mindspore.ops.SparseToDense

class mindspore.ops.SparseToDense[source]

Converts a sparse representation into a dense tensor.

Inputs:

  • indices (Tensor) - A 2-D Tensor, represents the position of the element in the sparse tensor. Support int32, int64, each element value should be a non-negative int number. The shape is \((n, 2)\).

  • values (Tensor) - A 1-D Tensor, represents the value corresponding to the position in the indices. The shape should be \((n,)\).

  • sparse_shape (tuple(int)) - A positive int tuple which specifies the shape of sparse tensor, should have 2 elements, represent sparse tensor shape is \((N, C)\).

Outputs:

Tensor, converted from sparse tensor. The dtype is same as values, and the shape is sparse_shape.

Raises

  • TypeError – If the dtype of indices is neither int32 nor int64.

  • ValueError – If sparse_shape, shape of indices and shape of values don’t meet the parameter description.

Supported Platforms:

CPU

Examples

>>> import mindspore
>>> from mindspore import Tensor, ops
>>> indices = Tensor([[0, 1], [1, 2]])
>>> values = Tensor([1, 2], dtype=mindspore.float32)
>>> sparse_shape = (3, 4)
>>> sparse_to_dense = ops.SparseToDense()
>>> out = sparse_to_dense(indices, values, sparse_shape)
>>> print(out)
[[0. 1. 0. 0.]
 [0. 0. 2. 0.]
 [0. 0. 0. 0.]]