Changelog

[2.3.6] - 2023-04-19

Fixed

Fix a CI bug that cpu cumm and spconv use different gcc compiler, must be same.

[2.3.5] - 2023-03-24

Fixed

use a flag to enable large kernel algo (need time to compile at runtime)

[2.3.4] - 2023-03-23

Added

Add SparseGlobalMaxPool and SparseGlobalAvgPool for training only. libspconv don't support it.

[2.3.3] - 2023-02-02

Fixed

Fix int8 nvrtc error when use prebuilt
Fix int8 kernel when run on turing GPU

[2.3.2] - 2023-01-20

Changed

change version

[2.3.1] - 2023-01-20

Changed

change version

[2.3.0] - 2023-01-19

Added

Add int8 quantization support
Add large kernel support for implicit gemm (kv <= 128)

[2.2.6] - 2022-11-06

Fixed

CI fail because of pypi temporary shutdown. assign a new version and run again.

[2.2.5] - 2022-11-05

Fixed

Fix overflow when shape is too large

[2.2.4] - 2022-10-13

Added

Add prebuilt for CUDA 11.8 (RTX 4090 and H100) and CUDA 11.6.

Fixed

Fix small bugs

[2.2.3] - 2022-9-28

Fixed

Fix missing .contiguous for input feature
Add some debug msg if points vanished.

[2.2.2] - 2022-9-25

Fixed

Fix CI problem: main function too long and cause OOM in CI vm.

[2.2.1] - 2022-9-25

Fixed

Fix build problem
Fix nvrtc problem

[2.2.0] - 2022-9-24

Added

Add Ampere support. faster fp16, faster tf32 and greatly faster int8 kernels in Ampere GPUs.
Add pure c++ code generation (libspconv.so) for deploy (or train in another deeplearning framework)
Add NVRTC support for all gemm kernels. if your GPU architecture isn't compiled in prebuilt, spconv will use slightly slower (10-20us overhead for every kernel launch) NVRTC kernels.

Fixed

Fix launch fail in maxpool if too much voxels

Changed

all weight layout will be KRSC, don't support old spconv 1.x weights anymore.
previous gemm ops in ops.py now move to c++ by default (controlled by spconv.constants.SPCONV_CPP_GEMM)

Removed

drop python 3.6 support.
pascal and kepler architecture is removed in CUDA 12 prebuilt.

[2.1.22] - 2022-6-11

Fixed

Fix thrust problem by adding -fvisibility=hidden

[2.1.22] - 2022-4-14

Added

add full nvrtc support
add support for large spatial shape and batch size. if detect large shape, we use int64 instead of int32 when hashing.

[2.1.21] - 2021-12-9

Added

add sm_37
add fp16 kernels witl fp32 accumulator (run slower, but can avoid nan if channel size is too large)
add SPCONV_BWD_SPLITK env to control splitk candidates.

[2.1.20] - 2021-12-6

Added

Add fp16 conv simt kernels for mixed-training in pascal or older GPUS. WARNING: not optimized for TESLA P100 which has 2x throughput in half.

[2.1.19] - 2021-12-3

Fixed

Fix wrong arch assert in all kernels for old GPUs to make spconv work in sm_50 GPUs

[2.1.18] - 2021-11-29

Fixed

Fix a small bug of spatial_shape.
Fix a bug in PointToVoxel, we must always return a clone instead of a view.

[2.1.17] - 2021-11-29

Fixed

Fix a bug in sparse add.
Fix a serious bug in conv weight init.

Added

Add more wrong usage check
Add insert_exist_keys for hash table

[2.1.16] - 2021-11-28

Fixed

Fix strange compile problem in windows

[2.1.15] - 2021-11-28

Fixed

Fix missing pccm.Class in setup.py

[2.1.14] - 2021-11-28

Added

Add hash table
update cumm version
Add AddTableMisaligned for sptensors with same shape but different indices.

Fixed

Fix a bug already fixed in 2.1.10 but introduced in 2.1.12 again.

[2.1.13] - 2021-?-?

Added

Add some ops from spconv 1.x, see spconv.utils for more details.
Add some debug tool for users to attach more info in issue.

[2.1.12] - 2021-11-23

Added

Add a method for voxel generator to get pc_voxel_id, which is usually used in semantic segmentation

Fixed

Fix a bug in cuda voxel generater when max_voxels is smaller than real number of voxels

[2.1.11] - 2021-11-22

Fixed

Fixed a bug Volta kernels (TITAN V, Tesla V100), backward weight kernels use f16 as accumulator. we should use f32.
Fixed a corner case when user use kernel size = 1x1 but stride != 1.
Fixed a corner case when input feature is non-contiguous when maxpool.

[2.1.10] - 2021-11-19

Fixed

Fixed a bug in utils.PointToVoxel, shouldn't get cuda stream in cpu code

[2.1.9] - 2021-11-18

Removed

Remove a wrong assert

[2.1.8] - 2021-11-15

Added

Add support for pytorch 1.5

[2.1.7] - 2021-11-11

Fixed

Fix a bug when net have inverse and run inference in eval mode.

[2.1.6] - 2021-11-10

Fixed

Fix missing -fopenmp in linker for CPU only

Removed

remove stale comment sending in CI

[2.1.5] - 2021-11-10

Added

Add cuda profile tool
Add python 36 support

Changed

Format all code

Removed

remove a unnecessary device sync and slightly improve performance.

[2.1.4] - 2021-11-10

Fixed

Fix a bug of SparseInverseConv3d

[2.1.3] - 2021-11-08

Fixed

Fix a bug of CPU only package

[2.1.2] - 2021-11-06

Fixed

Fix a bug of python 3.7

[2.1.0] - 2021-10-31

Added

add implicit gemm algorithm for all kind of convolution with kernel volume <= 32. this algorithm is very fast with float16.
add pytorch wrapper for voxel generator
add CPU support and CPU-only build.

[2.0.2] - 2021-10-26

Fixed

Fix a serious bug that do nothing with non-spconv layers in SparseSequential
Fix a bug of ProxyableClassMeta

[2.0.0] - 2021-10-16

Changed

Change build system from cmake to pccm.
Change pytorch python code to spconv.pytorch
Rewrite All c++ code.

[1.2.1] - 2020-06-04

Changed

The subm indice pair generation speed is greatly increased by two tricks: 1. most subm conv use only kernelsize=3, so we can unroll loops to get 100% performance increase. 2. subm indice pairs have a property: indicePairs[0, i] = indicePairs[1, kernelVolume - i - 1], so we can get another 100% performance increase.

[1.2.0] - 2020-05-28

Added

add batch gemm support. small performance increasement but more gpu memory usage. you can use algo=spconv.ConvAlgo.Batch to use it.

Changed

replace most of 'functor' with c++14 dispatch in c++ code.

Fixed

change gather/scatterAdd kernel parameter to support large points.