pylops.ToCupy

class pylops.ToCupy(dims, dtype='float64', name='C')

Convert to CuPy.

Convert an input array to CuPy in forward mode, and convert back to NumPy in adjoint mode.

Parameters

dimslist or int

Number of samples for each dimension

dtypestr, optional

Type of elements in input array.

namestr, optional

Name of operator (to be used by pylops.utils.describe.describe)

Notes

The ToCupy operator is a special operator that does not perform any transformation on the input arrays other than converting them from NumPy to CuPy. This operator can be used when one is interested to create a chain of operators where only one (or some of them) act on CuPy arrays, whilst other operate on NumPy arrays.

Attributes

shapetuple

Operator shape

explicitbool

Operator contains a matrix that can be solved explicitly (True) or not (False)

Methods

__init__(dims[, dtype, name])
adjoint()
apply_columns(cols)	Apply subset of columns of operator
cond([uselobpcg])	Condition number of linear operator.
conj()	Complex conjugate operator
div(y[, niter, densesolver])	Solve the linear problem \(\mathbf{y}=\mathbf{A}\mathbf{x}\).
dot(x)	Matrix-matrix or matrix-vector multiplication.
eigs([neigs, symmetric, niter, uselobpcg])	Most significant eigenvalues of linear operator.
matmat(X)	Matrix-matrix multiplication.
matvec(x)	Matrix-vector multiplication.
reset_count()	Reset counters
rmatmat(X)	Matrix-matrix multiplication.
rmatvec(x)	Adjoint matrix-vector multiplication.
todense([backend])	Return dense matrix.
toimag([forw, adj])	Imag operator
toreal([forw, adj])	Real operator
tosparse()	Return sparse matrix.
trace([neval, method, backend])	Trace of linear operator.
transpose()