Hi,

I want to calculate the jacobian matrix w.r.t. the parameters of a model. This is how I am doing it at the moment:

```
from functorch import jacrev, vmap, make_functional, grad
def _compute_centered_jacobian(model,samples):
func, parameters = make_functional(model)
def func_ampl(params):
return func(params, samples)
def func_phase(params):
return func(params, samples)[1]
jac_ampl = torch.autograd.functional.jacobian(func_ampl, parameters)
jac_phase = torch.autograd.functional.jacobian(func_phase parameters)
return jac_ampl, jac_phase
```

but I am getting the error `TypeError: func_ampl() takes 1 positional argument but 9 were given`

because there are 9 different weight matrices in the model. How can I resolve this problem?

Thanks a lot for your help in advance!