mindspore.SparseTensor

class mindspore.SparseTensor(indices, values, shape)[source]

A sparse representation of a set of nonzero elements from a tensor at given indices.

SparseTensor can only be used in the Cell’s construct method.

For a tensor dense, its SparseTensor(indices, values, dense_shape) has dense[indices[i]] = values[i].

For example, if indices is [[0, 1], [1, 2]], values is [1, 2], dense_shape is (3, 4), then the dense representation of the sparse tensor will be:

[[0, 1, 0, 0],
 [0, 0, 2, 0],
 [0, 0, 0, 0]]

Note

The interface is deprecated from version 1.7 and will be removed in a future version. Please use ‘COOTensor’ instead.

Parameters

indices (Tensor) – A 2-D integer Tensor of shape \((N, ndims)\), where N and ndims are the number of values and number of dimensions in the SparseTensor, respectively.
values (Tensor) – A 1-D tensor of any type and shape \((N)\), which supplies the values for each element in indices.
shape (tuple(int)) – An integer tuple of size ndims, which specifies the shape of the sparse tensor.

Returns

SparseTensor, composed of indices, values, and shape.

Examples

>>> import mindspore as ms
>>> from mindspore import Tensor, SparseTensor
>>> indices = Tensor([[0, 1], [1, 2]])
>>> values = Tensor([1, 2], dtype=ms.float32)
>>> shape = (3, 4)
>>> x = SparseTensor(indices, values, shape)
>>> print(x.values)
[1. 2.]
>>> print(x.indices)
[[0 1]
 [1 2]]
>>> print(x.shape)
(3, 4)

property indices: Return SparseTensor’s indices.

property shape: Return SparseTensor’s shape.

property values: Return SparseTensor’s non-zero values.