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)) – A 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 >>> import mindspore.nn as nn >>> 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)