srch

04.03.2017 · What is the current state of sparse tensors in PyTorch? That’s my question too (now on 21st Sept). Can anyone comment on the current state of sparse tensors in PyTorch? Thank you. 4 Likes. 11131 (崔雪) October 24, 2017, 8:14am #11. I would like to ...

S = torch.sparse_coo_tensor(indices = torch.tensor([[0,0,1,2],[2,3,0 ... Pytorch has the torch.sparse API for dealing with sparse matrices.

This package consists of a small extension library of optimized sparse matrix operations with autograd support. This package currently consists of the following ...

... sparse_tensor = torch.sparse_coo_tensor(i, v, [2, 4]). Now I want to convert a PyTorch sparse tensor into a PyTorch dense tensor.

Memory-Efficient Aggregations¶ · SparseTensor class (from the · torch-sparse package), which implements fast forward and backward passes for sparse-matrix ...

In PyTorch, the fill value of a sparse tensor cannot be specified explicitly and is assumed to be zero in general. However, there exists operations that may interpret the fill value differently. For instance, torch.sparse.softmax () computes the softmax with the assumption that the fill value is negative infinity.

A sparse tensor is a high-dimensional extension of a sparse matrix where non-zero elements are represented as a set of indices and associated ...

Pytorch implements an extension of sparse tensors with scalar values to sparse tensors with (contiguous) tensor values. Such tensors are called hybrid ...

Join the PyTorch developer community to contribute, learn, and get your questions answered. Developer Resources. Find resources and get questions answered. Forums. A place to discuss PyTorch code, issues, install, research. Models (Beta) ... torch.Tensor.is_sparse ...

torch.Tensor.to_sparse¶ Tensor. to_sparse (sparseDims) → Tensor ¶ Returns a sparse copy of the tensor. PyTorch supports sparse tensors in coordinate format. Parameters. sparseDims (int, optional) – the number of sparse dimensions to include in the new sparse tensor. Example:

torch.sparse_coo_tensor. Constructs a sparse tensor in COO (rdinate) format with specified values at the given indices. This function returns an uncoalesced tensor. indices ( array_like) – Initial data for the tensor. Can be a list, tuple, NumPy ndarray, scalar, and other types. Will be cast to a torch.LongTensor internally.

Our sparse tensor format permits uncoalesced sparse tensors, where there may be duplicate coordinates in the indices; in this case, the interpretation is that ...