minimize(method=’trust-ncg’)

torchmin.trustregion._minimize_trust_ncg(fun, x0, **trust_region_options)[source]

Minimization of scalar function of one or more variables using the Newton conjugate gradient trust-region algorithm.

Parameters

  • fun (callable) – Scalar objective function to minimize.

  • x0 (Tensor) – Initialization point.

  • initial_trust_radius (float) – Initial trust-region radius.

  • max_trust_radius (float) – Maximum value of the trust-region radius. No steps that are longer than this value will be proposed.

  • eta (float) – Trust region related acceptance stringency for proposed steps.

  • gtol (float) – Gradient norm must be less than gtol before successful termination.

Returns

result – Result of the optimization routine.

Return type

OptimizeResult

Notes

This is algorithm (7.2) of Nocedal and Wright 2nd edition. Only the function that computes the Hessian-vector product is required. The Hessian itself is not required, and the Hessian does not need to be positive semidefinite.