integrate

bayesflow.utils.integrate(fn: Callable, state: dict[str, int | float | Tensor], start_time: int | float | Tensor | None = None, stop_time: int | float | Tensor | None = None, min_steps: int = 10, max_steps: int = 10000, steps: int | Literal['adaptive'] | Tensor | ndarray = 100, method: str = 'euler', **kwargs) → dict[str, int | float | Tensor]