pyepo.func.abcmodule¶

Abstract autograd optimization module

Attributes¶

`logger`
`Reduction`

Classes¶

optModule

An abstract module for differentiable optimization losses in end-to-end

Module Contents¶

pyepo.func.abcmodule.logger¶

pyepo.func.abcmodule.Reduction¶

class pyepo.func.abcmodule.optModule(optmodel: pyepo.model.opt.optModel, processes: int = 1, solve_ratio: float = 1.0, reduction: Reduction = 'mean', dataset: pyepo.data.dataset.optDataset | None = None, require_solpool: bool = False, seed: int | None = None)¶

Bases: torch.nn.Module

An abstract module for differentiable optimization losses in end-to-end predict-then-optimize. It provides common functionality (multiprocessing, solution pooling, loss reduction) for all loss modules.

optmodel¶

processes¶

solve_ratio = 1.0¶

solpool = None¶

reduction = 'mean'¶

abstractmethod forward(*args: torch.Tensor) → torch.Tensor¶: Forward pass