Internal class - adapts the OptimizationProblem class to HiOp's interface.
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#include <hiop.hpp>
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| | HiopOptimizationProblem (const OptimizationProblem &prob) |
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| | HiopOptimizationProblem (const MPI_Comm &comm_, const OptimizationProblem &prob) |
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| void | setStartingPoint (const Vector &x0) |
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| virtual bool | get_prob_sizes (long long int &n, long long int &m) |
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| virtual bool | get_starting_point (const long long &n, double *x0) |
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| virtual bool | get_vars_info (const long long &n, double *xlow, double *xupp, NonlinearityType *type) |
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| virtual bool | get_cons_info (const long long &m, double *clow, double *cupp, NonlinearityType *type) |
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| virtual bool | eval_f (const long long &n, const double *x, bool new_x, double &obj_value) |
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| virtual bool | eval_grad_f (const long long &n, const double *x, bool new_x, double *gradf) |
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| virtual bool | eval_cons (const long long &n, const long long &m, const long long &num_cons, const long long *idx_cons, const double *x, bool new_x, double *cons) |
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| virtual bool | eval_Jac_cons (const long long &n, const long long &m, const long long &num_cons, const long long *idx_cons, const double *x, bool new_x, double *Jac) |
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| virtual bool | get_vecdistrib_info (long long global_n, long long *cols) |
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| virtual bool | get_MPI_comm (MPI_Comm &comm_out) |
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Internal class - adapts the OptimizationProblem class to HiOp's interface.
Definition at line 32 of file hiop.hpp.
| mfem::HiopOptimizationProblem::HiopOptimizationProblem |
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const MPI_Comm & |
comm_, |
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const OptimizationProblem & |
prob |
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inline |
| bool mfem::HiopOptimizationProblem::eval_cons |
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const long long & |
n, |
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const long long & |
m, |
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const long long & |
num_cons, |
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const long long * |
idx_cons, |
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const double * |
x, |
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bool |
new_x, |
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double * |
cons |
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Evaluates a subset of the constraints cons(x). The subset is of size num_cons and is described by indexes in the idx_cons array, i.e. cons[c] = C(x)[idx_cons[c]] where c = 0 .. num_cons-1. The methods may be called multiple times, each time for a subset of the constraints, for example, for the subset containing the equalities and for the subset containing the inequalities. However, each constraint will be inquired EXACTLY once. This is done for performance considerations, to avoid temporary holders and memory copying.
Parameters:
- n, m: the global number of variables and constraints
- num_cons, idx_cons (array of size num_cons): the number and indexes of constraints to be evaluated
- x: the point where the constraints are to be evaluated
- new_x: whether x has been changed from the previous call to f, grad_f, or Jac
- cons: array of size num_cons containing the value of the constraints indicated by idx_cons
When MPI enabled, every rank populates cons, since the constraints are not distributed.
Definition at line 111 of file hiop.cpp.
| bool mfem::HiopOptimizationProblem::eval_f |
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const long long & |
n, |
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const double * |
x, |
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bool |
new_x, |
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double & |
obj_value |
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Objective function evaluation. Each rank returns the global objective value.
Definition at line 82 of file hiop.cpp.
| bool mfem::HiopOptimizationProblem::eval_grad_f |
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const long long & |
n, |
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const double * |
x, |
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bool |
new_x, |
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double * |
gradf |
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Gradient of the objective function (local chunk).
Definition at line 96 of file hiop.cpp.
| bool mfem::HiopOptimizationProblem::eval_Jac_cons |
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const long long & |
n, |
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const long long & |
m, |
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const long long & |
num_cons, |
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const long long * |
idx_cons, |
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const double * |
x, |
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bool |
new_x, |
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double * |
Jac |
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Evaluates the Jacobian of the subset of constraints indicated by idx_cons. The idx_cons is assumed to be of size num_cons. Example: if cons[c] = C(x)[idx_cons[c]] where c = 0 .. num_cons-1, then one needs to do Jac[c][j] = d cons[c] / dx_j, j = 1 .. n_loc. Jac is computed and stored in a contiguous vector (offset by rows).
Parameters: see eval_cons().
When MPI enabled, each rank computes only the local columns of the Jacobian, that is the partials with respect to local variables.
Definition at line 137 of file hiop.cpp.
| bool mfem::HiopOptimizationProblem::get_cons_info |
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const long long & |
m, |
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double * |
clow, |
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double * |
cupp, |
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NonlinearityType * |
type |
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bounds on the constraints (clow<=-1e20 means no lower bound, cupp>=1e20 means no upper bound)
Definition at line 58 of file hiop.cpp.
| virtual bool mfem::HiopOptimizationProblem::get_MPI_comm |
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MPI_Comm & |
comm_out | ) |
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inlinevirtual |
| bool mfem::HiopOptimizationProblem::get_prob_sizes |
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long long int & |
n, |
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long long int & |
m |
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Extraction of problem dimensions: n is the number of variables, m is the number of constraints.
Definition at line 25 of file hiop.cpp.
| bool mfem::HiopOptimizationProblem::get_starting_point |
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const long long & |
n, |
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double * |
x0 |
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Provide an primal starting point. This point is subject to adjustments internally in HiOp.
Definition at line 33 of file hiop.cpp.
| bool mfem::HiopOptimizationProblem::get_vars_info |
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const long long & |
n, |
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double * |
xlow, |
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double * |
xupp, |
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NonlinearityType * |
type |
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| bool mfem::HiopOptimizationProblem::get_vecdistrib_info |
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long long |
global_n, |
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long long * |
cols |
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Specifies column partitioning for distributed memory vectors. Process p owns vector entries with indices cols[p] to cols[p+1]-1, where p = 0 .. nranks-1. The cols array is of size nranks + 1. Example: for a vector x of 6 entries (globally) on 3 ranks, the uniform column partitioning is cols=[0,2,4,6].
Definition at line 168 of file hiop.cpp.
| void mfem::HiopOptimizationProblem::setStartingPoint |
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const Vector & |
x0 | ) |
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inline |
The documentation for this class was generated from the following files:
1.8.5
