例子:: >>>crow_indices = [0,2,4]>>>col_indices = [0,1,0,1]>>>values = [1,2,3,4]>>>torch.sparse_csr_tensor(torch.tensor(crow_indices, dtype=torch.int64),...torch.tensor(col_indices, dtype=torch.int64),...torch.tensor(values), dtype=torch.double) tensor(crow_indices=tensor...
1importpaddlecrows=[0,1,2,3]cols=[1,2,0]values=[1.,2.,3.]csr=paddle.sparse.sparse_csr_tensor(crows,cols,values, [3,3])crows1=[0,1,2,3]cols1=[1,2,0]values1=[4.,5.,6.]csr2=paddle.sparse.sparse_csr_tensor(crows1,cols1,values1, [3,3])paddle.sparse.matmul(csr2,csr)...
🐛 Describe the bug In pytorch version 1.11.0 torch.mm method performs slower for sparse CSR matrices than in pytorch version 1.9.0. This issue can be reproduced by using the following code example on both pytorch versions: import torch i...
2. Compressed Sparse Row Format (CSR) 这种存储方式稍微复杂一些,它同样是使用3个数组来保存一个稀疏矩阵:row ptr、column indices和values。换个角度理解,我们可以认为CSR就是在COO的基础上,将row数组进行压缩,另外两个数组保持不变。在原来的COO中,相同行的元素会在row保存重复的行索引,所以我们在row中将重复的...
- Mini-Batch梯度下降首先将矩阵转换为COO格式，然后提取索引、值和形状，并将它们直接传递给SparseTensor...
最近在研究Pytorchgeometric中的SparseTensor对象,它是Pytorch_eometric内部用于存储稀疏矩阵的对象,它可以以三种不同的压缩存储方式来保存稀疏矩阵:COO、CSR、CSC。本文简单介绍一下这三种压缩存储方式。 这种存储方式最直接,它使用3个数组来存储一个稀疏矩阵。通过row和col数组指定元素的行索引和列索引,values中对应的值...
Scipy稀疏CSR矩阵到TensorFlow SparseTensor - Mini-Batch梯度下降首先将矩阵转换为COO格式，然后提取索引、...
🐛 Describe the bug It looks like the adjacency matrix cannot be multiplied by itself because it is a sparse tensor as opposed to when the edge weights aren't given and are given a one for all edges. Changing the tensor multiplication fun...
_apply_sparse_csr_linear_solve(const at::Tensor&, const at::Tensor&, bool, const at::Tensor&)’: /var/lib/jenkins/workspace/aten/src/ATen/native/sparse/cuda/SparseCsrTensorMath.cu:739:36: error: ‘T* at::Tensor::data() const [with T = int]’ is deprecated: Tensor.data<T>() ...
Tensors and Dynamic neural networks in Python with strong GPU acceleration - [BE] Do not use deprecated APIs in SparseCsrTensorMath.cu · pytorch/pytorch@a308ac3