neural_tangents.taylor_expand
- neural_tangents.taylor_expand(f, params, degree)[source]
Returns a function
f_tayl
, Taylor approximation tof
of orderdegree
.Example
>>> # Compute the MSE of the third order Taylor series of a function. >>> f_tayl = taylor_expand(f, params, 3) >>> mse = jnp.mean((f(new_params, x) - f_tayl(new_params, x)) ** 2)
- Parameters:
f (
ApplyFn
) – A function that we would like to Taylor expand. It should have the signature f(params, *args, **kwargs) where params is a PyTree, and f returns a PyTree.params (
Any
) – Initial parameters to the function that we would like to take the Taylor series about. This can be any structure that is compatible with the JAX tree operations.degree (
int
) – The degree of the Taylor expansion.
- Return type:
- Returns:
A function f_tayl(new_params, *args, **kwargs) whose signature is the same as f. Here f_tayl implements the degree-order taylor series of f about params.