self.shape = shapedefforward(self, features, coors, batch_size):coors = coors.int()# unlike torch, this library only accept int coordinates.x = spconv.SparseConvTensor(features, coors, self.shape, batch_size)returnself.net(x)# .dense() Inverse Convolution Inverse sparse convolution means "...
I am not sure you have already solved it or not. As the version was updated, the path was changed. I solved this problem by changing spconv.SparseSequential -> SparseSequential & import module with proper path as shown in upper snippet. Thank you. 11 qiaozhijian mentioned this issue De...
Hi@traveller59, First, I'd like to thank you for your excellent work on spconv. I am currently conducting a sanity check for sparse tensors with a density of 1.0, where I expect the outputs of sparse and dense convolutions to be identical. However, I'm observing significant discrepancies...
稀疏卷积操作sparse convolution,可以表示为SC(m, n, f, s), 其中m是input feature planes的输入特征channel数;n是输出特征channel数;f是filter size;s是stride。 其中f可以是non-square filter。传统的filter size一般是3x3, 5x5 ...这里可以是1x7... SC的input-output变化:当input大小是l的时候,输出就是...
本文主要对spconv1.2.1中的稀疏卷积中的C++部分代码进行解读,将其中spconv模块中代码提取建立了一个Qt个工程配置下工程就可以对其进行调试了。 这里主要使用How does sparse convolution work?中的一个5x5的例子进行简单调试,方便了解。 torch::Tensor indices = torch::zeros({2,3},torch::kInt32).to(torch:...
net(x)# .dense()Inverse ConvolutionInverse sparse convolution means "inv" of sparse convolution. the output of inverse convolution contains same indices as input of sparse convolution.Inverse convolution usually used in semantic segmentation.class ExampleNet(nn.Module): def __init__(self, shape):...
spconv.SubMConv3d(64, 64, 3, indice_key="subm0"), nn.BatchNorm1d(64), nn.ReLU(), spconv.SparseConvTranspose3d(64, 64, 3, 2), nn.BatchNorm1d(64), nn.ReLU(), spconv.ToDense(), # convert spconv tensor to dense and convert it to NCHW format. nn.Conv3d(64, 64, 3), nn...
SparseConvTensoris features + coordicates. If you want to convert a network to dense 3d, just nn.BatchNorm1dtonn.BatchNorm3d SparseConv3dtoConv3d SubMConv3dtoConv3dand make sure stride=1, padding is set to value that produce same shape between input and output ...
(),spconv.SparseConvTranspose3d(64,64,3,2),nn.BatchNorm1d(64),nn.ReLU(),spconv.ToDense(),# convert spconv tensor to dense and convert it to NCHW format.nn.Conv3d(64,64,3),nn.BatchNorm1d(64),nn.ReLU(), )self.shape=shapedefforward(self,features,coors,batch_size):coors=coors....
(kernelVolume<=4096,"error");// [41, 1440, 1440]->41*1440*1440autooutputVolume=outSpatialShape[0];for(inti=1;i<outSpatialShape.size();++i){outputVolume*=outSpatialShape[i];}std::stringmsg="due to limits of cuda hash, the volume of dense space include batch size ";msg+="must ...