chainer.utils.to_coo¶
-
chainer.utils.
to_coo
(x, ldnz=None, requires_grad=False)[source]¶ Returns a single or a batch of matrices in COO format.
- Parameters
x (numpy.ndarray or cupy.ndarray) – Input dense matrix. The ndim of
x
must be two or three. If ndim is two, it is treated as a single matrix. If three, it is treated as batched matrices.ldnz (int) – Size of arrays for data, row index and column index to be created. The Actual size becomes max(nnz, ldnz) where nnz is number of non-zero elements in a input dense matrix.
requires_grad (bool) – If
True
, gradient of sparse matrix will be computed in back-propagation.
- Returns
A sparse matrix or batched sparse matrices in COO format of a given dense matrix or batched dense matrices.
- Return type
Example
Create a
CooMatrix
from an array with 2 non-zero elements and 4 zeros and access its attributes. No batch dimension is involved.>>> data = np.array([[0, 2, 0], [-1, 0, 0]], np.float32) >>> x = chainer.utils.to_coo(data) >>> x.data variable([ 2., -1.]) >>> x.row array([0, 1], dtype=int32) >>> x.col array([1, 0], dtype=int32) >>> x.shape (2, 3)