Add absolute of matrix format #636

yhmtsai · 2020-09-04T20:48:42Z

This PR adds the absolute (inplace/outplace) of the matrix which is related to #634 and #528.

~~add make_complex~~ to_complex/real
make to_complex/real and remove_complex work for class or scalar/complex
Note. Can not use remove_complex<class> as friend class. Need to use class<remove_complex<V>, I>. this type helper should work in the other situation.
add inplace_absolute_array and outplace_absolute_array
~~format->turn_absolute(), format->apply_absolute()~~, format->compute_absolute_inplace() is inplace absolute function: format -> format
~~auto result = format->get_absolute()~~ auto result = format->compute_absolute() is outplace absolute function: format -> remove_complex (result type)
Add AbsoluteComputable interface and compute_absolute_linop can be used with LinOp.
After this PR, need /bigobj for all MSVC.

codecov · 2020-09-05T00:02:10Z

Codecov Report

Merging #636 into develop will increase coverage by 0.07%.
The diff coverage is 96.14%.

@@             Coverage Diff             @@
##           develop     #636      +/-   ##
===========================================
+ Coverage    92.88%   92.96%   +0.07%     
===========================================
  Files          303      307       +4     
  Lines        21331    21763     +432     
===========================================
+ Hits         19814    20232     +418     
- Misses        1517     1531      +14

Impacted Files	Coverage Δ
core/base/extended_float.hpp	`91.26% <ø> (ø)`
core/device_hooks/common_kernels.inc.cpp	`0.00% <0.00%> (ø)`
include/ginkgo/core/matrix/coo.hpp	`94.73% <ø> (ø)`
include/ginkgo/core/matrix/csr.hpp	`47.72% <ø> (ø)`
include/ginkgo/core/matrix/dense.hpp	`97.70% <ø> (ø)`
include/ginkgo/core/matrix/diagonal.hpp	`100.00% <ø> (ø)`
include/ginkgo/core/matrix/ell.hpp	`100.00% <ø> (ø)`
include/ginkgo/core/matrix/sellp.hpp	`89.74% <ø> (ø)`
include/ginkgo/core/base/lin_op.hpp	`95.50% <33.33%> (-2.17%)`	⬇️
core/test/base/lin_op.cpp	`88.88% <79.31%> (-3.52%)`	⬇️
... and 36 more

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pratikvn

Maybe emplace is more suitable than inplace ? See definition and usage in std::vector::emplace_back()

And with this instead of turn_absolute, maybe emplace_absolute is better ?

upsj · 2020-09-07T15:42:01Z

I like inplace, since it is a pretty common term for what we are doing (compute the absolute and replace the values by it).
I would suggest some alternatives for the names, though, since outplace sounds a bit off to me:
LinOp compute_absolute() and void compute_absolute_inplace()

tcojean · 2020-09-07T17:19:21Z

inplace is definitely the proper term here and it's actually used often in linear algebra in particular https://en.wikipedia.org/wiki/In-place_matrix_transposition (also similar, look for inplace decomposition).
As Tobias says, outplace does seem a bit off although it's probably the proper antonym. I would rather go with Tobias suggestion of outplace being the non qualified default and inplace being specifically qualified in the function name.

fritzgoebel

LGTM, only a few minor comments

common/matrix/dense_kernels.hpp.inc

core/matrix/csr.cpp

core/test/base/lin_op.cpp

include/ginkgo/core/base/lin_op.hpp

include/ginkgo/core/matrix/csr.hpp

reference/test/components/absolute_array.cpp

reference/test/matrix/csr_kernels.cpp

upsj

LGTM! Only a few nits and two suggestions for naming: make_complex -> add_complex and outplace_absolute_type -> just absolute_type. Outplace is not a commonly used term, so while it is perfectly fine in the implementation, in my opinion the public interface should aim to use names as intuitive as possible. outplace_absolute_type would mainly make sense if there was also inplace_absolute_type, but since this is just the same type as this, we don't need it.

core/matrix/ell.cpp

upsj · 2020-09-11T10:28:14Z

hip/test/matrix/coo_kernels.hip.cpp

+ mtx->compute_absolute_inplace();
+ dmtx->compute_absolute_inplace();
+
+ GKO_ASSERT_MTX_NEAR(mtx.get(), dmtx.get(), 1e-14);


(Comment for all tests in general) I believe you don't need the .get() here, it gets removed by gko::test::assertions::detail::plain_ptr; internally, as far as I know

I only refine the modification part in this PR.

include/ginkgo/core/base/math.hpp

include/ginkgo/core/matrix/csr.hpp

tcojean

LGTM. Some small comments.

core/matrix/csr.cpp

core/matrix/hybrid.cpp

core/test/base/lin_op.cpp

include/ginkgo/core/base/math.hpp

include/ginkgo/core/matrix/csr.hpp

1. rename turn_absolute -> apply_absolute 2. add AbsoluteComputable for LinOp usage

Co-authored-by: Tobias Ribizel <[email protected]>

1. remove/add_complex 2. to_real/complex alias 3. using absolute_type not outplace_absolute_type 4. remove unneeded .get() in test Co-authored-by: Tobias Ribizel <[email protected]>

include/ginkgo/core/base/math.hpp

stale

yhmtsai · 2020-09-17T13:05:01Z

Update:

adding to_complex/real
add get_strategy in Hybrid which allows get the same strategy with the new HybType
minimal_storage_limit will narrow to imbalance_limt with same config when the sizeof(VT)/sizeof(IT) are different such that
the new Hyb distribution is same as strategy.
change EnableAbsoluteComputation<ConcreteLinOp> to EnableAbsoluteComputation<AbsoluteLinOp> to give easily implementation for non usual cases in future

Co-authored-by: Terry Cojean <[email protected]>

tcojean · 2020-09-23T08:50:06Z

Anyone to re-review this PR so that we can merge it? It was already reviewed previously several times anyway.

thoasm

Part 1 / hopefully 2 of my review.
Mostly contains nits and naming suggestions.

cuda/test/components/absolute_array.cpp

include/ginkgo/core/base/math.hpp

include/ginkgo/core/matrix/coo.hpp

include/ginkgo/core/matrix/csr.hpp

thoasm

LGTM, I mostly have stylistic comments.

core/test/base/math.cpp

core/test/base/lin_op.cpp

hip/test/components/absolute_array.hip.cpp

include/ginkgo/core/matrix/hybrid.hpp

reference/test/components/absolute_array.cpp

reference/test/matrix/dense_kernels.cpp

reference/test/matrix/diagonal_kernels.cpp

- remove unneed void_t on enable_if_t - remove the remove_complex_s, to_complex_s/real_s in gko namespace - refine code style on test according to AAA rule Co-authored-by: Thomas Grützmacher <[email protected]>

sonarcloud · 2020-09-25T12:40:09Z

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Ginkgo release 1.4.0 The Ginkgo team is proud to announce the new Ginkgo minor release 1.4.0. This release brings most of the Ginkgo functionality to the Intel DPC++ ecosystem which enables Intel-GPU and CPU execution. The only Ginkgo features which have not been ported yet are some preconditioners. Ginkgo's mixed-precision support is greatly enhanced thanks to: 1. The new Accessor concept, which allows writing kernels featuring on-the-fly memory compression, among other features. The accessor can be used as header-only, see the [accessor BLAS benchmarks repository](https://github.com/ginkgo-project/accessor-BLAS/tree/develop) as a usage example. 2. All LinOps now transparently support mixed-precision execution. By default, this is done through a temporary copy which may have a performance impact but already allows mixed-precision research. Native mixed-precision ELL kernels are implemented which do not see this cost. The accessor is also leveraged in a new CB-GMRES solver which allows for performance improvements by compressing the Krylov basis vectors. Many other features have been added to Ginkgo, such as reordering support, a new IDR solver, Incomplete Cholesky preconditioner, matrix assembly support (only CPU for now), machine topology information, and more! Supported systems and requirements: + For all platforms, cmake 3.13+ + C++14 compliant compiler + Linux and MacOS + gcc: 5.3+, 6.3+, 7.3+, all versions after 8.1+ + clang: 3.9+ + Intel compiler: 2018+ + Apple LLVM: 8.0+ + CUDA module: CUDA 9.0+ + HIP module: ROCm 3.5+ + DPC++ module: Intel OneAPI 2021.3. Set the CXX compiler to `dpcpp`. + Windows + MinGW and Cygwin: gcc 5.3+, 6.3+, 7.3+, all versions after 8.1+ + Microsoft Visual Studio: VS 2019 + CUDA module: CUDA 9.0+, Microsoft Visual Studio + OpenMP module: MinGW or Cygwin. Algorithm and important feature additions: + Add a new DPC++ Executor for SYCL execution and other base utilities [#648](#648), [#661](#661), [#757](#757), [#832](#832) + Port matrix formats, solvers and related kernels to DPC++. For some kernels, also make use of a shared kernel implementation for all executors (except Reference). [#710](#710), [#799](#799), [#779](#779), [#733](#733), [#844](#844), [#843](#843), [#789](#789), [#845](#845), [#849](#849), [#855](#855), [#856](#856) + Add accessors which allow multi-precision kernels, among other things. [#643](#643), [#708](#708) + Add support for mixed precision operations through apply in all LinOps. [#677](#677) + Add incomplete Cholesky factorizations and preconditioners as well as some improvements to ILU. [#672](#672), [#837](#837), [#846](#846) + Add an AMGX implementation and kernels on all devices but DPC++. [#528](#528), [#695](#695), [#860](#860) + Add a new mixed-precision capability solver, Compressed Basis GMRES (CB-GMRES). [#693](#693), [#763](#763) + Add the IDR(s) solver. [#620](#620) + Add a new fixed-size block CSR matrix format (for the Reference executor). [#671](#671), [#730](#730) + Add native mixed-precision support to the ELL format. [#717](#717), [#780](#780) + Add Reverse Cuthill-McKee reordering [#500](#500), [#649](#649) + Add matrix assembly support on CPUs. [#644](#644) + Extends ISAI from triangular to general and spd matrices. [#690](#690) Other additions: + Add the possibility to apply real matrices to complex vectors. [#655](#655), [#658](#658) + Add functions to compute the absolute of a matrix format. [#636](#636) + Add symmetric permutation and improve existing permutations. [#684](#684), [#657](#657), [#663](#663) + Add a MachineTopology class with HWLOC support [#554](#554), [#697](#697) + Add an implicit residual norm criterion. [#702](#702), [#818](#818), [#850](#850) + Row-major accessor is generalized to more than 2 dimensions and a new "block column-major" accessor has been added. [#707](#707) + Add an heat equation example. [#698](#698), [#706](#706) + Add ccache support in CMake and CI. [#725](#725), [#739](#739) + Allow tuning and benchmarking variables non intrusively. [#692](#692) + Add triangular solver benchmark [#664](#664) + Add benchmarks for BLAS operations [#772](#772), [#829](#829) + Add support for different precisions and consistent index types in benchmarks. [#675](#675), [#828](#828) + Add a Github bot system to facilitate development and PR management. [#667](#667), [#674](#674), [#689](#689), [#853](#853) + Add Intel (DPC++) CI support and enable CI on HPC systems. [#736](#736), [#751](#751), [#781](#781) + Add ssh debugging for Github Actions CI. [#749](#749) + Add pipeline segmentation for better CI speed. [#737](#737) Changes: + Add a Scalar Jacobi specialization and kernels. [#808](#808), [#834](#834), [#854](#854) + Add implicit residual log for solvers and benchmarks. [#714](#714) + Change handling of the conjugate in the dense dot product. [#755](#755) + Improved Dense stride handling. [#774](#774) + Multiple improvements to the OpenMP kernels performance, including COO, an exclusive prefix sum, and more. [#703](#703), [#765](#765), [#740](#740) + Allow specialization of submatrix and other dense creation functions in solvers. [#718](#718) + Improved Identity constructor and treatment of rectangular matrices. [#646](#646) + Allow CUDA/HIP executors to select allocation mode. [#758](#758) + Check if executors share the same memory. [#670](#670) + Improve test install and smoke testing support. [#721](#721) + Update the JOSS paper citation and add publications in the documentation. [#629](#629), [#724](#724) + Improve the version output. [#806](#806) + Add some utilities for dim and span. [#821](#821) + Improved solver and preconditioner benchmarks. [#660](#660) + Improve benchmark timing and output. [#669](#669), [#791](#791), [#801](#801), [#812](#812) Fixes: + Sorting fix for the Jacobi preconditioner. [#659](#659) + Also log the first residual norm in CGS [#735](#735) + Fix BiCG and HIP CSR to work with complex matrices. [#651](#651) + Fix Coo SpMV on strided vectors. [#807](#807) + Fix segfault of extract_diagonal, add short-and-fat test. [#769](#769) + Fix device_reset issue by moving counter/mutex to device. [#810](#810) + Fix `EnableLogging` superclass. [#841](#841) + Support ROCm 4.1.x and breaking HIP_PLATFORM changes. [#726](#726) + Decreased test size for a few device tests. [#742](#742) + Fix multiple issues with our CMake HIP and RPATH setup. [#712](#712), [#745](#745), [#709](#709) + Cleanup our CMake installation step. [#713](#713) + Various simplification and fixes to the Windows CMake setup. [#720](#720), [#785](#785) + Simplify third-party integration. [#786](#786) + Improve Ginkgo device arch flags management. [#696](#696) + Other fixes and improvements to the CMake setup. [#685](#685), [#792](#792), [#705](#705), [#836](#836) + Clarification of dense norm documentation [#784](#784) + Various development tools fixes and improvements [#738](#738), [#830](#830), [#840](#840) + Make multiple operators/constructors explicit. [#650](#650), [#761](#761) + Fix some issues, memory leaks and warnings found by MSVC. [#666](#666), [#731](#731) + Improved solver memory estimates and consistent iteration counts [#691](#691) + Various logger improvements and fixes [#728](#728), [#743](#743), [#754](#754) + Fix for ForwardIterator requirements in iterator_factory. [#665](#665) + Various benchmark fixes. [#647](#647), [#673](#673), [#722](#722) + Various CI fixes and improvements. [#642](#642), [#641](#641), [#795](#795), [#783](#783), [#793](#793), [#852](#852) Related PR: #857

Release 1.4.0 to master The Ginkgo team is proud to announce the new Ginkgo minor release 1.4.0. This release brings most of the Ginkgo functionality to the Intel DPC++ ecosystem which enables Intel-GPU and CPU execution. The only Ginkgo features which have not been ported yet are some preconditioners. Ginkgo's mixed-precision support is greatly enhanced thanks to: 1. The new Accessor concept, which allows writing kernels featuring on-the-fly memory compression, among other features. The accessor can be used as header-only, see the [accessor BLAS benchmarks repository](https://github.com/ginkgo-project/accessor-BLAS/tree/develop) as a usage example. 2. All LinOps now transparently support mixed-precision execution. By default, this is done through a temporary copy which may have a performance impact but already allows mixed-precision research. Native mixed-precision ELL kernels are implemented which do not see this cost. The accessor is also leveraged in a new CB-GMRES solver which allows for performance improvements by compressing the Krylov basis vectors. Many other features have been added to Ginkgo, such as reordering support, a new IDR solver, Incomplete Cholesky preconditioner, matrix assembly support (only CPU for now), machine topology information, and more! Supported systems and requirements: + For all platforms, cmake 3.13+ + C++14 compliant compiler + Linux and MacOS + gcc: 5.3+, 6.3+, 7.3+, all versions after 8.1+ + clang: 3.9+ + Intel compiler: 2018+ + Apple LLVM: 8.0+ + CUDA module: CUDA 9.0+ + HIP module: ROCm 3.5+ + DPC++ module: Intel OneAPI 2021.3. Set the CXX compiler to `dpcpp`. + Windows + MinGW and Cygwin: gcc 5.3+, 6.3+, 7.3+, all versions after 8.1+ + Microsoft Visual Studio: VS 2019 + CUDA module: CUDA 9.0+, Microsoft Visual Studio + OpenMP module: MinGW or Cygwin. Algorithm and important feature additions: + Add a new DPC++ Executor for SYCL execution and other base utilities [#648](#648), [#661](#661), [#757](#757), [#832](#832) + Port matrix formats, solvers and related kernels to DPC++. For some kernels, also make use of a shared kernel implementation for all executors (except Reference). [#710](#710), [#799](#799), [#779](#779), [#733](#733), [#844](#844), [#843](#843), [#789](#789), [#845](#845), [#849](#849), [#855](#855), [#856](#856) + Add accessors which allow multi-precision kernels, among other things. [#643](#643), [#708](#708) + Add support for mixed precision operations through apply in all LinOps. [#677](#677) + Add incomplete Cholesky factorizations and preconditioners as well as some improvements to ILU. [#672](#672), [#837](#837), [#846](#846) + Add an AMGX implementation and kernels on all devices but DPC++. [#528](#528), [#695](#695), [#860](#860) + Add a new mixed-precision capability solver, Compressed Basis GMRES (CB-GMRES). [#693](#693), [#763](#763) + Add the IDR(s) solver. [#620](#620) + Add a new fixed-size block CSR matrix format (for the Reference executor). [#671](#671), [#730](#730) + Add native mixed-precision support to the ELL format. [#717](#717), [#780](#780) + Add Reverse Cuthill-McKee reordering [#500](#500), [#649](#649) + Add matrix assembly support on CPUs. [#644](#644) + Extends ISAI from triangular to general and spd matrices. [#690](#690) Other additions: + Add the possibility to apply real matrices to complex vectors. [#655](#655), [#658](#658) + Add functions to compute the absolute of a matrix format. [#636](#636) + Add symmetric permutation and improve existing permutations. [#684](#684), [#657](#657), [#663](#663) + Add a MachineTopology class with HWLOC support [#554](#554), [#697](#697) + Add an implicit residual norm criterion. [#702](#702), [#818](#818), [#850](#850) + Row-major accessor is generalized to more than 2 dimensions and a new "block column-major" accessor has been added. [#707](#707) + Add an heat equation example. [#698](#698), [#706](#706) + Add ccache support in CMake and CI. [#725](#725), [#739](#739) + Allow tuning and benchmarking variables non intrusively. [#692](#692) + Add triangular solver benchmark [#664](#664) + Add benchmarks for BLAS operations [#772](#772), [#829](#829) + Add support for different precisions and consistent index types in benchmarks. [#675](#675), [#828](#828) + Add a Github bot system to facilitate development and PR management. [#667](#667), [#674](#674), [#689](#689), [#853](#853) + Add Intel (DPC++) CI support and enable CI on HPC systems. [#736](#736), [#751](#751), [#781](#781) + Add ssh debugging for Github Actions CI. [#749](#749) + Add pipeline segmentation for better CI speed. [#737](#737) Changes: + Add a Scalar Jacobi specialization and kernels. [#808](#808), [#834](#834), [#854](#854) + Add implicit residual log for solvers and benchmarks. [#714](#714) + Change handling of the conjugate in the dense dot product. [#755](#755) + Improved Dense stride handling. [#774](#774) + Multiple improvements to the OpenMP kernels performance, including COO, an exclusive prefix sum, and more. [#703](#703), [#765](#765), [#740](#740) + Allow specialization of submatrix and other dense creation functions in solvers. [#718](#718) + Improved Identity constructor and treatment of rectangular matrices. [#646](#646) + Allow CUDA/HIP executors to select allocation mode. [#758](#758) + Check if executors share the same memory. [#670](#670) + Improve test install and smoke testing support. [#721](#721) + Update the JOSS paper citation and add publications in the documentation. [#629](#629), [#724](#724) + Improve the version output. [#806](#806) + Add some utilities for dim and span. [#821](#821) + Improved solver and preconditioner benchmarks. [#660](#660) + Improve benchmark timing and output. [#669](#669), [#791](#791), [#801](#801), [#812](#812) Fixes: + Sorting fix for the Jacobi preconditioner. [#659](#659) + Also log the first residual norm in CGS [#735](#735) + Fix BiCG and HIP CSR to work with complex matrices. [#651](#651) + Fix Coo SpMV on strided vectors. [#807](#807) + Fix segfault of extract_diagonal, add short-and-fat test. [#769](#769) + Fix device_reset issue by moving counter/mutex to device. [#810](#810) + Fix `EnableLogging` superclass. [#841](#841) + Support ROCm 4.1.x and breaking HIP_PLATFORM changes. [#726](#726) + Decreased test size for a few device tests. [#742](#742) + Fix multiple issues with our CMake HIP and RPATH setup. [#712](#712), [#745](#745), [#709](#709) + Cleanup our CMake installation step. [#713](#713) + Various simplification and fixes to the Windows CMake setup. [#720](#720), [#785](#785) + Simplify third-party integration. [#786](#786) + Improve Ginkgo device arch flags management. [#696](#696) + Other fixes and improvements to the CMake setup. [#685](#685), [#792](#792), [#705](#705), [#836](#836) + Clarification of dense norm documentation [#784](#784) + Various development tools fixes and improvements [#738](#738), [#830](#830), [#840](#840) + Make multiple operators/constructors explicit. [#650](#650), [#761](#761) + Fix some issues, memory leaks and warnings found by MSVC. [#666](#666), [#731](#731) + Improved solver memory estimates and consistent iteration counts [#691](#691) + Various logger improvements and fixes [#728](#728), [#743](#743), [#754](#754) + Fix for ForwardIterator requirements in iterator_factory. [#665](#665) + Various benchmark fixes. [#647](#647), [#673](#673), [#722](#722) + Various CI fixes and improvements. [#642](#642), [#641](#641), [#795](#795), [#783](#783), [#793](#793), [#852](#852) Related PR: #866

yhmtsai added is:new-feature A request or implementation of a feature that does not exist yet. type:matrix-format This is related to the Matrix formats mod:all This touches all Ginkgo modules. labels Sep 4, 2020

yhmtsai requested review from upsj, pratikvn, thoasm, hartwiganzt, tcojean and fritzgoebel September 4, 2020 20:48

yhmtsai self-assigned this Sep 4, 2020

yhmtsai mentioned this pull request Sep 7, 2020

Amgx parallel graph match reference and fill_seq_array #528

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Feature requests #639

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yhmtsai and others added 8 commits September 16, 2020 18:33

add template_convertor and remove_complex for class

a15d56f

implement absolute array

2351a45

implement Csr absolute

3c5d7ff

always use bigobj

648a6a8

coo/ell/sellp/hybrid/diagonal absolute

728b7f4

implement dense absolute

f5433aa

rename turn_absolute and add interface for LinOp

4c2f70d

1. rename turn_absolute -> apply_absolute 2. add AbsoluteComputable for LinOp usage

get/apply_absolute -> compute_absolute(_inplace)

b595be9

Co-authored-by: Tobias Ribizel <[email protected]>

rename make_complex, use absolute_type only...etc

69a5c5a

1. remove/add_complex 2. to_real/complex alias 3. using absolute_type not outplace_absolute_type 4. remove unneeded .get() in test Co-authored-by: Tobias Ribizel <[email protected]>

yhmtsai force-pushed the handle_complex_of_class branch from 7d9a37a to 424e038 Compare September 16, 2020 16:34

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yhmtsai force-pushed the handle_complex_of_class branch from 424e038 to cc13408 Compare September 17, 2020 12:43

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yhmtsai and others added 3 commits September 17, 2020 16:10

update document, add hybrid get_strategy<Hyb>, test

1ee6222

Co-authored-by: Terry Cojean <[email protected]>

use absoluteLinOp template not concreteLinOp

97a9e34

to_complex/real and remove_complex only

81fc85a

yhmtsai force-pushed the handle_complex_of_class branch from cc13408 to 81fc85a Compare September 17, 2020 14:10

split get_strategy<Hyb> impl, decl; check HybType

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tcojean requested review from pratikvn and fritzgoebel September 22, 2020 12:57

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yhmtsai force-pushed the handle_complex_of_class branch from 1768a3e to 39533c2 Compare September 24, 2020 23:49

review update (remove unneeded, refine format)

e0b703a

- remove unneed void_t on enable_if_t - remove the remove_complex_s, to_complex_s/real_s in gko namespace - refine code style on test according to AAA rule Co-authored-by: Thomas Grützmacher <[email protected]>

yhmtsai force-pushed the handle_complex_of_class branch from 39533c2 to e0b703a Compare September 25, 2020 08:34

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upsj commented Sep 7, 2020 •

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tcojean commented Sep 7, 2020 •

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