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class  Implicit

Description

Lower-level model optimization procedure

The implemented lower-level optimization procedure will optimize a wrapper of lower- level model for further using in the following upper level optimization.

Parameters

  • ll_objective: callable
    An optimization problem which is considered as the constraint of ll problem.

    Callable with signature callable(state). Defined based on modeling of the specific problem that need to be solved. Computing the loss of ll problem. The state object contains the following:

    • "data"(Tensor) - Data used in the ll optimization phase.
    • "target"(Tensor) - Target used in the ll optimization phase.
    • "ul_model"(Module) - UL model of the bi-level model structure.
    • "ll_model"(Module) - LL model of the bi-level model structure.

  • lower_loop: int
    Updating iterations over ll optimization.

  • ul_model: Module
    UL model in a hierarchical model structure whose parameters will be updated with ul objective.

  • ll_model: Module
    LL model in a hierarchical model structure whose parameters will be updated with ll objective during ll optimization.

Methods

optimize(train_data, train_target, auxiliary_model, auxiliary_opt)

Execute the ll optimization procedure with training data samples using ll objective. The passed in wrapper of ll model will be updated.

Parameters:

  • train_data(Tensor) - The training data used for ll problem optimization.

  • train_target(Tensor) - The labels of the samples in the train data.

  • auxiliary_model(_MonkeyPatchBase) - Wrapper of ll model encapsulated by module higher, will be optimized in ll optimization procedure.

  • auxiliary_opt(DifferentiableOptimizer) - Wrapper of ll optimizer encapsulated by module higher, will be used in ll optimization procedure.