Secure your code as it's written. Use Snyk Code to scan source code in minutes - no build needed - and fix issues immediately.
def __init__(
self, func, y0, rtol, atol, first_step=None, safety=0.9, ifactor=10.0, dfactor=0.2, max_num_steps=2**31 - 1,
**unused_kwargs
):
_handle_unused_kwargs(self, unused_kwargs)
del unused_kwargs
self.func = func
self.y0 = y0
self.rtol = rtol if _is_iterable(rtol) else [rtol] * len(y0)
self.atol = atol if _is_iterable(atol) else [atol] * len(y0)
self.first_step = first_step
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[0].device)
self.max_num_steps = _convert_to_tensor(max_num_steps, dtype=torch.int32, device=y0[0].device)
#self.n_step_record=[]
def __init__(
self, func, y0, rtol, atol, first_step=None, safety=0.9, ifactor=10.0, dfactor=0.2, max_num_steps=2**31 - 1,
**unused_kwargs
):
_handle_unused_kwargs(self, unused_kwargs)
del unused_kwargs
self.func = func
self.y0 = y0
self.rtol = rtol if _is_iterable(rtol) else [rtol] * len(y0)
self.atol = atol if _is_iterable(atol) else [atol] * len(y0)
self.first_step = first_step
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[0].device)
self.max_num_steps = _convert_to_tensor(max_num_steps, dtype=torch.int32, device=y0[0].device)
def __init__(
self, func, y0, rtol, atol, first_step=None, safety=0.9, ifactor=10.0, dfactor=0.2, max_num_steps=2**31 - 1,
**unused_kwargs
):
_handle_unused_kwargs(self, unused_kwargs)
del unused_kwargs
self.func = func
self.y0 = y0
self.rtol = rtol if _is_iterable(rtol) else [rtol] * len(y0)
self.atol = atol if _is_iterable(atol) else [atol] * len(y0)
self.first_step = first_step
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[0].device)
self.max_num_steps = _convert_to_tensor(max_num_steps, dtype=torch.int32, device=y0[0].device)
#self.n_step_record=[]
def __init__(
self, func, y0, rtol, atol, first_step=None, safety=0.9, ifactor=10.0, dfactor=0.2, max_num_steps=2**31 - 1,
**unused_kwargs
):
_handle_unused_kwargs(self, unused_kwargs)
del unused_kwargs
self.func = func
self.y0 = y0
self.rtol = rtol if _is_iterable(rtol) else [rtol] * len(y0)
self.atol = atol if _is_iterable(atol) else [atol] * len(y0)
self.first_step = first_step
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[0].device)
self.max_num_steps = _convert_to_tensor(max_num_steps, dtype=torch.int32, device=y0[0].device)