tfp.substrates.numpy.math.hpsd_solve

Computes matrix^-1 rhs, where matrix is HPSD.

Main aliases

tfp.experimental.substrates.numpy.math.hpsd_solve

tfp.substrates.numpy.math.hpsd_solve(
    matrix, rhs, cholesky_matrix=None
)

Given matrix and rhs, computes matrix^-1 rhs, where matrix is a Hermitian positive semi-definite matrix.

Args
`matrix`	Floating-point `Tensor` of shape `[..., N, N]`. Represents a Hermitian positive semi-definite matrix.
`rhs`	Floating-point `Tensor` of shape `[..., N, K]`.
`cholesky_matrix`	(Optional) Floating-point `Tensor` of shape `[..., N, N]` that represents a Cholesky factor of `matrix`.

Returns
`hpsd_solve`	`Tensor` of shape `[..., N, K]`.

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Last updated 2023-11-21 UTC.

Args