v2.1.4: fix #370 fix a bug in SparseInverseConv

CHANGELOG.md

 # Changelog
 
+## [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
-### Addad
-* 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.
+### 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

README.md

@@ -26,6 +26,8 @@
 
 [Spconv 1.x code](https://github.com/traveller59/spconv/tree/v1.2.1). We won't provide any support for spconv 1.x since it's deprecated. use spconv 2.x if possible. <!--remove this message in spconv 2.2-->
 
+**WARNING** spconv < 2.1.4 users need to upgrade your version to 2.1.4, it fix a serious bug in SparseInverseConvXd.
+
 ## Breaking changes in Spconv 2.x
 
 Spconv 1.x users **NEED READ [THIS](docs/SPCONV_2_BREAKING_CHANGEs.md)** before using spconv 2.x.

spconv/pytorch/conv.py

@@ -266,7 +266,7 @@ class SparseConvolution(SparseModule):
                 outids = datas.indices
                 indice_pairs = datas.indice_pairs
                 indice_pair_num = datas.indice_pair_num
-                out_spatial_shape = datas.out_spatial_shape
+                out_spatial_shape = datas.spatial_shape
                 assert indice_pair_num.shape[0] == np.prod(
                     self.kernel_size
                 ), "inverse conv must have same kernel size as its couple conv"
@@ -295,6 +295,7 @@ class SparseConvolution(SparseModule):
                                              indice_pairs,
                                              indice_pair_num,
                                              spatial_shape,
+                                             out_spatial_shape,
                                              is_subm=self.subm,
                                              algo=algo)
                     if self.indice_key is not None:
@@ -338,7 +339,7 @@ class SparseConvolution(SparseModule):
                 mask_argsort_fwd_splits = datas.mask_argsort_bwd_splits
                 mask_argsort_bwd_splits = datas.mask_argsort_fwd_splits
                 masks = datas.masks
-
+                out_spatial_shape = datas.spatial_shape
             else:
                 if self.indice_key is not None and datas is not None:
                     outids = datas.out_indices
@@ -385,6 +386,7 @@ class SparseConvolution(SparseModule):
                             mask_argsort_bwd_splits=mask_argsort_bwd_splits,
                             masks=masks,
                             is_subm=self.subm,
+                            spatial_shape=spatial_shape,
                             out_spatial_shape=out_spatial_shape,
                             algo=algo)
                         msg = f"your indice key {self.indice_key} already exists in this sparse tensor."

spconv/pytorch/core.py

@@ -40,11 +40,12 @@ else:
 
 class IndiceData(object):
     def __init__(self, out_indices, indices, indice_pairs, indice_pair_num,
-                 out_spatial_shape, is_subm: bool, algo: ConvAlgo):
+                 spatial_shape, out_spatial_shape, is_subm: bool, algo: ConvAlgo):
         self.out_indices = out_indices
         self.indices = indices
         self.indice_pairs = indice_pairs
         self.indice_pair_num = indice_pair_num
+        self.spatial_shape = spatial_shape
         self.out_spatial_shape = out_spatial_shape
         self.is_subm = is_subm
         self.algo = algo
@@ -57,7 +58,8 @@ class ImplicitGemmIndiceData(object):
                  pair_mask_bwd_splits: List[torch.Tensor],
                  mask_argsort_fwd_splits: List[torch.Tensor],
                  mask_argsort_bwd_splits: List[torch.Tensor],
-                 masks: List[np.ndarray], out_spatial_shape, is_subm: bool, algo: ConvAlgo):
+                 masks: List[np.ndarray], spatial_shape, 
+                 out_spatial_shape, is_subm: bool, algo: ConvAlgo):
         self.out_indices = out_indices
         self.indices = indices
         self.pair_fwd = pair_fwd
@@ -67,6 +69,7 @@ class ImplicitGemmIndiceData(object):
         self.mask_argsort_fwd_splits = mask_argsort_fwd_splits
         self.mask_argsort_bwd_splits = mask_argsort_bwd_splits
         self.masks = masks
+        self.spatial_shape = spatial_shape
         self.out_spatial_shape = out_spatial_shape
         self.is_subm = is_subm
         self.algo = algo

spconv/pytorch/pool.py

@@ -148,6 +148,7 @@ class SparseMaxPool(SparseModule):
                                              indice_pairs,
                                              indice_pairs_num,
                                              spatial_shape,
+                                             out_spatial_shape,
                                              is_subm=False,
                                              algo=self.algo)
                     indice_dict[self.indice_key] = indice_data
@@ -192,6 +193,7 @@ class SparseMaxPool(SparseModule):
                     mask_argsort_bwd_splits=mask_argsort_bwd_splits,
                     masks=masks,
                     is_subm=self.subm,
+                    spatial_shape=spatial_shape,
                     out_spatial_shape=out_spatial_shape,
                     algo=self.algo)
                 msg = f"your indice key {self.indice_key} already exists in this sparse tensor."

version.txt

-2.1.3
\ No newline at end of file
+2.1.4
\ No newline at end of file