class_docstr: A type alias for a predictor function.
class_docstr_tok: ["A","type","alias","for","a","predictor","function","."]
code: def __call__(
      self,
      t: Optional[ArrayOrScalar] = None,
      fx_train_0: ArrayOrScalar = 0.0,
      fx_test_0: Optional[ArrayOrScalar] = None,
      k_test_train: Optional[jnp.ndarray] = None,
  ) -> Union[jnp.ndarray, tuple[jnp.ndarray, jnp.ndarray]]:
      ...
  
imports: import collections
  from functools import lru_cache
  from typing import Any, Callable, Generator, Iterable, NamedTuple, Optional, Protocol, Union
  import jax
  from jax import grad
  from jax.experimental import ode
  import jax.numpy
  import jax.scipy
  from jax.tree_util import tree_all
  from jax.tree_util import tree_map
  import numpy
  import scipy
  from .utils import dataclasses
  from .utils import utils
  from .utils.typing import Axes
  from .utils.typing import Get
  from .utils.typing import KernelFn
label_desc: Use image node_id 1 for calling the PredictFn obj's underlying member method code with example usage: obj.__call__(t, fx_train_0, fx_test_0, k_test_train) without return types