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| PlasticFlowRate (const OptionSet &options) |
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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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enum | Stage { SOLVING
, UPDATING
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static enum neml2::Model::Stage | stage = UPDATING |
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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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