The base class for all constitutive models.
A model maps some input to output. The forward operator (and its derivative) is defined in the method set_value. All concrete models must provide the implementation of the forward operator by overriding the set_value method.
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| | Model (const OptionSet &options) |
| | Construct a new Model object.
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| virtual std::vector< Diagnosis > | preflight () const |
| | Check for common problems.
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| virtual bool | is_nonlinear_system () const |
| | Whether this model defines one or more nonlinear equations to be solved.
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| virtual void | reinit (TorchShapeRef batch_shape, int deriv_order=0, const torch::Device &device=torch::kCPU, const torch::Dtype &dtype=NEML2_DTYPE) |
| | Allocate storage and setup views for all the variables of this model and recursively all of the sub-models.
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| virtual void | reinit (const BatchTensor &tensor, int deriv_order) |
| | Allocate storage and setup views for all the variables of this model and recursively all of the sub-models. See the other overload for detailed description.
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| bool | requires_grad () const |
| | Whether derivative has been requested for this model.
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| bool | requires_2nd_grad () const |
| | Whether 2nd derivative has been requested for this model.
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| TorchSize | batch_dim () const |
| | This model's batch dim.
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| TorchShapeRef | batch_sizes () const |
| | This model's batch shape.
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| const torch::TensorOptions & | options () const |
| | This model's tensor options.
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| const std::vector< Model * > & | registered_models () const |
| | The models that may be used during the evaluation of this model.
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| Model * | registered_model (const std::string &name) const |
| | Get a registered model by its name.
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| virtual const std::set< VariableName > | consumed_items () const override |
| | The variables that this model depends on.
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| virtual const std::set< VariableName > | provided_items () const override |
| | The variables that this model defines as part of its output.
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| virtual void | check_AD_limitation () const |
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| void | input_requires_grad_ (bool req=true) |
| | Set requires_grad for the input variables.
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| bool | using_AD_1st_derivative () const |
| | Whether this model is using AD to get 1st derivatives.
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| bool | using_AD_2nd_derivative () const |
| | Whether this model is using AD to get 2nd derivatives.
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| void | use_AD_derivatives (bool first=true, bool second=true) |
| | Tell this model to use AD to get derivatives.
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| virtual void | set_input (const LabeledVector &in) |
| | Set in to be the input of this model.
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| virtual LabeledVector | get_output () |
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| virtual LabeledMatrix | get_doutput_dinput () |
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| virtual LabeledTensor3D | get_d2output_dinput2 () |
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| virtual LabeledVector | value (const LabeledVector &in) |
| | Convenient shortcut to construct and return the model value.
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| virtual std::tuple< LabeledVector, LabeledMatrix > | value_and_dvalue (const LabeledVector &in) |
| | Convenient shortcut to construct and return the model value and its derivative.
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| virtual std::tuple< LabeledVector, LabeledMatrix, LabeledTensor3D > | value_and_dvalue_and_d2value (const LabeledVector &in) |
| | Convenient shortcut to construct and return the model's value, first and second derivative.
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| virtual void | value () |
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| virtual void | value_and_dvalue () |
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| virtual void | value_and_dvalue_and_d2value () |
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| | Data (const OptionSet &options) |
| | Construct a new Data object.
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| const std::vector< Data * > & | registered_data () const |
| | All the registered data objects.
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| | NEML2Object (const OptionSet &options) |
| | Construct a new NEML2Object object.
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| virtual | ~NEML2Object ()=default |
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| const OptionSet & | input_options () const |
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| const std::string & | name () const |
| | A readonly reference to the object's name.
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| const std::string & | type () const |
| | A readonly reference to the object's type.
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| const std::string & | path () const |
| | A readonly reference to the object's path.
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| const std::string & | doc () const |
| | A readonly reference to the object's docstring.
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| template<typename T = NEML2Object> |
| const T * | host () const |
| | Get a readonly pointer to the host.
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| template<typename T = NEML2Object> |
| T * | host () |
| | Get a writable pointer to the host.
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| | BufferStore (const OptionSet &options, NEML2Object *object) |
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| const Storage< std::string, TensorValueBase > & | named_buffers () const |
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| Storage< std::string, TensorValueBase > & | named_buffers () |
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| template<typename T , typename = typename std::enable_if_t<std::is_base_of_v<BatchTensorBase<T>, T>>> |
| T & | get_buffer (const std::string &name) |
| | }@
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| | ParameterStore (const OptionSet &options, NEML2Object *object) |
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| const Storage< std::string, TensorValueBase > & | named_parameters () const |
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| Storage< std::string, TensorValueBase > & | named_parameters () |
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| template<typename T , typename = typename std::enable_if_t<std::is_base_of_v<BatchTensorBase<T>, T>>> |
| T & | get_parameter (const std::string &name) |
| | }@
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| bool | has_nl_param () const |
| | Whether this parameter store has any nonlinear parameter.
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| const std::map< std::string, const VariableBase * > & | nl_params () const |
| | Get all nonlinear parameters.
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| const VariableBase * | nl_param (const std::string &) const |
| | Query the existence of a nonlinear parameter.
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| | VariableStore (const OptionSet &options, NEML2Object *object) |
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| LabeledAxis & | declare_axis (const std::string &name) |
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| virtual void | setup_layout () |
| | Setup the layouts of all the registered axes.
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| VariableBase * | input_view (const VariableName &) |
| | Get the view of an input variable.
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| VariableBase * | output_view (const VariableName &) |
| | Get the view of an output variable.
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| template<typename T = BatchTensor> |
| Variable< T > & | get_input_variable (const VariableName &name) |
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| template<typename T = BatchTensor> |
| const Variable< T > & | get_input_variable (const VariableName &name) const |
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| template<typename T = BatchTensor> |
| const Variable< T > & | get_output_variable (const VariableName &name) |
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| template<typename T = BatchTensor> |
| const Variable< T > & | get_output_variable (const VariableName &name) const |
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| LabeledAxis & | input_axis () |
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| const LabeledAxis & | input_axis () const |
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| LabeledAxis & | output_axis () |
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| const LabeledAxis & | output_axis () const |
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| Storage< VariableName, VariableBase > & | input_views () |
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| const Storage< VariableName, VariableBase > & | input_views () const |
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| Storage< VariableName, VariableBase > & | output_views () |
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| const Storage< VariableName, VariableBase > & | output_views () const |
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| LabeledVector & | input_storage () |
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| const LabeledVector & | input_storage () const |
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| LabeledVector & | output_storage () |
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| const LabeledVector & | output_storage () const |
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| LabeledMatrix & | derivative_storage () |
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| const LabeledMatrix & | derivative_storage () const |
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| LabeledTensor3D & | second_derivative_storage () |
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| const LabeledTensor3D & | second_derivative_storage () const |
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| | NonlinearSystem (const OptionSet &options) |
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| virtual void | init_scaling (const bool verbose=false) |
| | Compute algebraic Jacobian-based automatic scaling following https://cs.stanford.edu/people/paulliu/files/cs517-project.pdf.
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| BatchTensor | scale_residual (const BatchTensor &r) const |
| | Apply scaling to the residual.
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| BatchTensor | scale_Jacobian (const BatchTensor &J) const |
| | Apply scaling to the Jacobian.
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| BatchTensor | scale_direction (const BatchTensor &p) const |
| | Remove scaling from the search direction, i.e. \( J^{-1} r \).
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| virtual BatchTensor | solution () const |
| | Get the solution vector.
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| BatchTensor | residual (const BatchTensor &x) |
| | Convenient shortcut to set the current solution, assemble and return the system residual.
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| void | residual () |
| | Convenient shortcut to assemble and return the system residual.
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| BatchTensor | Jacobian (const BatchTensor &x) |
| | Convenient shortcut to set the current solution, assemble and return the system Jacobian.
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| void | Jacobian () |
| | Convenient shortcut to assemble and return the system Jacobian.
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| std::tuple< BatchTensor, BatchTensor > | residual_and_Jacobian (const BatchTensor &x) |
| | Convenient shortcut to set the current solution, assemble and return the system residual and Jacobian.
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| void | residual_and_Jacobian () |
| | Convenient shortcut to assemble and return the system residual and Jacobian.
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| const BatchTensor & | residual_view () const |
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| const BatchTensor & | Jacobian_view () const |
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| BatchTensor | residual_norm () const |
| | The residual norm.
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| virtual void | setup () override |
| | Setup this model.
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| virtual void | allocate_variables (int deriv_order, bool options_changed) |
| | Call VariableStore::allocate_variables recursively on all submodels.
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| virtual void | setup_input_views () override |
| | Call VariableStore::setup_input_views recursively on all submodels.
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| virtual void | setup_submodel_input_views () |
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| virtual void | setup_output_views () override |
| | Call VariableStore::setup_output_views recursively on all submodels.
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| virtual void | setup_submodel_output_views () |
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| virtual void | reinit_input_views () override |
| | Call VariableStore::reinit_input_views recursively on all submodels.
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| virtual void | reinit_output_views (bool out, bool dout_din=true, bool d2out_din2=true) override |
| | Call VariableStore::reinit_output_views recursively on all submodels.
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| virtual void | detach_and_zero (bool out, bool dout_din=true, bool d2out_din2=true) override |
| | Call VariableStore::detach_and_zero recursively on all submodels.
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| virtual void | set_solution (const BatchTensor &x) override |
| | Set x as the current solution of the nonlinear system.
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| virtual void | set_value (bool out, bool dout_din, bool d2out_din2)=0 |
| | The map between input -> output, and optionally its derivatives.
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| virtual void | cache (TorchShapeRef batch_shape) override |
| | Cache the variable's batch shape.
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| virtual void | cache (const torch::TensorOptions &options) |
| | Cache tensor options.
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| template<typename T , typename = typename std::enable_if_t<std::is_base_of_v<Model, T>>> |
| T & | register_model (const std::string &name, int extra_deriv_order=0, bool nonlinear=false, bool merge_input=true) |
| | Register a model that the current model may use during its evaluation.
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| virtual void | assemble (bool residual, bool Jacobian) override |
| | Compute the residual and Jacobian.
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| virtual void | allocate_variables (TorchShapeRef batch_shape, const torch::TensorOptions &options, bool in, bool out, bool dout_din, bool d2out_din2) |
| | Allocate variable storages given the batch shape and tensor options.
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| virtual void | cache (TorchShapeRef batch_shape) |
| | Cache the variable's batch shape.
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| template<typename T , typename = typename std::enable_if_t<std::is_base_of_v<Data, T>>> |
| T & | register_data (const std::string &name) |
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| virtual void | send_buffers_to (const torch::TensorOptions &options) |
| | Send all buffers to options.
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| template<typename T , typename = typename std::enable_if_t<std::is_base_of_v<BatchTensorBase<T>, T>>> |
| const T & | declare_buffer (const std::string &name, const T &rawval) |
| | Declare a buffer.
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| template<typename T , typename = typename std::enable_if_t<std::is_base_of_v<BatchTensorBase<T>, T>>> |
| const T & | declare_buffer (const std::string &name, const std::string &input_option_name) |
| | Declare a buffer.
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| virtual void | send_parameters_to (const torch::TensorOptions &options) |
| | Send parameters to options.
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| template<typename T , typename = typename std::enable_if_t<std::is_base_of_v<BatchTensorBase<T>, T>>> |
| const T & | declare_parameter (const std::string &name, const T &rawval) |
| | Declare a parameter.
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| template<typename T , typename = typename std::enable_if_t<std::is_base_of_v<BatchTensorBase<T>, T>>> |
| const T & | declare_parameter (const std::string &name, const std::string &input_option_name) |
| | Declare a parameter.
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| template<typename T , typename... S> |
| const Variable< T > & | declare_input_variable (S &&... name) |
| | Declare an input variable.
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| template<typename... S> |
| const Variable< BatchTensor > & | declare_input_variable (TorchSize sz, S &&... name) |
| | Declare an input variable (with unknown base shape at compile time)
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| template<typename T , typename... S> |
| const Variable< BatchTensor > & | declare_input_variable_list (TorchSize list_size, S &&... name) |
| | Declare an input variable that is a list of tensors of fixed size.
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| template<typename T , typename... S> |
| Variable< T > & | declare_output_variable (S &&... name) |
| | Declare an output variable.
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| template<typename... S> |
| Variable< BatchTensor > & | declare_output_variable (TorchSize sz, S &&... name) |
| | Declare an input variable (with unknown base shape at compile time)
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| template<typename T , typename... S> |
| Variable< BatchTensor > & | declare_output_variable_list (TorchSize list_size, S &&... name) |
| | Declare an output variable that is a list of tensors of fixed size.
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| template<typename T > |
| VariableName | declare_variable (LabeledAxis &axis, const VariableName &var) const |
| | Declare an item recursively on an axis.
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| VariableName | declare_variable (LabeledAxis &axis, const VariableName &var, TorchSize sz) const |
| | Declare an item (with known storage size) recursively on an axis.
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| VariableName | declare_subaxis (LabeledAxis &axis, const VariableName &subaxis) const |
| | Declare a subaxis recursively on an axis.
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Public Member Functions inherited from Data