class_docstr: A type alias for initialization functions.
  
  Initialization functions construct parameters for neural networks given a
  random key and an input shape. Specifically, they produce a tuple giving the
  output shape and a PyTree of parameters.
class_docstr_tok: ["A","type","alias","for","initialization","functions",".","Initialization","functions","construct","parameters","for","neural","networks","given","a","random","key","and","an","input","shape",".","Specifically",",","they","produce","a","tuple","giving","the","output","shape","and","a","PyTree","of","parameters","."]
code: def __call__(
      self, rng: jax.Array, input_shape: Shapes, **kwargs
  ) -> tuple[Shapes, PyTree]:
      ...
  
imports: from typing import Any, Generator, Optional, Protocol, Sequence, TYPE_CHECKING, TypeVar, Union
  import jax
  import jax.numpy
  from .kernel import Kernel
label_desc: Use image node_id 1 for calling the InitFn obj's underlying member method code with example usage: obj.__call__(rng, input_shape) without return types