value_E =spspmm(index_St.cpu(), value_St.cpu(), index_B.cpu(), value_B.cpu(), kN, N, kN)index_E, value_E =spspmm(index_St, value_St, index_B, value_B, kN, N, kN)# return index_E.to(device), value_E.to(device)returnindex_E, value_E ...
Torch functions specific to sparse Tensors(与稀疏有关的torch函数) 支持稀疏张量的常规torch函数 cat()dstack()empty()empty_like()hstack()index_select()is_complex()is_floating_point()is_nonzero()is_same_size()is_signed()is_tensor()lobpcg()mm()native_norm()pca_lowrank()select()stack()svd...
get_device() hspmm() mm() mul() mul_() resizeAs_() size() spadd() spmm() sspaddmm() sspmm() sub() sub_() t_() toDense() transpose() transpose_() zero_() coalesce() is_coalesced() _indices() _values() _nnz()
How did you try to install PyTorch Geometric and its extensions (wheel, source): from torch_sparse import spspmm, spmm ModuleNotFoundError: No module named 'torch_sparse' I follow the solution of#542,I have successfully installed related packaegs using the follow command: pip install --ve...
tmp_adj = sp.coo_matrix((data, (row, col)), shape=(n_nodes, n_nodes)) 转换成tensor,具体流程同上,把稀疏矩阵中每个元素都转换成tensor即可。 2. 稀疏矩阵计算 该版本稀疏矩阵类支持稀疏矩阵和稀疏矩阵的乘积torch.sparse.mm(sparse, sparse/dense);(1.8.0支持,之前版本不支持) ...
get_device() hspmm() mm() mul() mul_() resizeAs_() size() spadd() spmm() sspaddmm() sspmm() sub() sub_() t_() toDense() transpose() transpose_() zero_() coalesce() is_coalesced() _indices() _values() _nnz()
RuntimeError: MKL error: SPARSE_STATUS_ALLOC_FAILED when calling `mkl_sparse_spmm( SPARSE_OPERATION_NON_TRANSPOSE, mkl_sparse_mat1.descriptor(), mkl_sparse_mat2.descriptor(), &result_desc)` 20161.82454 Note that doing the same multiplication withscipy.sparse.csc_arrayinstead, produces no error...
sparse_coo_tensor( edge_index, torch.ones(edge_index.shape[1]).float(), (input.shape[0], input.shape[0]), ).to(input.device) support = torch.mm(input, self.weight) output = torch.spmm(adj, support) if self.bias is not None: return output + self.bias else: return output ...
spadd() spmm() sspaddmm() sspmm() sub() sub_() t_() toDense() transpose() transpose_() zero_() coalesce() is_coalesced() _indices() _values() _nnz() 函数 torch.sparse.addmm(mat,mat1,mat2,beta=1,alpha=1) 这个函数和torch.addmm()在forward中做同样的事情, 除了它支持稀疏矩阵...
size(1)), p) sp_mm = Sparse() Snp = sp_mm(Snp, S_mat) Snp_1 = Snp.clone() Snp_2 = Snp.clone() # # blur for f in range(num_features+1): B_var1 = Variable(B_mat[f].cuda(), requires_grad = False) sp_mm1 = Sparse() Snp_1 = sp_mm1(Snp_1, B_var1) B_var2...