizz <lizz@sensetime.com>
* minor changes
* change to modulist
* change to Sequential
* replace dropout with attn_drop and proj_drop in MultiheadAttention
* add operation_name for attn
* add drop path and move all ffn args to ffncfgs
* fix typo
* fix a bug when use default value of ffn_cfgs
* fix ffns
* add deprecate warning
* fix deprecate warning
* change to pop kwargs
* support register FFN of transformer
* support batch first
* fix batch first wapper
* fix forward wapper
* fix typo
* fix lint
* add unitest for transformer
* fix unitest
* fix equal
* use allclose
* fix comments
* fix comments
* change configdict to dict
* move drop to a file
* add comments for drop path
* add noqa 501
* move bnc wapper to MultiheadAttention
* move bnc wapper to MultiheadAttention
* use dep warning
* resolve comments
* add unitest:
* rename residual to identity
* revert runner
* msda residual to identity
* rename inp_identity to identity
* fix name
* fix transformer
* remove key in msda
* remove assert for key
Co-authored-by: HIT-cwh <2892770585@qq.com>
Co-authored-by: bkhuang <congee524@gmail.com>
Co-authored-by: Wenwei Zhang <40779233+ZwwWayne@users.noreply.github.com>
* Add score_threshold and max_num to NMS
* Fix codestyle
* Fix codestyle
* Fix inds in nms
* Update nms docstring
* Move score_threshold and max_num arguments
* Fix args order in docstring
* fix lint of c++ file
* Remove torch.onnx.is_in_onnx_export() and add max_num to batched_nms for separate classes.
* Rewrote max_num handling in NMSop.symbolic
* Added processing max_output_boxes_per_class when exporting to TensorRT
* Added score_threshold and max_num for NMS in test_onnx.py and test_tensorrt.py
* Remove _is_value(max_num)
* fix ci errors with torch==1.3.1
* Update test_batched_nms in test_nms.py
* Added tests for preprocess_onnx
* Moved 'test_tensorrt_preprocess.py' and 'preprocess', updated 'remove_tmp_file'.
* Update mmcv/tensorrt/__init__.py
* Fix segfault torch==1.3.1 (remove onnx.checker.check_model)
* Returned 'onnx.checker.check_model' with torch version check
* Changed torch version from 1.3.1 to 1.4.0
* update version check
* remove check for onnx
Co-authored-by: maningsheng <maningsheng@sensetime.com>
* fix fp16 bug on DCNv2
* support fp16 on DCN/DCNv2 when pytorch >= '1.6.0'
* add comment
* Modified the comments
* Unified the usages of '.to()' and '.type_as()'
* Assign different priority to default hooks, and add custom hook register in base runner.
* Add custom hook register in example train file
* Add unittest of custom hook
* Code format
Zaida Zhou
Wencheng Wu
whcao
Danila Rukhovich
del-zhenwu
JarvisKevin
Jiazhen Wang
jmercat
pc
WilliamKyle
q.yao
Artem
Mashiro
Vince Jankovics
Hu Di
Charlyo
VVsssssk
Qiza-lyhm
Tan SU
Sharpiless
Tan SU
Wenhao Wu
Alex Yang
saurbhc
Hakjin Lee
Ma Zerun
RangiLyu
Yue Zhou
bilibilee
imyhxy
fatih
zhanggefan
Hongbin Sun
David de la Iglesia Castro
Shilong Zhang
Luting Wang
zhouzaida
Tong Gao
dingchang
q.yao
Ezra-Yu
Eugene Liu
Miao Zheng
Wenwei Zhang
Leojc
young
Paige Wang
Yining Li
Jerry Jiarui XU
Haodong Duan
Gu Wang
qjqfl
Y_Xuan
Haodong Duan
achaiah
lizz
Junjun2016
Jintao Lin
Dmitry Sidnev
SemyonBevzuk
RunningLeon
v-qjqs
Guangchen Lin