#include <alpaqa/problem/type-erased-problem.hpp>
Detailed Description
class alpaqa::TypeErasedProblem< Conf, Allocator >
The main polymorphic minimization problem interface.
This class wraps the actual problem implementation class, filling in the missing member functions with sensible defaults, and providing a uniform interface that is used by the solvers.
The problem implementations do not inherit from an abstract base class. Instead, structural typing is used. The ProblemVTable constructor uses reflection to discover which member functions are provided by the problem implementation. See Problem formulations for more information, and C++/CustomCppProblem/main.cpp for an example.
Definition at line 216 of file type-erased-problem.hpp.
Inheritance diagram for TypeErasedProblem< Conf, Allocator >: Collaboration diagram for TypeErasedProblem< Conf, Allocator >:Problem dimensions | |
| length_t | get_n () const |
| [Required] Number of decision variables. | |
| length_t | get_m () const |
| [Required] Number of constraints. | |
Required cost and constraint functions | |
| real_t | eval_f (crvec x) const |
| [Required] Function that evaluates the cost, \( f(x) \) | |
| void | eval_grad_f (crvec x, rvec grad_fx) const |
| [Required] Function that evaluates the gradient of the cost, \( \nabla f(x) \) | |
| void | eval_g (crvec x, rvec gx) const |
| [Required] Function that evaluates the constraints, \( g(x) \) | |
| void | eval_grad_g_prod (crvec x, crvec y, rvec grad_gxy) const |
| [Required] Function that evaluates the gradient of the constraints times a vector, \( \nabla g(x)\,y = \tp{\jac_g(x)}y \) | |
Projections onto constraint sets and proximal mappings | |
| void | eval_proj_diff_g (crvec z, rvec e) const |
| [Required] Function that evaluates the difference between the given point \( z \) and its projection onto the constraint set \( D \). | |
| void | eval_proj_multipliers (rvec y, real_t M) const |
| [Required] Function that projects the Lagrange multipliers for ALM. | |
| real_t | eval_prox_grad_step (real_t γ, crvec x, crvec grad_ψ, rvec x̂, rvec p) const |
| [Required] Function that computes a proximal gradient step. | |
| index_t | eval_inactive_indices_res_lna (real_t γ, crvec x, crvec grad_ψ, rindexvec J) const |
| [Optional] Function that computes the inactive indices \( \mathcal J(x) \) for the evaluation of the linear Newton approximation of the residual, as in [4]. | |
Constraint sets | |
| const Box & | get_box_C () const |
| [Optional] Get the rectangular constraint set of the decision variables, \( x \in C \). | |
| const Box & | get_box_D () const |
| [Optional] Get the rectangular constraint set of the general constraint function, \( g(x) \in D \). | |
Functions for second-order solvers | |
| void | eval_jac_g (crvec x, rvec J_values) const |
| [Optional] Function that evaluates the nonzero values of the Jacobian matrix of the constraints, \( \jac_g(x) \) | |
| Sparsity | get_jac_g_sparsity () const |
| [Optional] Function that returns (a view of) the sparsity pattern of the Jacobian of the constraints. | |
| void | eval_grad_gi (crvec x, index_t i, rvec grad_gi) const |
| [Optional] Function that evaluates the gradient of one specific constraint, \( \nabla g_i(x) \) | |
| void | eval_hess_L_prod (crvec x, crvec y, real_t scale, crvec v, rvec Hv) const |
| [Optional] Function that evaluates the Hessian of the Lagrangian multiplied by a vector, \( \nabla_{xx}^2L(x, y)\,v \) | |
| void | eval_hess_L (crvec x, crvec y, real_t scale, rvec H_values) const |
| [Optional] Function that evaluates the nonzero values of the Hessian of the Lagrangian, \( \nabla_{xx}^2L(x, y) \) | |
| Sparsity | get_hess_L_sparsity () const |
| [Optional] Function that returns (a view of) the sparsity pattern of the Hessian of the Lagrangian. | |
| void | eval_hess_ψ_prod (crvec x, crvec y, crvec Σ, real_t scale, crvec v, rvec Hv) const |
| [Optional] Function that evaluates the Hessian of the augmented Lagrangian multiplied by a vector, \( \nabla_{xx}^2L_\Sigma(x, y)\,v \) | |
| void | eval_hess_ψ (crvec x, crvec y, crvec Σ, real_t scale, rvec H_values) const |
| [Optional] Function that evaluates the nonzero values of the Hessian of the augmented Lagrangian, \( \nabla_{xx}^2L_\Sigma(x, y) \) | |
| Sparsity | get_hess_ψ_sparsity () const |
| [Optional] Function that returns (a view of) the sparsity pattern of the Hessian of the augmented Lagrangian. | |
Combined evaluations | |
| real_t | eval_f_grad_f (crvec x, rvec grad_fx) const |
| [Optional] Evaluate both \( f(x) \) and its gradient, \( \nabla f(x) \). | |
| real_t | eval_f_g (crvec x, rvec g) const |
| [Optional] Evaluate both \( f(x) \) and \( g(x) \). | |
| void | eval_grad_f_grad_g_prod (crvec x, crvec y, rvec grad_f, rvec grad_gxy) const |
| [Optional] Evaluate both \( \nabla f(x) \) and \( \nabla g(x)\,y \). | |
| void | eval_grad_L (crvec x, crvec y, rvec grad_L, rvec work_n) const |
| [Optional] Evaluate the gradient of the Lagrangian \( \nabla_x L(x, y) = \nabla f(x) + \nabla g(x)\,y \) | |
Augmented Lagrangian | |
| real_t | eval_ψ (crvec x, crvec y, crvec Σ, rvec ŷ) const |
| [Optional] Calculate both ψ(x) and the vector ŷ that can later be used to compute ∇ψ. | |
| void | eval_grad_ψ (crvec x, crvec y, crvec Σ, rvec grad_ψ, rvec work_n, rvec work_m) const |
| [Optional] Calculate the gradient ∇ψ(x). | |
| real_t | eval_ψ_grad_ψ (crvec x, crvec y, crvec Σ, rvec grad_ψ, rvec work_n, rvec work_m) const |
| [Optional] Calculate both ψ(x) and its gradient ∇ψ(x). | |
Checks | |
| void | check () const |
| [Optional] Check that the problem formulation is well-defined, the dimensions match, etc. | |
Querying specialized implementations | |
| bool | provides_eval_inactive_indices_res_lna () const |
| Returns true if the problem provides an implementation of eval_inactive_indices_res_lna. | |
| bool | provides_eval_jac_g () const |
| Returns true if the problem provides an implementation of eval_jac_g. | |
| bool | provides_get_jac_g_sparsity () const |
| Returns true if the problem provides an implementation of get_jac_g_sparsity. | |
| bool | provides_eval_grad_gi () const |
| Returns true if the problem provides an implementation of eval_grad_gi. | |
| bool | provides_eval_hess_L_prod () const |
| Returns true if the problem provides an implementation of eval_hess_L_prod. | |
| bool | provides_eval_hess_L () const |
| Returns true if the problem provides an implementation of eval_hess_L. | |
| bool | provides_get_hess_L_sparsity () const |
| Returns true if the problem provides an implementation of get_hess_L_sparsity. | |
| bool | provides_eval_hess_ψ_prod () const |
| Returns true if the problem provides an implementation of eval_hess_ψ_prod. | |
| bool | provides_eval_hess_ψ () const |
| Returns true if the problem provides an implementation of eval_hess_ψ. | |
| bool | provides_get_hess_ψ_sparsity () const |
| Returns true if the problem provides an implementation of get_hess_ψ_sparsity. | |
| bool | provides_eval_f_grad_f () const |
| Returns true if the problem provides a specialized implementation of eval_f_grad_f, false if it uses the default implementation. | |
| bool | provides_eval_f_g () const |
| Returns true if the problem provides a specialized implementation of eval_f_g, false if it uses the default implementation. | |
| bool | provides_eval_grad_f_grad_g_prod () const |
| Returns true if the problem provides a specialized implementation of eval_grad_f_grad_g_prod, false if it uses the default implementation. | |
| bool | provides_eval_grad_L () const |
| Returns true if the problem provides a specialized implementation of eval_grad_L, false if it uses the default implementation. | |
| bool | provides_eval_ψ () const |
| Returns true if the problem provides a specialized implementation of eval_ψ, false if it uses the default implementation. | |
| bool | provides_eval_grad_ψ () const |
| Returns true if the problem provides a specialized implementation of eval_grad_ψ, false if it uses the default implementation. | |
| bool | provides_eval_ψ_grad_ψ () const |
| Returns true if the problem provides a specialized implementation of eval_ψ_grad_ψ, false if it uses the default implementation. | |
| bool | provides_get_box_C () const |
| Returns true if the problem provides an implementation of get_box_C. | |
| bool | provides_get_box_D () const |
| Returns true if the problem provides an implementation of get_box_D. | |
| bool | provides_check () const |
| Returns true if the problem provides an implementation of check. | |
Helpers | |
| real_t | calc_ŷ_dᵀŷ (rvec g_ŷ, crvec y, crvec Σ) const |
| Given g(x), compute the intermediate results ŷ and dᵀŷ that can later be used to compute ψ(x) and ∇ψ(x). | |
Public Types | |
| using | Sparsity = alpaqa::Sparsity< config_t > |
| using | Box = alpaqa::Box< config_t > |
| using | VTable = ProblemVTable< config_t > |
| using | allocator_type = Allocator |
| using | TypeErased = util::TypeErased< VTable, allocator_type > |
Public Member Functions | |
| TypeErased () noexcept(noexcept(allocator_type()))=default | |
| Default constructor. | |
| template<class Alloc > | |
| TypeErased (std::allocator_arg_t, const Alloc &alloc) | |
| Default constructor (allocator aware). | |
| TypeErased (const TypeErased &other) | |
| Copy constructor. | |
| TypeErased (const TypeErased &other, allocator_type alloc) | |
| Copy constructor (allocator aware). | |
| TypeErased (TypeErased &&other) noexcept | |
| Move constructor. | |
| TypeErased (TypeErased &&other, const allocator_type &alloc) noexcept | |
| Move constructor (allocator aware). | |
| template<class T , class Alloc > | |
| TypeErased (std::allocator_arg_t, const Alloc &alloc, T &&d) | |
| Main constructor that type-erases the given argument. | |
| template<class T , class Alloc , class... Args> | |
| TypeErased (std::allocator_arg_t, const Alloc &alloc, te_in_place_t< T >, Args &&...args) | |
| Main constructor that type-erases the object constructed from the given argument. | |
| template<class T > requires no_child_of_ours<T> | |
| TypeErased (T &&d) | |
| template<class T , class... Args> | |
| TypeErased (te_in_place_t< T >, Args &&...args) | |
| Main constructor that type-erases the object constructed from the given argument. | |
| operator bool () const noexcept | |
| Check if this wrapper wraps an object. | |
| bool | owns_referenced_object () const noexcept |
| Check if this wrapper owns the storage of the wrapped object, or whether it simply stores a reference to an object that was allocated elsewhere. | |
| bool | referenced_object_is_const () const noexcept |
| Check if the wrapped object is const. | |
| allocator_type | get_allocator () const noexcept |
| Get a copy of the allocator. | |
| const std::type_info & | type () const noexcept |
| Query the contained type. | |
| template<class T > | |
| T & | as () & |
| Convert the type-erased object to the given type. | |
| template<class T > | |
| const T & | as () const & |
| Convert the type-erased object to the given type. | |
| template<class T > | |
| const T && | as () && |
| Convert the type-erased object to the given type. | |
| void * | get_pointer () const |
| Get a type-erased pointer to the wrapped object. | |
| const void * | get_const_pointer () const |
| Get a type-erased pointer to the wrapped object. | |
Static Public Member Functions | |
| template<class T , class... Args> | |
| static TypeErasedProblem | make (Args &&...args) |
| template<class Ret , class T , class Alloc , class... Args> requires std::is_base_of_v<TypeErased, Ret> | |
| static Ret | make (std::allocator_arg_t tag, const Alloc &alloc, Args &&...args) |
| Construct a type-erased wrapper of type Ret for an object of type T, initialized in-place with the given arguments. | |
Static Public Attributes | |
| static constexpr size_t | small_buffer_size = SmallBufferSize |
Protected Member Functions | |
| template<class Ret , class... FArgs, class... Args> | |
| decltype(auto) | call (Ret(*f)(const void *, FArgs...), Args &&...args) const |
Call the vtable function f with the given arguments args, implicitly passing the self pointer and vtable reference if necessary. | |
| template<class Ret , class... FArgs, class... Args> | |
| decltype(auto) | call (Ret(*f)(void *, FArgs...), Args &&...args) |
Call the vtable function f with the given arguments args, implicitly passing the self pointer and vtable reference if necessary. | |
| template<class Ret > | |
| decltype(auto) | call (Ret(*f)(const void *)) const |
Call the vtable function f with the given arguments args, implicitly passing the self pointer and vtable reference if necessary. | |
| template<class Ret > | |
| decltype(auto) | call (Ret(*f)(void *)) |
Call the vtable function f with the given arguments args, implicitly passing the self pointer and vtable reference if necessary. | |
| template<class Ret > | |
| decltype(auto) | call (Ret(*f)(const void *, const VTable &)) const |
Call the vtable function f with the given arguments args, implicitly passing the self pointer and vtable reference if necessary. | |
| template<class Ret > | |
| decltype(auto) | call (Ret(*f)(void *, const VTable &)) |
Call the vtable function f with the given arguments args, implicitly passing the self pointer and vtable reference if necessary. | |
| template<class T , class... Args> | |
| void | construct_inplace (Args &&...args) |
| Ensure storage and construct the type-erased object of type T in-place. | |
| template<class Ret > | |
| decltype(auto) | call (Ret(*f)(const void *, const VTable &)) const |
Call the vtable function f with the given arguments args, implicitly passing the self pointer and vtable reference if necessary. | |
| template<class Ret > | |
| decltype(auto) | call (Ret(*f)(void *, const VTable &)) |
Call the vtable function f with the given arguments args, implicitly passing the self pointer and vtable reference if necessary. | |
Static Protected Member Functions | |
| static bool | size_indicates_ownership (size_t size) |
| static bool | size_indicates_const (size_t size) |
Protected Attributes | |
| void * | self |
| Pointer to the stored object. | |
| VTable | vtable |
| size_t | size = invalid_size |
| Size required to store the object. | |
Static Protected Attributes | |
| static constexpr size_t | invalid_size |
| static constexpr size_t | mut_ref_size |
| static constexpr size_t | const_ref_size |
Private Types | |
| using | allocator_traits = std::allocator_traits< allocator_type > |
| using | buffer_type = std::array< std::byte, small_buffer_size > |
Private Member Functions | |
| Deallocator | allocate (size_t size) |
| Ensure that storage is available, either by using the small buffer if it is large enough, or by calling the allocator. | |
| void | deallocate () |
| Deallocate the memory without invoking the destructor. | |
| void | cleanup () |
| Destroy the type-erased object (if not empty), and deallocate the memory if necessary. | |
| template<bool CopyAllocator> | |
| void | do_copy_assign (const TypeErased &other) |
Private Attributes | |
| buffer_type | small_buffer |
| allocator_type | allocator |
Static Private Attributes | |
| template<class T > | |
| static constexpr auto | no_child_of_ours |
True if T is not a child class of TypeErased. | |
Member Typedef Documentation
◆ Sparsity
| using Sparsity = alpaqa::Sparsity<config_t> |
Definition at line 219 of file type-erased-problem.hpp.
◆ Box
| using Box = alpaqa::Box<config_t> |
Definition at line 220 of file type-erased-problem.hpp.
◆ VTable
| using VTable = ProblemVTable<config_t> |
Definition at line 221 of file type-erased-problem.hpp.
◆ allocator_type
Definition at line 222 of file type-erased-problem.hpp.
◆ TypeErased
Definition at line 223 of file type-erased-problem.hpp.
◆ allocator_traits
|
privateinherited |
Definition at line 199 of file type-erasure.hpp.
◆ buffer_type
|
privateinherited |
Definition at line 200 of file type-erasure.hpp.
Member Function Documentation
◆ make() [1/2]
|
inlinestatic |
Definition at line 233 of file type-erased-problem.hpp.
◆ get_n()
[Required] Number of decision variables.
Definition at line 697 of file type-erased-problem.hpp.
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[Required] Number of constraints.
Definition at line 701 of file type-erased-problem.hpp.
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[Required] Function that evaluates the cost, \( f(x) \)
- Parameters
-
[in] x Decision variable \( x \in \R^n \)
Definition at line 726 of file type-erased-problem.hpp.
Here is the caller graph for this function:◆ eval_grad_f()
[Required] Function that evaluates the gradient of the cost, \( \nabla f(x) \)
- Parameters
-
[in] x Decision variable \( x \in \R^n \) [out] grad_fx Gradient of cost function \( \nabla f(x) \in \R^n \)
Definition at line 730 of file type-erased-problem.hpp.
Here is the caller graph for this function:◆ eval_g()
[Required] Function that evaluates the constraints, \( g(x) \)
- Parameters
-
[in] x Decision variable \( x \in \R^n \) [out] gx Value of the constraints \( g(x) \in \R^m \)
Definition at line 734 of file type-erased-problem.hpp.
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[Required] Function that evaluates the gradient of the constraints times a vector, \( \nabla g(x)\,y = \tp{\jac_g(x)}y \)
- Parameters
-
[in] x Decision variable \( x \in \R^n \) [in] y Vector \( y \in \R^m \) to multiply the gradient by [out] grad_gxy Gradient of the constraints \( \nabla g(x)\,y \in \R^n \)
Definition at line 738 of file type-erased-problem.hpp.
◆ eval_proj_diff_g()
[Required] Function that evaluates the difference between the given point \( z \) and its projection onto the constraint set \( D \).
- Parameters
-
[in] z Slack variable, \( z \in \R^m \) [out] e The difference relative to its projection, \( e = z - \Pi_D(z) \in \R^m \)
- Note
zandecan refer to the same vector.
Definition at line 706 of file type-erased-problem.hpp.
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[Required] Function that projects the Lagrange multipliers for ALM.
- Parameters
-
[in,out] y Multipliers, \( y \leftarrow \Pi_Y(y) \in \R^m \) [in] M The radius/size of the set \( Y \). See ALMParams::max_multiplier.
Definition at line 710 of file type-erased-problem.hpp.
◆ eval_prox_grad_step()
[Required] Function that computes a proximal gradient step.
- Parameters
-
[in] γ Step size, \( \gamma \in \R_{>0} \) [in] x Decision variable \( x \in \R^n \) [in] grad_ψ Gradient of the subproblem cost, \( \nabla\psi(x) \in \R^n \) [out] x̂ Next proximal gradient iterate, \( \hat x = T_\gamma(x) = \prox_{\gamma h}(x - \gamma\nabla\psi(x)) \in \R^n \) [out] p The proximal gradient step, \( p = \hat x - x \in \R^n \)
- Returns
- The nonsmooth function evaluated at x̂, \( h(\hat x) \).
- Note
- The vector \( p \) is often used in stopping criteria, so its numerical accuracy is more important than that of \( \hat x \).
Definition at line 714 of file type-erased-problem.hpp.
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[Optional] Function that computes the inactive indices \( \mathcal J(x) \) for the evaluation of the linear Newton approximation of the residual, as in [4].
- Parameters
-
[in] γ Step size, \( \gamma \in \R_{>0} \) [in] x Decision variable \( x \in \R^n \) [in] grad_ψ Gradient of the subproblem cost, \( \nabla\psi(x) \in \R^n \) [out] J The indices of the components of \( x \) that are in the index set \( \mathcal J(x) \). In ascending order, at most n.
- Returns
- The number of inactive constraints, \( \# \mathcal J(x) \).
For example, in the case of box constraints, we have
\[ \mathcal J(x) \defeq \defset{i \in \N_{[0, n-1]}}{\underline x_i \lt x_i - \gamma\nabla_{\!x_i}\psi(x) \lt \overline x_i}. \]
Definition at line 719 of file type-erased-problem.hpp.
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[Optional] Get the rectangular constraint set of the decision variables, \( x \in C \).
Definition at line 818 of file type-erased-problem.hpp.
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[Optional] Get the rectangular constraint set of the general constraint function, \( g(x) \in D \).
Definition at line 822 of file type-erased-problem.hpp.
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[Optional] Function that evaluates the nonzero values of the Jacobian matrix of the constraints, \( \jac_g(x) \)
- Parameters
-
[in] x Decision variable \( x \in \R^n \) [out] J_values Nonzero values of the Jacobian \( \jac_g(x) \in \R^{m\times n} \)
Required for second-order solvers only.
Definition at line 746 of file type-erased-problem.hpp.
Here is the caller graph for this function:◆ get_jac_g_sparsity()
[Optional] Function that returns (a view of) the sparsity pattern of the Jacobian of the constraints.
Required for second-order solvers only.
Definition at line 750 of file type-erased-problem.hpp.
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[Optional] Function that evaluates the gradient of one specific constraint, \( \nabla g_i(x) \)
- Parameters
-
[in] x Decision variable \( x \in \R^n \) [in] i Which constraint \( 0 \le i \lt m \) [out] grad_gi Gradient of the constraint \( \nabla g_i(x) \in \R^n \)
Required for second-order solvers only.
Definition at line 742 of file type-erased-problem.hpp.
◆ eval_hess_L_prod()
[Optional] Function that evaluates the Hessian of the Lagrangian multiplied by a vector, \( \nabla_{xx}^2L(x, y)\,v \)
- Parameters
-
[in] x Decision variable \( x \in \R^n \) [in] y Lagrange multipliers \( y \in \R^m \) [in] scale Scale factor for the cost function. [in] v Vector to multiply by \( v \in \R^n \) [out] Hv Hessian-vector product \( \nabla_{xx}^2 L(x, y)\,v \in \R^{n} \)
Required for second-order solvers only.
Definition at line 754 of file type-erased-problem.hpp.
◆ eval_hess_L()
[Optional] Function that evaluates the nonzero values of the Hessian of the Lagrangian, \( \nabla_{xx}^2L(x, y) \)
- Parameters
-
[in] x Decision variable \( x \in \R^n \) [in] y Lagrange multipliers \( y \in \R^m \) [in] scale Scale factor for the cost function. [out] H_values Nonzero values of the Hessian \( \nabla_{xx}^2 L(x, y) \in \R^{n\times n} \).
Required for second-order solvers only.
Definition at line 759 of file type-erased-problem.hpp.
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[Optional] Function that returns (a view of) the sparsity pattern of the Hessian of the Lagrangian.
Required for second-order solvers only.
Definition at line 764 of file type-erased-problem.hpp.
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[Optional] Function that evaluates the Hessian of the augmented Lagrangian multiplied by a vector, \( \nabla_{xx}^2L_\Sigma(x, y)\,v \)
- Parameters
-
[in] x Decision variable \( x \in \R^n \) [in] y Lagrange multipliers \( y \in \R^m \) [in] Σ Penalty weights \( \Sigma \) [in] scale Scale factor for the cost function. [in] v Vector to multiply by \( v \in \R^n \) [out] Hv Hessian-vector product \( \nabla_{xx}^2 L_\Sigma(x, y)\,v \in \R^{n} \)
Required for second-order solvers only.
Definition at line 768 of file type-erased-problem.hpp.
Here is the caller graph for this function:◆ eval_hess_ψ()
[Optional] Function that evaluates the nonzero values of the Hessian of the augmented Lagrangian, \( \nabla_{xx}^2L_\Sigma(x, y) \)
- Parameters
-
[in] x Decision variable \( x \in \R^n \) [in] y Lagrange multipliers \( y \in \R^m \) [in] Σ Penalty weights \( \Sigma \) [in] scale Scale factor for the cost function. [out] H_values Nonzero values of the Hessian \( \nabla_{xx}^2 L_\Sigma(x, y) \in \R^{n\times n} \)
Required for second-order solvers only.
Definition at line 773 of file type-erased-problem.hpp.
Here is the caller graph for this function:◆ get_hess_ψ_sparsity()
[Optional] Function that returns (a view of) the sparsity pattern of the Hessian of the augmented Lagrangian.
Required for second-order solvers only.
Definition at line 778 of file type-erased-problem.hpp.
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[Optional] Evaluate both \( f(x) \) and its gradient, \( \nabla f(x) \).
- Default implementation:
- ProblemVTable::default_eval_f_grad_f
Definition at line 782 of file type-erased-problem.hpp.
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[Optional] Evaluate both \( f(x) \) and \( g(x) \).
- Default implementation:
- ProblemVTable::default_eval_f_g
Definition at line 786 of file type-erased-problem.hpp.
◆ eval_grad_f_grad_g_prod()
[Optional] Evaluate both \( \nabla f(x) \) and \( \nabla g(x)\,y \).
- Default implementation:
- ProblemVTable::default_eval_grad_f_grad_g_prod
Definition at line 790 of file type-erased-problem.hpp.
◆ eval_grad_L()
[Optional] Evaluate the gradient of the Lagrangian \( \nabla_x L(x, y) = \nabla f(x) + \nabla g(x)\,y \)
- Default implementation:
- ProblemVTable::default_eval_grad_L
Definition at line 795 of file type-erased-problem.hpp.
Here is the caller graph for this function:◆ eval_ψ()
[Optional] Calculate both ψ(x) and the vector ŷ that can later be used to compute ∇ψ.
\[ \psi(x) = f(x) + \tfrac{1}{2} \text{dist}_\Sigma^2\left(g(x) + \Sigma^{-1}y,\;D\right) \]
\[ \hat y = \Sigma\, \left(g(x) + \Sigma^{-1}y - \Pi_D\left(g(x) + \Sigma^{-1}y\right)\right) \]
- Default implementation:
- ProblemVTable::default_eval_ψ
- Parameters
-
[in] x Decision variable \( x \) [in] y Lagrange multipliers \( y \) [in] Σ Penalty weights \( \Sigma \) [out] ŷ \( \hat y \)
Definition at line 800 of file type-erased-problem.hpp.
Here is the caller graph for this function:◆ eval_grad_ψ()
[Optional] Calculate the gradient ∇ψ(x).
\[ \nabla \psi(x) = \nabla f(x) + \nabla g(x)\,\hat y(x) \]
- Default implementation:
- ProblemVTable::default_eval_grad_ψ
- Parameters
-
[in] x Decision variable \( x \) [in] y Lagrange multipliers \( y \) [in] Σ Penalty weights \( \Sigma \) [out] grad_ψ \( \nabla \psi(x) \) work_n Dimension \( n \) work_m Dimension \( m \)
Definition at line 804 of file type-erased-problem.hpp.
Here is the caller graph for this function:◆ eval_ψ_grad_ψ()
[Optional] Calculate both ψ(x) and its gradient ∇ψ(x).
\[ \psi(x) = f(x) + \tfrac{1}{2} \text{dist}_\Sigma^2\left(g(x) + \Sigma^{-1}y,\;D\right) \]
\[ \nabla \psi(x) = \nabla f(x) + \nabla g(x)\,\hat y(x) \]
- Default implementation:
- ProblemVTable::default_eval_ψ_grad_ψ
- Parameters
-
[in] x Decision variable \( x \) [in] y Lagrange multipliers \( y \) [in] Σ Penalty weights \( \Sigma \) [out] grad_ψ \( \nabla \psi(x) \) work_n Dimension \( n \) work_m Dimension \( m \)
Definition at line 809 of file type-erased-problem.hpp.
Here is the caller graph for this function:◆ check()
[Optional] Check that the problem formulation is well-defined, the dimensions match, etc.
Throws an exception if this is not the case.
Definition at line 826 of file type-erased-problem.hpp.
◆ provides_eval_inactive_indices_res_lna()
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inline |
Returns true if the problem provides an implementation of eval_inactive_indices_res_lna.
Definition at line 561 of file type-erased-problem.hpp.
Here is the caller graph for this function:◆ provides_eval_jac_g()
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inline |
Returns true if the problem provides an implementation of eval_jac_g.
Definition at line 566 of file type-erased-problem.hpp.
Here is the caller graph for this function:◆ provides_get_jac_g_sparsity()
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inline |
Returns true if the problem provides an implementation of get_jac_g_sparsity.
Definition at line 571 of file type-erased-problem.hpp.
Here is the caller graph for this function:◆ provides_eval_grad_gi()
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inline |
Returns true if the problem provides an implementation of eval_grad_gi.
Definition at line 576 of file type-erased-problem.hpp.
Here is the caller graph for this function:◆ provides_eval_hess_L_prod()
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inline |
Returns true if the problem provides an implementation of eval_hess_L_prod.
Definition at line 581 of file type-erased-problem.hpp.
Here is the caller graph for this function:◆ provides_eval_hess_L()
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inline |
Returns true if the problem provides an implementation of eval_hess_L.
Definition at line 586 of file type-erased-problem.hpp.
Here is the caller graph for this function:◆ provides_get_hess_L_sparsity()
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inline |
Returns true if the problem provides an implementation of get_hess_L_sparsity.
Definition at line 591 of file type-erased-problem.hpp.
Here is the caller graph for this function:◆ provides_eval_hess_ψ_prod()
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inline |
Returns true if the problem provides an implementation of eval_hess_ψ_prod.
Definition at line 596 of file type-erased-problem.hpp.
Here is the caller graph for this function:◆ provides_eval_hess_ψ()
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inline |
Returns true if the problem provides an implementation of eval_hess_ψ.
Definition at line 601 of file type-erased-problem.hpp.
Here is the caller graph for this function:◆ provides_get_hess_ψ_sparsity()
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inline |
Returns true if the problem provides an implementation of get_hess_ψ_sparsity.
Definition at line 606 of file type-erased-problem.hpp.
Here is the caller graph for this function:◆ provides_eval_f_grad_f()
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inline |
Returns true if the problem provides a specialized implementation of eval_f_grad_f, false if it uses the default implementation.
Definition at line 611 of file type-erased-problem.hpp.
Here is the caller graph for this function:◆ provides_eval_f_g()
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inline |
Returns true if the problem provides a specialized implementation of eval_f_g, false if it uses the default implementation.
Definition at line 616 of file type-erased-problem.hpp.
Here is the caller graph for this function:◆ provides_eval_grad_f_grad_g_prod()
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inline |
Returns true if the problem provides a specialized implementation of eval_grad_f_grad_g_prod, false if it uses the default implementation.
Definition at line 621 of file type-erased-problem.hpp.
Here is the caller graph for this function:◆ provides_eval_grad_L()
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inline |
Returns true if the problem provides a specialized implementation of eval_grad_L, false if it uses the default implementation.
Definition at line 626 of file type-erased-problem.hpp.
Here is the caller graph for this function:◆ provides_eval_ψ()
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inline |
Returns true if the problem provides a specialized implementation of eval_ψ, false if it uses the default implementation.
Definition at line 631 of file type-erased-problem.hpp.
Here is the caller graph for this function:◆ provides_eval_grad_ψ()
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inline |
Returns true if the problem provides a specialized implementation of eval_grad_ψ, false if it uses the default implementation.
Definition at line 634 of file type-erased-problem.hpp.
Here is the caller graph for this function:◆ provides_eval_ψ_grad_ψ()
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inline |
Returns true if the problem provides a specialized implementation of eval_ψ_grad_ψ, false if it uses the default implementation.
Definition at line 639 of file type-erased-problem.hpp.
Here is the caller graph for this function:◆ provides_get_box_C()
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inline |
Returns true if the problem provides an implementation of get_box_C.
Definition at line 644 of file type-erased-problem.hpp.
Here is the caller graph for this function:◆ provides_get_box_D()
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inline |
Returns true if the problem provides an implementation of get_box_D.
Definition at line 649 of file type-erased-problem.hpp.
Here is the caller graph for this function:◆ provides_check()
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inline |
Returns true if the problem provides an implementation of check.
Definition at line 653 of file type-erased-problem.hpp.
Here is the caller graph for this function:◆ calc_ŷ_dᵀŷ()
Given g(x), compute the intermediate results ŷ and dᵀŷ that can later be used to compute ψ(x) and ∇ψ(x).
Computes the result using the following algorithm:
\[ \begin{aligned} \zeta &= g(x) + \Sigma^{-1} y \\[] d &= \zeta - \Pi_D(\zeta) = \operatorname{eval\_proj\_diff\_g}(\zeta, \zeta) \\[] \hat y &= \Sigma d \\[] \end{aligned} \]
- See also
- page_math
- Parameters
-
[in,out] g_ŷ Input \( g(x) \), outputs \( \hat y \) [in] y Lagrange multipliers \( y \) [in] Σ Penalty weights \( \Sigma \)
- Returns
- The inner product \( d^\top \hat y \)
Definition at line 814 of file type-erased-problem.hpp.
◆ TypeErased() [1/10]
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defaultnoexcept |
Default constructor.
◆ TypeErased() [2/10]
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inline |
Default constructor (allocator aware).
Definition at line 235 of file type-erasure.hpp.
◆ TypeErased() [3/10]
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inline |
Copy constructor.
Definition at line 237 of file type-erasure.hpp.
◆ TypeErased() [4/10]
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inline |
Copy constructor (allocator aware).
Definition at line 243 of file type-erasure.hpp.
◆ TypeErased() [5/10]
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inlinenoexcept |
Move constructor.
Definition at line 259 of file type-erasure.hpp.
◆ TypeErased() [6/10]
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inlinenoexcept |
Move constructor (allocator aware).
Definition at line 278 of file type-erasure.hpp.
◆ TypeErased() [7/10]
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inlineexplicit |
Main constructor that type-erases the given argument.
Definition at line 373 of file type-erasure.hpp.
◆ TypeErased() [8/10]
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inlineexplicit |
Main constructor that type-erases the object constructed from the given argument.
Definition at line 380 of file type-erasure.hpp.
◆ TypeErased() [9/10]
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inlineexplicit |
Requirement prevents this constructor from taking precedence over the copy and move constructors.
Definition at line 390 of file type-erasure.hpp.
◆ TypeErased() [10/10]
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inlineexplicit |
Main constructor that type-erases the object constructed from the given argument.
Definition at line 396 of file type-erasure.hpp.
◆ call() [1/8]
Call the vtable function f with the given arguments args, implicitly passing the self pointer and vtable reference if necessary.
Definition at line 586 of file type-erasure.hpp.
◆ call() [2/8]
Call the vtable function f with the given arguments args, implicitly passing the self pointer and vtable reference if necessary.
Definition at line 598 of file type-erasure.hpp.
◆ call() [3/8]
Call the vtable function f with the given arguments args, implicitly passing the self pointer and vtable reference if necessary.
Definition at line 612 of file type-erasure.hpp.
◆ call() [4/8]
Call the vtable function f with the given arguments args, implicitly passing the self pointer and vtable reference if necessary.
Definition at line 619 of file type-erasure.hpp.
◆ call() [5/8]
Call the vtable function f with the given arguments args, implicitly passing the self pointer and vtable reference if necessary.
Definition at line 628 of file type-erasure.hpp.
◆ call() [6/8]
Call the vtable function f with the given arguments args, implicitly passing the self pointer and vtable reference if necessary.
Definition at line 636 of file type-erasure.hpp.
◆ size_indicates_ownership()
◆ size_indicates_const()
◆ make() [2/2]
requires std::is_base_of_v<TypeErased, Ret>
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Construct a type-erased wrapper of type Ret for an object of type T, initialized in-place with the given arguments.
Definition at line 404 of file type-erasure.hpp.
◆ operator bool()
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inlineexplicitnoexceptinherited |
Check if this wrapper wraps an object.
False for default-constructed objects.
Definition at line 421 of file type-erasure.hpp.
◆ owns_referenced_object()
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inlinenoexceptinherited |
Check if this wrapper owns the storage of the wrapped object, or whether it simply stores a reference to an object that was allocated elsewhere.
Definition at line 426 of file type-erasure.hpp.
Here is the call graph for this function: Here is the caller graph for this function:◆ referenced_object_is_const()
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inlinenoexceptinherited |
Check if the wrapped object is const.
Definition at line 431 of file type-erasure.hpp.
Here is the call graph for this function: Here is the caller graph for this function:◆ get_allocator()
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inlinenoexceptinherited |
Get a copy of the allocator.
Definition at line 436 of file type-erasure.hpp.
◆ type()
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inlinenoexceptinherited |
Query the contained type.
Definition at line 439 of file type-erasure.hpp.
Here is the caller graph for this function:◆ as() [1/3]
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inlineinherited |
Convert the type-erased object to the given type.
The type is checked in debug builds only, use with caution.
Definition at line 446 of file type-erasure.hpp.
Here is the call graph for this function:◆ as() [2/3]
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inlineinherited |
Convert the type-erased object to the given type.
The type is checked in debug builds only, use with caution.
Definition at line 453 of file type-erasure.hpp.
Here is the call graph for this function:◆ as() [3/3]
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inlineinherited |
Convert the type-erased object to the given type.
The type is checked in debug builds only, use with caution.
Definition at line 460 of file type-erasure.hpp.
Here is the call graph for this function:◆ get_pointer()
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inlineinherited |
Get a type-erased pointer to the wrapped object.
- Exceptions
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alpaqa::util::bad_type_erased_constness If the wrapped object is const.
- See also
- get_const_pointer()
Definition at line 470 of file type-erasure.hpp.
Here is the call graph for this function:◆ get_const_pointer()
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inlineinherited |
Get a type-erased pointer to the wrapped object.
Definition at line 476 of file type-erasure.hpp.
◆ allocate()
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inlineprivateinherited |
Ensure that storage is available, either by using the small buffer if it is large enough, or by calling the allocator.
Returns a RAII wrapper that deallocates the storage unless released.
Definition at line 502 of file type-erasure.hpp.
Here is the call graph for this function: Here is the caller graph for this function:◆ deallocate()
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inlineprivateinherited |
Deallocate the memory without invoking the destructor.
Definition at line 514 of file type-erasure.hpp.
Here is the call graph for this function: Here is the caller graph for this function:◆ cleanup()
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inlineprivateinherited |
Destroy the type-erased object (if not empty), and deallocate the memory if necessary.
Definition at line 526 of file type-erasure.hpp.
Here is the call graph for this function: Here is the caller graph for this function:◆ do_copy_assign()
◆ construct_inplace()
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inlineprotectedinherited |
Ensure storage and construct the type-erased object of type T in-place.
Definition at line 562 of file type-erasure.hpp.
Here is the call graph for this function:◆ call() [7/8]
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inlineprotectedinherited |
Call the vtable function f with the given arguments args, implicitly passing the self pointer and vtable reference if necessary.
Definition at line 628 of file type-erasure.hpp.
◆ call() [8/8]
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inlineprotectedinherited |
Call the vtable function f with the given arguments args, implicitly passing the self pointer and vtable reference if necessary.
Definition at line 636 of file type-erasure.hpp.
Here is the call graph for this function:Member Data Documentation
◆ self
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protected |
Pointer to the stored object.
Definition at line 225 of file type-erasure.hpp.
◆ vtable
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protected |
Definition at line 228 of file type-erasure.hpp.
◆ small_buffer_size
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staticconstexprinherited |
Definition at line 195 of file type-erasure.hpp.
◆ small_buffer
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privateinherited |
Definition at line 201 of file type-erasure.hpp.
◆ allocator
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privateinherited |
Definition at line 202 of file type-erasure.hpp.
◆ no_child_of_ours
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staticconstexprprivateinherited |
True if T is not a child class of TypeErased.
Definition at line 207 of file type-erasure.hpp.
◆ invalid_size
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staticconstexprprotectedinherited |
Definition at line 211 of file type-erasure.hpp.
◆ mut_ref_size
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staticconstexprprotectedinherited |
Definition at line 213 of file type-erasure.hpp.
◆ const_ref_size
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staticconstexprprotectedinherited |
Definition at line 215 of file type-erasure.hpp.
◆ size
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protectedinherited |
Size required to store the object.
Definition at line 227 of file type-erasure.hpp.
The documentation for this class was generated from the following file:
- src/alpaqa/include/alpaqa/problem/type-erased-problem.hpp
