b914816142ae2776f531be1c0b49812a0bfde91f,torchdiffeq/_impl/adams.py,VariableCoefficientAdamsBashforth,__init__,#VariableCoefficientAdamsBashforth#,74

Before Change

class VariableCoefficientAdamsBashforth(AdaptiveStepsizeODESolver):
    def __init__(self, func, y0, rtol, atol, first_step=None, max_order=_MAX_ORDER, safety=0.9,
                 ifactor=10.0, dfactor=0.2, dtype=torch.float64, **kwargs):
        super(VariableCoefficientAdamsBashforth, self).__init__(dtype=dtype, y0=y0, **kwargs)

        assert _MIN_ORDER <= max_order <= _MAX_ORDER, "max_order must lie between {} and {}".format(_MIN_ORDER,
                                                                                                    _MAX_ORDER)

After Change

        self.max_order = int(max(_MIN_ORDER, min(max_order, _MAX_ORDER)))
        self.safety = _convert_to_tensor(safety, dtype=torch.float64, device=y0[0].device)
        self.ifactor = _convert_to_tensor(ifactor, dtype=torch.float64, device=y0[0].device)
        self.dfactor = _convert_to_tensor(dfactor, dtype=torch.float64, device=y0[].device)

    def before_integrate(self, t):
        prev_f = collections.deque(maxlen=self.max_order + 1)

Instances